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Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for $U(1)_{B-L}$ gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the $U(1)_{B-L}$ gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM., Comment: 20 pages, 5 figures

Considering accretion onto a charged dilaton black hole, the fundamental equations governing accretion, general analytic expressions for critical points, critical velocity, critical speed of sound, and ultimately the mass accretion rate are obtained. A new constraint on the dilation parameter coming from string theory is found and the case for polytropic gas is delved into a detailed discussion. It is found that the dialtion and the adiabatic index of accreted material have deep effects on the accretion process., Comment: 9 pages, 3 figures

We report new experimental results on the search for dark photons based on a near-quantum-limited haloscope equipped with a superconducting cavity. The loaded quality factor of the superconducting cavity is $6\times10^{5}$, so that the expected signal from dark photon dark matter can be enhanced by more than one order compared to a copper cavity. A Josephson parametric amplifier with a near-quantum-limited noise temperature has been utilized to minimize the noise during the search. Furthermore, a digital acquisition card based on field programmable gate arrays has been utilized to maximize data collection efficiency with a duty cycle being 100$\%$. This work has established the most stringent constraints on dark photons at around 26.965 $\mu$eV. In the future, our apparatus can be extended to search for other dark matter candidates, such as axions and axion-like particles, and scrutinize new physics beyond the Standard Model.

Recent years have seen rapid progress in the field of quantum algorithms for linear algebra problems. These algorithms can solve important problems in quantum chemistry, condensed matter physics, and quantum field theory simulation, with potentially exponential speedup compared to classical algorithms. The progress is in part due to the development of new methods to implement matrix functions on a quantum computer. Examples include the linear combination of unitaries (LCU) method, quantum signal processing (QSP), and quantum singular value transformation (QSVT), which is closely related to QSP. Using these methods, one can construct matrix functions to filter out unwanted eigenstates of a given Hermitian matrix, and thereby obtain a target eigenstate on a quantum computer. This technique we call quantum eigenstate filtering.We focus our attention on two specific problems: ground state preparation and energy estimation, and solving linear systems. For the ground state preparation problem, we want to prepare the ground state, i.e., the lowest eigenstate of the Hamiltonian $H$, while for ground state energy estimation, we want to estimate the ground state energy, i.e., the the lowest eigenvalue of the Hamiltonian $H$. The ground state energy estimation problem is cannot be solved in polynomial time even on a quantum computer in the worst case. However, this problem becomes tractable with additional assumptions, which may be satisfied in many real-world applications. In this work we assume access to a good initial guess of the ground state, such that its overlap with the ground state is lower bounded by a parameter $\gamma$. Under this assumption, we present quantum algorithms based on the quantum eigenstate filtering technique to estimate the ground state energy and to prepare the ground state, with nearly optimal scaling with respect to both $\gamma$ and the precision.The above mentioned algorithms work in the setting where the quantum computers are fully fault-tolera

Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.

Studying complex relaxation behaviors is of critical importance for understanding the nature of glasses. Here we report a Kovacs-like memory effect in glasses, manifested by non-monotonic stress relaxation during two-step high-to-low strains stimulations. During the stress relaxation process, if the strain jumps from a higher state to a lower state, the stress does not continue to decrease, but increases first and then decreases. The memory effect becomes stronger when the atomic motions become highly collective with a large activation energy, e.g. the strain in the first stage is larger, the temperature is higher, and the stimulation is longer. The physical origin of the stress memory effect is studied based on the relaxation kinetics and the in-situ synchrotron X-ray experiments. The stress memory effect is probably a universal phenomenon in different types of glasses., Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura, Postprint (published version)

Yong Li,1,2,* Senbo Zhu,2,* Junchao Luo,2 Yu Tong,2 Yixuan Zheng,1 Lichen Ji,2 Zeju He,2 Qiangan Jing,1 Jiaqing Huang,2 Yinjun Zhang,1 Qing Bi2 1College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, 310014, People’s Republic of China; 2Laboratory Medicine Center, Department of Laboratory Medicine, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, 310014, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yinjun Zhang, College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, Zhejiang, 310014, People’s Republic of China, Tel +86-13735494556, Email zhangyj@zjut.edu.cn Qing Bi, Laboratory Medicine Center, Department of Laboratory Medicine, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, 310014, People’s Republic of China, Tel +86-13588302991, Email bqzjsrmyy@163.comIntroduction: Osteoarthritis (OA) is a common chronic joint disease characterized by articular cartilage degeneration. OA usually manifests as joint pain, limited mobility, and joint effusion. Currently, the primary OA treatment is non-steroidal anti-inflammatory drugs (NSAIDs). Although they can alleviate the disease’s clinical symptoms and signs, the drugs have some side effects. Selenium nanoparticles (SeNPs) may be an alternative to relieve OA symptoms.Materials and Results: We confirmed the anti-inflammatory effect of selenium nanoparticles (SeNPs) in vitro and in vivo experiments for OA disease in this study. In vitro experiments, we found that SeNPs could significantly reduce the expression of nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), the major inflammatory factors, and had significant anti-inflammatory and anti-arthritic effects. SeNPs can inhibit reactive oxygen species (ROS) production and increas

We develop a protocol for learning a class of interacting bosonic Hamiltonians from dynamics with Heisenberg-limited scaling. For Hamiltonians with an underlying bounded-degree graph structure, we can learn all parameters with root mean squared error $\epsilon$ using $\mathcal{O}(1/\epsilon)$ total evolution time, which is independent of the system size, in a way that is robust against state-preparation and measurement error. In the protocol, we only use bosonic coherent states, beam splitters, phase shifters, and homodyne measurements, which are easy to implement on many experimental platforms. A key technique we develop is to apply random unitaries to enforce symmetry in the effective Hamiltonian, which may be of independent interest., Comment: 14 pages with 21-page appendix

