Density-wave tendency from a topological nodal-line perspective

The understanding of density waves is a vital component of our insight into electronic quantum matters. Here, we propose an additional mosaic to the existing mechanisms such as Fermi-surface nesting, electron–phonon coupling, and exciton condensation. In particular, we find that certain two-dimensional(2D) spin density-wave systems are equivalent to three-dimensional(3D) Dirac nodal-line systems in the presence of a magnetic field, whose electronic structure takes the form of Dirac-fermion Landau levels and allows a straightforward analysis of its optimal filling. The subsequent minimumenergy wave vector varies over a continuous range and shows no direct connection to the original Fermi surfaces in 2D.Also, we carry out numerical calculations where the results on model examples support our theory. Our study points out that we have yet to attain a complete understanding of the emergent density wave formalism.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Association of DNA methylation/demethylation with the functional outcome of stroke in a hyperinflammatory state

Inflammation is closely related to stroke prognosis, and high inflammation status leads to poor functional outcome in stroke. DNA methylation is involved in the pathogenesis and prognosis of stroke. However, the effect of DNA methylation on stroke at high levels of inflammation is unclear. In this study, we constructed a hyperinflammatory cerebral ischemia mouse model and investigated the effect of hypomethylation and hypermethylation on the functional outcome. We constructed a mouse model of transient middle cerebral artery occlusion and treated the mice with lipopolysaccharide to induce a hyperinflammatory state. To investigate the effect of DNA methylation on stroke, we used small molecule inhibitors to restrain the function of key DNA methylation and demethylation enzymes. 2,3,5-Triphenyltetrazolium chloride staining, neurological function scores, neurobehavioral tests, enzyme-linked immunosorbent assay, quantitative reverse transcription PCR and western blot assay were used to evaluate the effects after stroke in mice. We assessed changes in the global methylation status by measuring DNA 5-mc and DNA 5-hmc levels in peripheral blood after the use of the inhibitor. In the group treated with the DNA methylation inhibitor, brain tissue 2,3,5-triphenyltetrazolium chloride staining showed an increase in infarct volume, which was accompanied by a decrease in neurological scores and worsening of neurobehavioral performance. The levels of inflammatory factors interleukin 6 and interleukin-1 beta in ischemic brain tissue and plasma were elevated, indicating increased inflammation. Related inflammatory pathway exploration showed significant overactivation of nuclear factor kappa B. These results suggested that inhibiting DNA methylation led to poor functional outcome in mice with high inflammation following stroke. Further, the effects were reversed by inhibition of DNA demethylation. Our findings suggest that DNA methylation regulates the inflammatory response in stroke and has an important role in the functional outcome of hyperinflammatory stroke.

Whole-process case management effects on mental state and selfcare ability in patients with liver cancer

BACKGROUND Regarding the incidence of malignant tumors in China,the incidence of liver cancer ranks fourth,second only to lung,gastric,and esophageal cancers.The case fatality rate ranks third after lung and cervical cancer.In a previous study,the whole-process management model was applied to patients with breast cancer,which effectively reduced their negative emotions and improved treatment adherence and nursing satisfaction.METHODS In this single-center,randomized,controlled study,60 randomly selected patients with liver cancer who had been admitted to our hospital from January 2021 to January 2022 were randomly divided into an observation group(n=30),who received whole-process case management on the basis of routine nursing mea-sures,and a control group(n=30),who were given routine nursing measures.We compared differences between the two groups in terms of anxiety,depression,the level of hope,self-care ability,symptom distress,sleep quality,and quality of life.RESULTS Post-intervention,Hamilton anxiety scale,Hamilton depression scale,memory symptom assessment scale,and Pittsburgh sleep quality index scores in both groups were lower than those pre-intervention,and the observation group had lower scores than the control group(P<0.05).Herth hope index,self-care ability assessment scale-revision in Chinese,and quality of life measurement scale for patients with liver cancer scores in both groups were higher than those pre-intervention,with higher scores in the observation group compared with the control group(P<0.05).CONCLUSION Whole-process case management can effectively reduce anxiety and depression in patients with liver cancer,alleviate symptoms and problems,and improve the level of hope,self-care ability,sleep quality,and quality of life,as well as provide feasible nursing alternatives for patients with liver cancer.