To simply predict the motion characteristics of a floating ship on the river and assess the safety in floating, this work developed a multiphase fluid-solid coupling solver based on the Volume of Fluid (VoF) model in open-source code OpenFOAM and multi-sphere DEM model in LIGGGHTS. Benchmarks of non-spherical particles settling in the single-phase and two-phase fluids at different Reynolds numbers were studied. The results show that the solver is relatively accurate and can approximately capture the settlement trajectory of particles under different Reynolds numbers. In application, the drift behaviors of a floating ship with different densities were studied. We introduced the hydrodynamic parameters to characterize the mechanical states and evaluate the stability of the drifting boat. We found that the hull weight has a significant influence on the ship drifting motion. Therefore, ship designers can design the ship according to the proposed model to ensure the safety of drifters. © 2022 Elsevier Ltd

Background: Tea trees originated in southwest China 60 million or 70 million years ago. Written records show that Chinese ancestors had begun drinking tea over 3000 years ago. Nowadays, with the aging of populations worldwide and more people suffering from non-communicable diseases or poor health, tea beverages have become an inexpensive and fine complementary and alternative medicine (CAM) therapy. At present, there are 3 billion people who like to drink tea in the world, but few of them actually understand tea, especially on its development process and the spiritual and cultural connotations. Methods: We searched PubMed, Google Scholar, Web of Science, CNKI, and other relevant platforms with the key word “tea”, and reviewed and analyzed tea-related literatures and pictures in the past 40 years about tea’s history, culture, customs, experimental studies, and markets. Results: China is the hometown of tea, tea trees, tea drinking, and tea culture. China has the oldest wild and planted tea trees in the world, fossil of a tea leaf from 35,400,000 years ago, and abundant tea-related literatures and art works. Moreover, tea may be the first Chinese herbal medicine (CHM) used by Chinese people in ancient times. Tea drinking has many benefits to our physical health via its antioxidant, anti-inflammatory, immuno-regulatory, anticancer, cardiovascular-protective, anti-diabetic, and anti-obesity activities. At the moment, COVID-19 is wreaking havoc across the globe and causing severe damages to people’s health and lives. Tea has anti-COVID-19 functions via the enhancement of the innate immune response and inhibition of viral growth. Besides, drinking tea can allow people to acquire a peaceful, relaxed, refreshed and cheerful enjoyment, and even longevity. According to the meridian theory of traditional Chinese medicine, different kinds of tea can activate different meridian systems in the human body. At present, black tea (fermented tea) and green tea (non-fermented tea) are

We prove an entanglement area law for a class of 1D quantum systems involving infinite-dimensional local Hilbert spaces. This class of quantum systems include bosonic models such as the Hubbard-Holstein model, and both U(1) and SU(2) lattice gauge theories in one spatial dimension. Our proof relies on new results concerning the robustness of the ground state and spectral gap to the truncation of Hilbert space, applied within the approximate ground state projector (AGSP) framework from previous work. In establishing this area law, we develop a system-size independent bound on the expectation value of local observables for Hamiltonians without translation symmetry, which may be of separate interest. Our result provides theoretical justification for using tensor network methods to study the ground state properties of quantum systems with infinite local degrees of freedom.

We consider the accretion process in the thin disk around a supermassive black hole in Einstein-aether-scalar theory. We probe the effects of the model parameter on the physical properties of the disk. The results show that with increasing value of the parameter, the energy flux, the radiation temperature, the spectra cut-off frequency, the spectra luminosity, and the conversion efficiency of the disk decrease. The disk is hotter and more luminous than that in general relativity for negative parameter, while it is cooler and less luminous for positive parameter. We also find some values of the parameter allowed by the theory are excluded by the physical properties of the disk., Comment: 9 pages, 6 figures, 1 table, some errors are corrected

Under suitable assumptions, some recently developed quantum algorithms can estimate the ground-state energy and prepare the ground state of a quantum Hamiltonian with near-optimal query complexities. However, this is based on a block-encoding input model of the Hamiltonian, the implementation of which is known to require a large resource overhead. We develop a tool called quantum eigenvalue transformation of unitary matrices with real polynomials (QETU), which uses a controlled Hamiltonian evolution as the input model, a single ancilla qubit, and no multiqubit control operations and is thus suitable for early fault-tolerant quantum devices. This leads to a simple quantum algorithm that outperforms all previous algorithms with a comparable circuit structure for estimating the ground-state energy. For a class of quantum spin Hamiltonians, we propose a new method that exploits certain anticommutation relations and further removes the need to implement the controlled Hamiltonian evolution. Coupled with a Trotter-based approximation of the Hamiltonian evolution, the resulting algorithm can be very suitable for early fault-tolerant quantum devices. We demonstrate the performance of the algorithm using IBM qiskit for the transverse-field Ising model. If we are further allowed to use multiqubit Toffoli gates, we can then implement amplitude amplification and a new binary amplitude-estimation algorithm, which increases the circuit depth but decreases the total query complexity. The resulting algorithm saturates the near-optimal complexity for ground-state preparation and energy estimation using a constant number of ancilla qubits (no more than three).

Quantum dynamics can be simulated on a quantum computer by exponentiating elementary terms from the Hamiltonian in a sequential manner. However, such an implementation of Trotter steps has gate complexity depending on the total Hamiltonian term number, comparing unfavorably to algorithms using more advanced techniques. We develop methods to perform faster Trotter steps with complexity sublinear in the number of terms. We achieve this for a class of Hamiltonians whose interaction strength decays with distance according to power law. Our methods include one based on a recursive block encoding and one based on an average-cost simulation, overcoming the normalization-factor barrier of these advanced quantum simulation techniques. We also realize faster Trotter steps when certain blocks of Hamiltonian coefficients have low rank. Combining with a tighter error analysis, we show that it suffices to use $\left(\eta^{1/3}n^{1/3}+\frac{n^{2/3}}{\eta^{2/3}}\right)n^{1+o(1)}$ gates to simulate uniform electron gas with $n$ spin orbitals and $\eta$ electrons in second quantization in real space, asymptotically improving over the best previous work. We obtain an analogous result when the external potential of nuclei is introduced under the Born-Oppenheimer approximation. We prove a circuit lower bound when the Hamiltonian coefficients take a continuum range of values, showing that generic $n$-qubit $2$-local Hamiltonians with commuting terms require at least $\Omega(n^2)$ gates to evolve with accuracy $\epsilon=\Omega(1/poly(n))$ for time $t=\Omega(\epsilon)$. Our proof is based on a gate-efficient reduction from the approximate synthesis of diagonal unitaries within the Hamming weight-$2$ subspace, which may be of independent interest. Our result thus suggests the use of Hamiltonian structural properties as both necessary and sufficient to implement Trotter steps with lower gate complexity., Comment: 69 pages, 7 figures. Tightened gate complexity analysis with no amplitude amplification prefactors. Discussed ancilla space complexity. Added master theorem analysis of the recursive low-rank algorithm. Enhanced version of the article published in PRX Quantum at https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.4.020323

Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics. In this work, we propose the first algorithm to achieve the Heisenberg limit for learning an interacting $N$-qubit local Hamiltonian. After a total evolution time of $\mathcal{O}(\epsilon^{-1})$, the proposed algorithm can efficiently estimate any parameter in the $N$-qubit Hamiltonian to $\epsilon$-error with high probability. The proposed algorithm is robust against state preparation and measurement error, does not require eigenstates or thermal states, and only uses $\mathrm{polylog}(\epsilon^{-1})$ experiments. In contrast, the best previous algorithms, such as recent works using gradient-based optimization or polynomial interpolation, require a total evolution time of $\mathcal{O}(\epsilon^{-2})$ and $\mathcal{O}(\epsilon^{-2})$ experiments. Our algorithm uses ideas from quantum simulation to decouple the unknown $N$-qubit Hamiltonian $H$ into noninteracting patches, and learns $H$ using a quantum-enhanced divide-and-conquer approach. We prove a matching lower bound to establish the asymptotic optimality of our algorithm., Comment: 11 pages, 1 figure + 27-page appendix

The time-marching strategy, which propagates the solution from one time step to the next, is a natural strategy for solving time-dependent differential equations on classical computers, as well as for solving the Hamiltonian simulation problem on quantum computers. For more general linear differential equations, a time-marching based quantum solver can suffer from exponentially vanishing success probability with respect to the number of time steps and is thus considered impractical. We solve this problem by repeatedly invoking a technique called the uniform singular value amplification, and the overall success probability can be lower bounded by a quantity that is independent of the number of time steps. The success probability can be further improved using a compression gadget lemma. This provides a path of designing quantum differential equation solvers that is alternative to those based on quantum linear systems algorithms (QLSA). We demonstrate the performance of the time-marching strategy with a high-order integrator based on the truncated Dyson series. The complexity of the algorithm depends linearly on the amplification ratio, which quantifies the deviation from a unitary dynamics. We prove that the linear dependence on the amplification ratio attains the query complexity lower bound and thus cannot be improved in the worst case. This algorithm also surpasses existing QLSA based solvers in three aspects: (1) the coefficient matrix $A(t)$ does not need to be diagonalizable. (2) $A(t)$ can be non-smooth, and is only of bounded variation. (3) It can use fewer queries to the initial state. Finally, we demonstrate the time-marching strategy with a first-order truncated Magnus series, while retaining the aforementioned benefits. Our analysis also raises some open questions concerning the differences between time-marching and QLSA based methods for solving differential equations., Comment: 45 pages, 6 figures

Real-time monitoring of wound healing remains a major challenge in clinical tissue regeneration, calling the need for the development of biomaterial-guided on-site monitoring wound healing technology. In this study, multifunctional double colorimetry-integrated polyacrylamide-quaternary ammonium chitosan-carbon quantum dots (CQDs)-phenol red hydrogels are presented, aiming to simultaneously detect the wound pH level, reduce bacterial infection, and promote wound healing. The hybridization of CQDs and pH indicator (phenol red) with the hydrogels enables their high responsiveness, reversibility, and accurate indication of pH variability to reflect the dynamic wound status in the context of both ultraviolet and visible light. Furthermore, these visual images can be collected by smartphones and converted into on-site wound pH signals, allowing for a real-time evaluation of the wound dynamic conditions in a remote approach. Notably, the hydrogels exhibit excellent hemostatic and adhesive properties, maintain sufficient wound moisture, and promote wound healing via their high antibacterial activity (against Staphylococcus Aureus, and Escherichia Coli) and skin repair function. Overall, the resulting hydrogels have high potential as a novel smart and flexible wound dressing platform for theranostic skin regeneration.