Preparation of entangledW states based on the cavity QED system

We present a qubit-loss-free(QLF)fusion scheme for generating large-scale atom W states in cavity quantum electrodynamics(QED)system.Compared to the most current fusion schemes which are conditioned on the case where one particle can be extracted from each initial W state to the fusion process,our scheme will access one or two particles from each W state.Based on the atom–cavity-field detuned interaction,three jWin+m+t states can be generated from the jWin,jWim,and jWit states with the help of two auxiliary atoms,and three jWin+m+t+q states can be generated from jWin,jWim,jWit,and a jWiq state with the help of three auxiliary atoms.Comparing the numerical simulations of the resource cost of fusing three small-size W states based on the previous schemes,our fusion scheme seems to be more efficient.This QLF fusion scheme can be generalized to the case of fusing k different or identical particle W states.Furthermore,with no qubit loss,it greatly reduces the number of fusion steps and prepares W states with larger particle numbers.

Entropy variances of pure coherent states in the diffusion channel

Using the operator correspondence of the real and fictious modes in the thermo entangled state representation, wesolve the quantum master equation describing the diffusion channel and obtain the Kraus operator-sum representation ofits analytical solution. we find that the pure coherent states evolve into the new mixed thermal superposed states in thediffusion channel. Also, we investigate the statistical properties of the initial coherent states and their entropy evolutions inthe diffusion channel, and find that the entropy evolutions are only related to the decay time and without the amplitudes ofthe initial coherent states.

Machine-learning-assisted efficient reconstruction of the quantum states generated from the Sagnac polarization-entangled photon source

Neural networks are becoming ubiquitous in various areas of physics as a successful machine learning(ML)technique for addressing different tasks.Based on ML technique,we propose and experimentally demonstrate an efficient method for state reconstruction of the widely used Sagnac polarization-entangled photon source.By properly modeling the target states,a multi-output fully connected neural network is well trained using only six of the sixteen measurement bases in standard tomography technique,and hence our method reduces the resource consumption without loss of accuracy.We demonstrate the ability of the neural network to predict state parameters with a high precision by using both simulated and experimental data.Explicitly,the mean absolute error for all the parameters is below 0.05 for the simulated data and a mean fidelity of 0.99 is achieved for experimentally generated states.Our method could be generalized to estimate other kinds of states,as well as other quantum information tasks.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Topological edge and corner states of valley photonic crystals with zipper-like boundary conditions

We present a stable valley photonic crystal(VPC)unit cell with C_(3v)symmetric quasi-ring-shaped dielectric columns and realize its topological phase transition by breaking mirror symmetry.Based on this unit cell structure,topological edge states(TESs)and topological corner states(TCSs)are realized.We obtain a new type of wave transmission mode based on photonic crystal zipper-like boundaries and apply it to a beam splitter assembled from rectangular photonic crystals(PCs).The constructed beam splitter structure is compact and possesses frequency separation functions.In addition,we construct a box-shaped triangular PC structures with zipper-like boundaries and discover phenomena of TCSs in the corners,comparing its corner states with those formed by other boundaries.Based on this,we explore the regularities of the electric field patterns of TESs and TCSs,explain the connection between the characteristic frequencies and locality of TCSs,which helps better control photons and ensures low power consumption of the system.

Predicted Critical State Based on Invariance of the Lyapunov Exponent in Dual Spaces

Critical states in disordered systems,fascinating and subtle eigenstates,have attracted a lot of research interests.However,the nature of critical states is difficult to describe quantitatively,and in general,it cannot predict a system that hosts the critical state.We propose an explicit criterion whereby the Lyapunov exponent of the critical state should be 0 simultaneously in dual spaces,namely the Lyapunov exponent remains invariant under the Fourier transform.With this criterion,we can exactly predict a one-dimensional quasiperiodic model which is not of self-duality,but hosts a large number of critical states.Then,we perform numerical verification of the theoretical prediction and display the self-similarity of the critical state.Due to computational complexity,calculations are not performed for higher dimensional models.However,since the description of extended and localized states by the Lyapunov exponent is universal and dimensionless,utilizing the Lyapunov exponent of dual spaces to describe critical states should also be universal.Finally,we conjecture that some kind of connection exists between the invariance of the Lyapunov exponent and conformal invariance,which can promote the research of critical phenomena.