Quantum many-body systems involving bosonic modes or gauge fields have infinite-dimensional local Hilbert spaces which must be truncated to perform simulations of real-time dynamics on classical or quantum computers. To analyze the truncation error, we develop methods for bounding the rate of growth of local quantum numbers such as the occupation number of a mode at a lattice site, or the electric field at a lattice link. Our approach applies to various models of bosons interacting with spins or fermions, and also to both abelian and non-abelian gauge theories. We show that if states in these models are truncated by imposing an upper limit $\Lambda$ on each local quantum number, and if the initial state has low local quantum numbers, then an error at most $\epsilon$ can be achieved by choosing $\Lambda$ to scale polylogarithmically with $\epsilon^{-1}$, an exponential improvement over previous bounds based on energy conservation. For the Hubbard-Holstein model, we numerically compute a bound on $\Lambda$ that achieves accuracy $\epsilon$, obtaining significantly improved estimates in various parameter regimes. We also establish a criterion for truncating the Hamiltonian with a provable guarantee on the accuracy of time evolution. Building on that result, we formulate quantum algorithms for dynamical simulation of lattice gauge theories and of models with bosonic modes; the gate complexity depends almost linearly on spacetime volume in the former case, and almost quadratically on time in the latter case. We establish a lower bound showing that there are systems involving bosons for which this quadratic scaling with time cannot be improved. By applying our result on the truncation error in time evolution, we also prove that spectrally isolated energy eigenstates can be approximated with accuracy $\epsilon$ by truncating local quantum numbers at $\Lambda=\textrm{polylog}(\epsilon^{-1})$.

A larger portion of fake news quotes untampered images from other sources with ulterior motives rather than conducting image forgery. Such elaborate engraftments keep the inconsistency between images and text reports stealthy, thereby, palm off the spurious for the genuine. This paper proposes an architecture named News Image Steganography (NIS) to reveal the aforementioned inconsistency through image steganography based on GAN. Extractive summarization about a news image is generated based on its source texts, and a learned steganographic algorithm encodes and decodes the summarization of the image in a manner that approaches perceptual invisibility. Once an encoded image is quoted, its source summarization can be decoded and further presented as the ground truth to verify the quoting news. The pairwise encoder and decoder endow images of the capability to carry along their imperceptible summarization. Our NIS reveals the underlying inconsistency, thereby, according to our experiments and investigations, contributes to the identification accuracy of fake news that engrafts untampered images.

With the prevailing of live video streaming, establishing an online pixelation method for privacy-sensitive objects is an urgency. Caused by the inaccurate detection of privacy-sensitive objects, simply migrating the tracking-by-detection structure into the online form will incur problems in target initialization, drifting, and over-pixelation. To cope with the inevitable but impacting detection issue, we propose a novel Privacy-sensitive Objects Pixelation (PsOP) framework for automatic personal privacy filtering during live video streaming. Leveraging pre-trained detection networks, our PsOP is extendable to any potential privacy-sensitive objects pixelation. Employing the embedding networks and the proposed Positioned Incremental Affinity Propagation (PIAP) clustering algorithm as the backbone, our PsOP unifies the pixelation of discriminating and indiscriminating pixelation objects through trajectories generation. In addition to the pixelation accuracy boosting, experiments on the streaming video data we built show that the proposed PsOP can significantly reduce the over-pixelation ratio in privacy-sensitive object pixelation.

Preparing the ground state of a given Hamiltonian and estimating its ground energy are important but computationally hard tasks. However, given some additional information, these problems can be solved efficiently on a quantum computer. We assume that an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and the first excited energy is bounded from below. With these assumptions we design an algorithm that prepares the ground state when an upper bound of the ground energy is known, whose runtime has a logarithmic dependence on the inverse error. When such an upper bound is not known, we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on the desired precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019]. These two algorithms can then be combined to prepare a ground state without knowing an upper bound of the ground energy. We also prove that our algorithms reach the complexity lower bounds by applying it to the unstructured search problem and the quantum approximate counting problem.

In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese. CLUENER2020 contains 10 categories. Apart from common labels like person, organization, and location, it contains more diverse categories. It is more challenging than current other Chinese NER datasets and could better reflect real-world applications. For comparison, we implement several state-of-the-art baselines as sequence labeling tasks and report human performance, as well as its analysis. To facilitate future work on fine-grained NER for Chinese, we release our dataset, baselines, and leader-board., Comment: 6 pages, 5 tables, 1 figure

Preconditioning is the most widely used and effective way for treating ill-conditioned linear systems in the context of classical iterative linear system solvers. We introduce a quantum primitive called fast inversion, which can be used as a preconditioner for solving quantum linear systems. The key idea of fast inversion is to directly block-encode a matrix inverse through a quantum circuit implementing the inversion of eigenvalues via classical arithmetics. We demonstrate the application of preconditioned linear system solvers for computing single-particle Green's functions of quantum many-body systems, which are widely used in quantum physics, chemistry, and materials science. We analyze the complexities in three scenarios: the Hubbard model, the quantum many-body Hamiltonian in the planewave-dual basis, and the Schwinger model. We also provide a method for performing Green's function calculation in second quantization within a fixed particle manifold and note that this approach may be valuable for simulation more broadly. Besides solving linear systems, fast inversion also allows us to develop fast algorithms for computing matrix functions, such as the efficient preparation of Gibbs states. We introduce two efficient approaches for such a task, based on the contour integral formulation and the inverse transform respectively.

Yin Zhang,1,2 Xinji Chen,1 Yu Tong,3 Junchao Luo,3 Qing Bi1,2 1Department of Orthopedic Surgery, Zhejiang Provincial People’s Hospital and People’s Hospital of Hangzhou Medical College, Hangzhou, Zhejiang 310014, People’s Republic of China; 2The First Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui 233004, People’s Republic of China; 3The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325000, People’s Republic of ChinaCorrespondence: Qing BiDepartment of Orthopedic Surgery, Zhejiang Provincial People’s Hospital, No. 158 Shangtang Road, Hangzhou, Zhejiang, People’s Republic of ChinaEmail bqzjsrmyy@163.comAbstract: Osteoarthritis (OA) is a common degenerative disease that affects the vast majority of the elderly and may eventually embark on the road of the total knee arthroplasty (TKA), although controversy still exists in the medical community about the best therapies for osteoarthritis. Compared with physical therapy, oral analgesics and other non-operative treatments, intra-articular injection is more safe and effective. Moreover, intra-articular injection is much less invasive and has fewer adverse reactions than surgical treatment. This article reviews mechanism, benefits and adverse reactions of corticosteroids (CS), hyaluronic acid (HA), platelet-rich plasma (PRP), mesenchymal stem cell (MSCs), stromal vascular fraction (SVF) and other new therapies (for example: gene therapy). The application prospect of intra-articular injection was analyzed according to the recent progress in drug research.Keywords: osteoarthritis, intra-articular injection, treatment, prospect, review

We present a quantum eigenstate filtering algorithm based on quantum signal processing (QSP) and minimax polynomials. The algorithm allows us to efficiently prepare a target eigenstate of a given Hamiltonian, if we have access to an initial state with non-trivial overlap with the target eigenstate and have a reasonable lower bound for the spectral gap. We apply this algorithm to the quantum linear system problem (QLSP), and present two algorithms based on quantum adiabatic computing (AQC) and quantum Zeno effect respectively. Both algorithms prepare the final solution as a pure state, and achieves the near optimal $\mathcal{\widetilde{O}}(d\kappa\log(1/\epsilon))$ query complexity for a $d$-sparse matrix, where $\kappa$ is the condition number, and $\epsilon$ is the desired precision. Neither algorithm uses phase estimation or amplitude amplification.

Tensor network operators, such as the matrix product operator (MPO) and the projected entangled-pair operator (PEPO), can provide efficient representation of certain linear operators in high dimensional spaces. This paper focuses on the efficient representation of tensor network operators with long-range pairwise interactions such as the Coulomb interaction. For MPOs, we find that all existing efficient methods exploit a peculiar "upper-triangular low-rank" (UTLR) property, i.e. the upper-triangular part of the matrix can be well approximated by a low-rank matrix, while the matrix itself can be full-rank. This allows us to convert the problem of finding the efficient MPO representation into a matrix completion problem. We develop a modified incremental singular value decomposition method (ISVD) to solve this ill-conditioned matrix completion problem. This algorithm yields equivalent MPO representation to that developed in [Stoudenmire and White, Phys. Rev. Lett. 2017]. In order to efficiently treat more general tensor network operators, we develop another strategy for compressing tensor network operators based on hierarchical low-rank matrix formats, such as the hierarchical off-diagonal low-rank (HODLR) format, and the $\mathcal{H}$-matrix format. Though the pre-constant in the complexity is larger, the advantage of using the hierarchical low-rank matrix format is that it is applicable to both MPOs and PEPOs. For the Coulomb interaction, the operator can be represented by a linear combination of $\mathcal{O}(\log(N)\log(N/\epsilon))$ MPOs/PEPOs, each with a constant bond dimension, where $N$ is the system size and $\epsilon$ is the accuracy of the low-rank truncation. Neither the modified ISVD nor the hierarchical low-rank algorithm assumes that the long-range interaction takes a translation-invariant form.

Wan-Wei Wang,1 Xi-Lei Zhou,1 Ying-Jian Song,2 Chang-Hua Yu,1 Wei-Guo Zhu,1 Yu-Suo Tong1 1Department of Radiation Oncology, Huai’an First People’s Hospital, Nanjing Medical University, Huai’an, Jiangsu, China; 2Department of Respiratory Medicine, Huai’an First People’s Hospital, Nanjing Medical University, Huai’an, Jiangsu, China Purpose: Long noncoding RNAs (lncRNAs) are present in body fluids, but their potential as tumor biomarkers has never been investigated in malignant pleural effusion (MPE) caused by lung cancer. The aim of this study was to assess the clinical significance of lncRNAs in pleural effusion, which could potentially serve as diagnostic and predictive markers for lung cancer-associated MPE (LC-MPE). Patients and methods: RNAs from pleural effusion were extracted in 217 cases of LC-MPE and 132 cases of benign pleural effusion (BPE). Thirty-one lung cancer-associated lncRNAs were measured using quantitative real-time polymerase chain reaction (qRT-PCR). The level of carcinoembryonic antigen (CEA) was also determined. The receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were established to evaluate the sensitivity and specificity of the identified lncRNAs and other biomarkers. The correlations between baseline pleural effusion lncRNAs expression and response to chemotherapy were also analyzed. Results: Three lncRNAs (MALAT1, H19, and CUDR) were found to have potential as diagnostic markers in LC-MPE. The AUCs for MALAT1, H19, CUDR, and CEA were 0.891, 0.783, 0.824, and 0.826, respectively. Using a logistic model, the combination of MALAT1 and CEA (AUC, 0.924) provided higher sensitivity and accuracy in predicting LC-MPE than CEA (AUC, 0.826) alone. Moreover, baseline MALAT1 expression in pleural fluid was inversely correlated with chemotherapy response in patients with LC-MPE. Conclusion: Pleural effusion lncRNAs were effective in differentiating LC-MPE fr