Screening of Rodents from Rural Communities of Lagos and Ogun State Nigeria of Lassa Virus RNA

Background: In recent times, there has been an increase in the number of Lassa fever cases resulting from the several episodes of Lassa fever epidemics ravaging Nigeria and other West African countries. The presence of Lassa virus in rodents other than the major reservoir (Mastomys natalensis) has been a public health concern as to the actual burden of the disease. It is therefore of a public health necessity to explore the LASV RNA habouring potential of several species of rodents in endemic as well as non-endemic areas for proper prevention of emergence of outbreaks in non-endemic areas. Objectives: The aim of this study was to detect the presence of LASV RNA in different species of rodents in Ikorodu, Lagos state and Abeokuta, Ogun state. Methods: A total of ninety one (91) rodents were captured from Ikorodu, Lagos State (61 rodents) and Abeokuta, Ogun State (30 rodents), euthanized, bled, and plasma obtained for the detection of LASV RNA by Reverse Transcriptase Polymerase Chain Reaction. Results: A total of 91 rodents consisting of 77 Rattus rattus and 14 Crocidura spp. The S segment of LASV RNA was not in any of the 91 rodents’ plasma samples. Conclusion: The rodents captured within the rural communities of Ikorodu, Lagos State and Abeokuta, Ogun State were found not to habour the LASV RNA. This study is limited by the relatively small sample size. Similar studies should be encouraged both in endemic and non-endemic areas in order to understand the actual burden of Lassa fever as well as put into check future epidemics.

Comparative Study of the Socioeconomic Characteristics and Digital Literacy Level of Agricultural Extension Personnel in Imo and Ebonyi States, South-East, Nigeria

The study comparatively analysed the socioeconomic characteristics and digital literacy level of Agricultural Extension personnel (AEP) in Ebonyi and Imo States, South-East, Nigeria. The specific objectives were to describe the socioeconomic characteristics of agricultural extension personnel in Ebonyi and Imo States, and to ascertain the digital literacy level of AEP in the studied states. Purposive sampling technique was used to select 312 Agricultural Extension personnel (132 from Ebonyi State Agricultural Development Program and 180 from Imo State Agricultural Development Program) for the study. Data were collected through the use of validated and structured questionnaire, and administered through the help of well-trained enumerators. Data were analysed using simple descriptive statistical tools such as percentages mean score, standard deviation and weighted mean. Findings indicated that they were more male in the both States (55.3% and 57.8%) for Ebonyi and Imo State respectively and that the average age of AEP in Ebonyi and Imo States were 44.7 years and 49.2 years respectively. It was further revealed that the majority (77.3% and 82.8%) had B.Sc./HND as their highest academic qualifications, belonged to professional organisations (62.1% and 75%), and were earning an average monthly income of N58,798 and N62,648 for Ebonyi and Imo State respectively. Also, it was revealed that their mean years of service were 12.4 years and 13.4 years for Ebonyi and Imo State respectively. Almost all of them (87.9% and 95.0%) own a smartphone, had access to the internet (80.3% and 90.0%), but do not own a laptop/ipad (82.6% and 72.8%) for Ebon-yi and Imo State respectively. Results further revealed that Agricultural extension personnel in both Ebonyi and Imo State respectively had low digital literacy level ( = 2.41 and 2.32). The study concluded that AEP in Ebonyi and Imo State respectively had similar socioeconomic characteristics and low level of digital literacy. The study recommended that the management of ADPs in both Ebonyi and Imo State should ensure the training of AEP in digital skills to enhance their digital literacy level to enable them use digital technologies in their work.

Pure State Feedback Switching Control Based on the Online Estimated State for Stochastic Open Quantum Systems

For the n-qubit stochastic open quantum systems,based on the Lyapunov stability theorem and LaSalle’s invariant set principle,a pure state switching control based on on-line estimated state feedback(short for OQST-SFC)is proposed to realize the state transition the pure state of the target state including eigenstate and superposition state.The proposed switching control consists of a constant control and a control law designed based on the Lyapunov method,in which the Lyapunov function is the state distance of the system.The constant control is used to drive the system state from an initial state to the convergence domain only containing the target state,and a Lyapunov-based control is used to make the state enter the convergence domain and then continue to converge to the target state.At the same time,the continuous weak measurement of quantum system and the quantum state tomography method based on the on-line alternating direction multiplier(QST-OADM)are used to obtain the system information and estimate the quantum state which is used as the input of the quantum system controller.Then,the pure state feedback switching control method based on the on-line estimated state feedback is realized in an n-qubit stochastic open quantum system.The complete derivation process of n-qubit QST-OADM algorithm is given;Through strict theoretical proof and analysis,the convergence conditions to ensure any initial state of the quantum system to converge the target pure state are given.The proposed control method is applied to a 2-qubit stochastic open quantum system for numerical simulation experiments.Four possible different position cases between the initial estimated state and that of the controlled system are studied and discussed,and the performances of the state transition under the corresponding cases are analyzed.