Hao-jie Zhang,1,2 Jing Tao,1 Lu Sheng,1 Xin Hu,3 Rui-ming Rong,2 Ming Xu,2 Tong-yu Zhu2 1Department of Urology, Huadong Hospital, Fudan University, Shanghai, People’s Republic of China; 2Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 3Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Shanghai, People’s Republic of China Abstract: Twist2 is a member of the basic helix-loop-helix (bHLH) family and plays a critical role in tumorigenesis. Growing evidence has proven that Twist2 is involved in tumor progression; however, the role of Twist2 in human kidney cancer and its underlying mechanisms remain unclear. Real-time polymerase chain reaction and Western blot analysis were used to detect the expression of Twist2 in kidney cancer cells and tissues. Cell proliferation, cell cycle, apoptosis, migration, and invasion assay were analyzed using the Cell Count Kit-8, flow cytometry, wound healing, and Transwell analysis, respectively. In this study, we showed that Twist2 was upregulated in human kidney cancer tissues compared with normal kidney tissues. Twist2 promoted cell proliferation, inhibited cell apoptosis, and augmented cell migration and invasion in human kidney-cancer-derived cells in vitro. Twist2 also promoted tumor growth in vivo. Moreover, we found that the knockdown of Twist2 decreased the levels of ITGA6 and CD44 expression. This result indicates that Twist2 may promote migration and invasion of kidney cancer cells by regulating ITGA6 and CD44 expression. Therefore, our data demonstrated that Twist2 is involved in kidney cancer progression. The identification of the role of Twist2 in the migration and invasion of kidney cancer provides a potential appropriate treatment for human kidney cancer. Keywords: kidney cancer, Twist2, ITGA6, CD44

Wei-Wei Tang,1,* Qingquan Wu,3,* Su-Qing Li,1 Yu-Suo Tong,1 Zi-Hao Liu,1 Tong-Xin Yang,1 Yong Xu,1,2 Xiu-Feng Cao1 1Department of Surgical Oncology, Nanjing First Hospital, 2Cancer Center, Nanjing Medical University, Nanjing, People’s Republic of China; 3Department of Cardiothoracic Surgery, Huaian No 1 People’s Hospital, Affiliated to Nanjing Medical University, Nanjing, People’s Republic of China *Indicates both are first authors Abstract: Long non-coding RNAs (lncRNAs), transcripts as longer than 200 nt in length with a great number of varieties in human genomics, play important roles in the regulation of genetics and epigenetics including gene transcription and post-transcription. Increasing evidence have demonstrated the upregulation of lncRNAs in tumorigenesis and metastasis of esophageal cancer (EC), a type of malignant tumors particularly in Asia. In this review, we briefly discuss the profiles and functions of lncRNAs involved in the progression of EC, which may provide a new approach to improve EC diagnosis and treatment. Keywords: long non-coding RNAs, esophageal cancer, biomarker, review

As a cornerstone of open innovations' success, the work of external search has been altered by the advancement in information technologies (ITs). This study depicts the IT-induced evolution of open search patterns in two case firms. While three patterns were observed in both firms, they took different trajectories of open search pattern change due to the different enabling roles of ITs. ITs were found to serve as an amplifier and a catalyst to induce different trajectories. This study contributes to the literature by unveiling the process of open search evolution including identifying different open search patterns and the roles of ITs. The managerial lessons learned from the two case firms can be applied by other firms.

Nowadays there is an increasing trend of leveraging on external knowledge for innovation, which is termed as open innovation. While open innovation can help organizations obtain complementary knowledge from collaborators, it is likely to have inherent challenges in knowledge absorption. The differences of interorganizational knowledge can seriously inhibit the ability of the focal organization to innovate via external knowledge. While the concept of open innovation has attracted significant attention, there remains a paucity of research on how information technology (IT) can address the knowledge absorption challenges. Drawing on absorptive capacity and organizational learning literature, this study examines the effects of interorganizational knowledge distance on organizational open innovation performance and different influential roles of four IT-enabled knowledge capabilities. Our study contributes to existing research by focusing on the interplay of knowledge distance and IT-enabled knowledge capabilities. Results of the study will also have important managerial implications for open innovation practitioners.

Hypoxia-ischemia (HI) occurring in immature brains stimulates the expression of tissue-type plasminogen activator (tPA). Neuroserpin is a selected inhibitor of tPA in the central nerves system. However, the role that neuroserpin plays and the possible mechanisms involved during neonatal HI are poorly defined. In this study, an oxygen-glucose deprivation and reoxygenation (OGD/R) model was generated with cultured rat cortical neurons mimicking neonatal HI injury ex vivo, and an acute neuronal excitatory injury was induced by exposure to a high concentration of N-methyl-D-aspartic acid (NMDA). Cells received either neuroserpin or MK-801, an antagonist of the NMDA receptor, during OGD/R, and were incubated with or without neuroserpin after NMDA exposure. Cell viability and morphology were detected by a Cell Counting Kit-8 and immunohistochemical staining, respectively. TPA expression and activity were also assessed. We found that MK-801 alleviated injuries induced by OGD/R, suggesting an excitatory damage involvement. Neuroserpin provided a dose-dependent neuroprotective effect in both OGD/R and acute excitatory injuries by inhibiting the activity of tPA, without affecting neuronal tPA expression. Neuroserpin protected neurons against OGD/R even after a delayed administration of 3h. Collectively, our data indicate that neuroserpin protects neurons against OGD/R. mainly by inhibiting tPA-mediated acute neuronal excitotoxicity.

The use of crack growth analysis tools based on plasticity-induced crack closure model, such as FASTRAN, CGAP and AFGROW, requires the conversion of crack growth rate versus the nominal stress intensity range curves to a 'single' curve of crack growth rate versus the effective stress intensity range. In order to minimise the error arising from crack growth rate conversion and judicially utilise these software tools, a user-friendly tool was integrated into CGAP. This report documents the theory, implementation, the user guide and examples of the crack growth rate conversion software module., The original document contains color images.

Prenatal diagnosis is an established obstetrics practice in many countries. Currently available methods to obtain fetal materials for a definitive diagnosis involve invasive procedures such as chorionic villus sampling and amniocentesis. Due to the invasive nature of the procedures, confirmatory testing is usually recommended only for pregnant women who are screened as being high risk of bearing a fetus with abnormalities. There has been an urge to develop safer alternatives in obtaining fetal genetic materials for prenatal assessment. Thus, the discovery of circulating fetal DNA in maternal plasma and serum has opened up new possibilities for noninvasive prenatal diagnosis., The use of genetic markers such as Y chromosomal sequences from a male fetus or paternally-inherited polymorphic markers has been well-described in the literature. However, there is an obvious limitation on the use of these markers because they are gender- and/or polymorphism-dependent. This thesis focuses on the development of a universal fetal marker, namely SERPINB5 (encoding maspin), based on the intrinsic epigenetic differences between the placenta (the major contributor of fetal genetic materials in maternal plasma) and maternal blood cells (postulated to be the predominant source of cell-free DNA in the circulation). Analysis of the methylation profile of the SERPINB5 promoter in the placenta and maternal blood cells, and the development of methods and protocols to detect the differentially methylated SERPINB5 promoter molecules are described. The application of this epigenetic marker in prenatal assessment of the fetal chromosomal aneuploidy is illustrated by an epigenetic allelic ratio (EAR) approach. Basically, the ratio of a single-nucleotide polymorphism (SNP) on the placenta-derived SERPINB5 molecules is shown to be deviated in the maternal plasma from trisomic pregnancies when compared to the euploid ones. Results described in this thesis show the promising potential for the EAR approach for the noninvasive prenatal detection of fetal chromosomal aneuploidies. In addition, a novel approach for methylation analyses on the amplification and detection of restriction enzyme-digested DNA fragments will be discussed. This thesis has essentially described the evolution of a fetal epigenetic marker from basic science to potential clinical application., Tong, Yu Kwan., Adviser: Yuk-Ming Dennis Lo., Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 0953., Thesis (Ph.D.)--Chinese University of Hong Kong, 2007., Includes bibliographical references (leaves 149-172)., Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web., Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web., also in Chinese., School code: 1307., isbn: 9780549480815, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Centimeter-long strands of well-aligned single-walled carbon nanotubes (SWNT) synthesized by a hydrogen-argon arc discharge method were employed for the investigation of their field emission properties. These macroscopically long aligned SWNT strands showed advantages of low turn on electric field, high current density, good emission stability, and easy manipulation over the disoriented SWNT samples. The field enhancement factor of the strand is basically linearly proportional to its macro aspect ratio when the microstructure of the emission tip is kept unchanged. The present SWNT strands can be valuable candidates for the applications as electron-emitting sources in various electronic devices.

Aircraft structural risk and reliability analysis has gained considerable interest in the area of aircraft structural integrity and fleet management in recent times. In this report, a literature review of the current approaches and methodologies that have been utilised in the area of structural risk and reliability analysis for aircraft structures and components is conducted. The structural risk and reliability approach discussed here deals mainly with the probability of failure due to aircraft structural fatigue. It reviews the engineering techniques and probabilistic methodologies that have been reported in the literature. It also discuss the advantages, disadvantage and the limitations of this approach and the reason for its need in aircraft structural and component integrity. The application of structural risk and reliability analysis is not limited to structural fatigue problem, its implication in areas other than airframe and component fatigue are also presented. This review shows that risk and reliability analysis can be a very useful tool for fleet management and it has potential implications for structural design.

Esophageal cancers have a unique geographical distribution yet contribute to cancer mortality worldwide. There is an important relationship between genetic factors and the development of cancers. While loss of heterozygosity (LOH), mutations, deletions, and amplifications of genes are reported for esophageal cancers, functional evidence for the involvement of chromosomal regions in this cancer is still lacking. Microcell-mediated chromosome transfer (MMCT) is a powerful functional approach to study the involvement of tumor suppressor genes (TSGs) in cancers. The introduction of a normal copy of certain chromosomes has been observed to have tumor suppressive effects on various cancer cell lines. In this project, MMCT was employed to investigate the effects of the introduction of normal intact copies of chromosomes 3 and 17 into the esophageal carcinoma cell line T.Tn. Tumorigenicity assays for hybrid clones obtained from transferring intact and different deletion fragments of the two chromosomes showed variable results. After thorough investigation, the parental recipient cell line T.Tn was found to contain a mixed population of highly tumorigenic cells and non-tumorigenic cells. Hence the observed suppression of tumor growth in vivo of the hybrid clones may have been caused by this heterogeneity. Only results from the few tumorigenic clones were clearly reliable. Microsatellite analysis of the recipient and donor cell lines, and the hybrids and their tumor segregants showed a frequent loss of regions of donor chromosomes in the hybrid clones with a strong selection pressure for clones able to expand in vitro. Two regions on each of those two chromosomes (3p24.2-22 and 3q27 on chromosome 3; 17p13.1 and 17q11.2-12 on chromosome 17) may play an important role in cell growth properties in vitro and/or in vivo.