The 5αcondensate state in 20Ne

Theclustering phenomenon,in which nucleons are arranged intoparticles(4 He nuclei)within a nuclear system,is one of the most intriguing aspects of nuclear structure.It has been observed in various light nuclei,such as^(8)Be,^(12)C,^(16)O,and^(20)Ne,and is responsible for many exotic and fascinating phenomena,such as the Hoyle state in^(12)C,which plays an essential role in stellar nucleosynthesis[1-6]as well as in heavy-ion collisions[7-9].

Dispersive Analysis of Excited Glueball States

Motivated by the determination for the spin-parity quantum numbers of the X(2370)meson at BESⅢ,we extend our dispersive analysis on hadronic ground states to excited states.The idea is to start with the dispersion relation which a correlation function obeys,and subtract the known ground-state contribution from the involved spectral density.

Effects of quantum noise on teleportation of arbitrary two-qubit state via five-particle Brown state

We propose a new protocol for quantum teleportation(QT)which adopts the Brown state as the quantum channel.This work focuses on the teleportation of a single unknown two-qubit state via a Brown state channel in an ideal environment.To validate the effectiveness of our proposed scheme,we conduct experiments by using the quantum circuit simulator Quirk.Furthermore,we investigate the effects of four noisy channels,namely,the phase damping noise,the bit-flip noise,the amplitude damping noise,and the phase-flip noise.Notably,we employ Monte Carlo simulation to elucidate the fidelity density under various noise parameters.Our analysis demonstrates that the fidelity of the protocol in a noisy environment is influenced significantly by the amplitude of the initial state and the noise factor.

Microenvironment and electronic state modulation of Pd nanoparticles within MOFs for enhancing low-temperature activity towards DCPD hydrogenation

Precise control of the local environment and electronic state of the guest is an important method of controlling catalytic activity and reaction pathways.In this paper,guest Pd NPs were introduced into a series of host UiO-67 MOFs with different functional ligands and metal nodes,the microenvironment and local electronic structure of Pd is modulated by introducing bipyridine groups and changing metal nodes(Ce6O6 or Zr6O6).The bipyridine groups not only promoted the dispersion Pd NPs,but also facilitated electron transfer between Pd and UiO-67 MOFs through the formation of Pd-N bridges.Compared with Zr6 clusters,the tunability and orbital hybridisation of the 4f electronic structure in the Ce6 clusters modulate the electronic structure of Pd through the construction of the Ce-O-Pd interfaces.The optimal catalyst Pd/UiO-67(Ce)-bpy presented excellent low-temperature activity towards dicyclopentadiene hydrogenation with a conversion of>99%and a selectivity of>99%(50℃,10 bar).The results show that the synergy of Ce-O-Pd and Pd-N promotes the formation of active Pdδ+,which not only enhances the adsorption of H2 and electron-rich C=C bonds,but also contributes to the reduction of proton migration distance and improves proton utilization efficiency.These results provide valuable insights for investigating the regulatory role of the host MOFs,the nature of host-guest interactions,and their correlation with catalytic performance.

Deep learning for determining pure isotropic proton spectra from solidstate spectra

Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS)rate.This approach even allowed to obtain,by far,the best resolved ^(1)H spectra of molecular solids[1](https://doi.org/10.1002/anie.202216607).Deep learning based artificial intelligence is developing rapidly,and its application is deepening.Currently,there are many applications of deep learning in the field of magnetic resonance,such as the reconstruction of the under-sampled multidimensional spectra[2-4],the deconvolution of two-dimensional NMR spectra[5]and noise suppression and weak peak retrial[6],etc.

Preparation and interface state of phosphate tailing-based geopolymers

The long-term storage of phosphate tailings will occupy a large amount of land,pollute soil and groundwater,thus,it is crucial to achieve the harmless disposal of phosphate tailings.In this study,high-performance geopolymers with compressive strength of 38.8 MPa were prepared by using phosphate tailings as the main raw material,fly ash as the active silicon-aluminum material,and water glass as the alkaline activator.The solid content of phosphate tailings and fly ash was 60% and 40%,respectively,and the water-cement ratio was 0.22.The results of XRD,FTIR,SEM-EDS and XPS show that the reactivity of phosphate tailings with alkaline activator is weak,and the silicon-aluminum material can react with alkaline activator to form zeolite and gel,and encapsulate/cover the phosphate tailings to form a dense phosphate tailings-based geopolymer.During the formation of geopolymers,part of the aluminum-oxygen tetrahedron replaced the silicon-oxygen tetrahedron,causing the polycondensation reaction between geopolymers and increasing the strength of geopolymers.The leaching toxicity test results show that the geopolymer has a good solid sealing effect on heavy metal ions.The preparation of geopolymer from phosphate tailings is an important way to alleviate the storage pressure and realize the resource utilization of phosphate tailings.