Tong Yu Chung., Thesis (M.Phil.)--Chinese University of Hong Kong, 1997., Includes bibliographical references., p.i, Acknowledgments --- p.ii, Table of Contents --- p.iii, Chapter (1) --- Introduction --- p.1, Chapter 1.1 --- Background --- p.1, Chapter 1.2 --- Overview of the Thesis --- p.2, References --- p.4, Chapter (2) --- Review of Ultrashort Pulse Generation and Pulsewidth Measurement --- p.5, Chapter 2.1 --- Introduction --- p.5, Chapter 2.2 --- Q-switching --- p.5, Chapter 2.3 --- Gain-switching --- p.8, Chapter 2.4 --- Mode-locking --- p.11, Chapter 2.4.1 --- Active mode-locking --- p.12, Chapter 2.4.2 --- Passive mode-locking --- p.13, Chapter 2.5 --- Optical Pulse Compression --- p.15, Chapter 2.6 --- Pulsewidth Detection Methods --- p.18, Chapter 2.6.1 --- Streak camera --- p.18, Chapter 2.6.2 --- Photodetector and sampling oscilloscope --- p.20, Chapter 2.6.3 --- Nonlinear autocorrelator --- p.21, Chapter 2.6.4 --- Other techniques --- p.24, References --- p.25, Chapter (3) --- Erbium Doped Fiber Amplifier and Active Mode-locking --- p.28, Chapter 3.1 --- Introduction --- p.28, Chapter 3.2 --- Erbium Doped Fiber Amplifier --- p.28, Chapter 3.2.1 --- Background --- p.28, Chapter 3.2.2 --- Experiment --- p.31, Chapter 3.3 --- Additive Pulse Mode-locking --- p.35, Chapter 3.4 --- Active Mode-locking --- p.37, Chapter 3.4.1 --- Background --- p.37, Chapter 3.4.2 --- Experiment and result --- p.38, Chapter 3.4.3 --- Discussion --- p.43, Chapter 3.5 --- Chapter Summary --- p.46, References --- p.46, Chapter (4) --- Passive Mode-locking of Erbium Doped Fiber Laser --- p.49, Chapter 4.1 --- Introduction --- p.49, Chapter 4.2 --- Background --- p.49, Chapter 4.3 --- Experimental Setup --- p.51, Chapter 4.4 --- Initialing Mode-locking --- p.54, Chapter 4.5 --- Experimental Result --- p.55, Chapter 4.5.1 --- Real time pulse train --- p.55, Chapter 4.5.2 --- Autocorrelation trace --- p.57, Chapter 4.5.3 --- RF spectrum --- p.58, Chapter 4.5.4 --- Optical spectrum --- p.59, Chapter 4.5.5 --- Time-bandwidth product --- p.60, Chapter 4.5.6 --- Output power --- p.61, Chapter 4.6 --- Discussion --- p.63, Chapter 4.6.1 --- Linear pulse broadening --- p.63, Chapter 4.6.2 --- Cavity oscillation --- p.65, Chapter 4.6.3 --- Pump power hysteresis --- p.66, Chapter 4.6.4 --- Sideband generation --- p.67, Chapter 4.6.5 --- Spectral distortion --- p.68, Chapter 4.7 --- Chapter Summary --- p.71, References --- p.72, Chapter (5) --- Application of Ultrashort Optical Pulses from Figure Eight Laser --- p.74, Chapter 5.1 --- Introduction --- p.74, Chapter 5.2 --- Dispersion Measurement --- p.74, Chapter 5.2.1 --- Introduction --- p.74, Chapter 5.2.2 --- Background --- p.75, Chapter 5.2.3 --- Experiment and result --- p.76, Chapter 5.2.4 --- Discussion and conclusion --- p.80, Chapter 5.3 --- Time Domain Spectral Estimation --- p.82, Chapter 5.3.1 --- Introduction --- p.82, Chapter 5.3.2 --- Background --- p.82, Chapter 5.3.3 --- Experiment and result --- p.83, Chapter 5.3.4 --- Discussion --- p.88, Chapter 5.4 --- Ultrashort Pulse Amplification --- p.89, Chapter 5.4.1 --- Introduction --- p.89, Chapter 5.4.2 --- Background --- p.89, Chapter 5.4.3 --- Experiment and result --- p.92, Chapter 5.4.4 --- Discussion and conclusion --- p.95, References --- p.96, Chapter (6) --- Picosecond Pulse Generation from Semiconductor Laser Diodes --- p.99, Chapter 6.1 --- Introduction --- p.99, Chapter 6.2 --- Gain-switching --- p.99, Chapter 6.2.1 --- Experiment using commercial laser diodes --- p.99, Chapter 6.2.2 --- Repetition rate multiplication --- p.102, Chapter 6.2.3 --- Pulse compression with HDSF --- p.107, Chapter 6.2.4 --- Fiber loop compressor --- p.110, Chapter 6.3 --- Active or Hybrid Mode-locking --- p.112, Chapter 6.3.1 --- Introduction --- p.112, Chapter 6.3.2 --- Laser structure --- p.113, Chapter 6.3.3 --- Experiment and result --- p.113, Chapter 6.3.4 --- Discussion and conclusion --- p.116, Chapter 6.4 --- Amplifier Modulation --- p.117, Chapter 6.4.1 --- Introduction --- p.117, Chapter 6.4.2 --- Experiment and result --- p.118, Chapter 6.5 --- Wavelength Tuning --- p.120, Chapter 6.5.1 --- Introduction --- p.120, Chapter 6.5.2 --- Experiment and result --- p.121, Chapter 6.5.3 --- Conclusion --- p.123, Chapter 6.6 --- Chapter Summary --- p.124, References --- p.124, Chapter (7) --- Conclusion --- p.126, Chapter 7.1 --- Summary of the Research --- p.126, Chapter 7.1.1 --- Fiber lasers --- p.126, Chapter 7.1.2 --- Diode lasers --- p.128, Chapter 7.2 --- Further Study --- p.129, Appendix I Project Instrumentation --- p.A-l, Appendix II Curve Fitting Program for the SHG Autocorrelation Trace --- p.A-8, Appendix III Experiment Setup of Figure Eight Laser --- p.A-12, "Appendix IV Curve Fitting Program for Determination of Second Order Dispersion, dD/dλ" --- p.A-14, Appendix V 1.3 μm two sections DFB/TA Laser Diode Chips --- p.A-17, Appendix VI Publication List --- p.A-l9, http://library.cuhk.edu.hk/record=b5889208, 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Starting with the one-band t-J model and using the slave-boson method to enforce the constraint of no double occupation, we examine the role of the spin-charge interaction in the π-flux phase at half-filling and the uniform resonantvalence- bond mean-field solution away from half-filling. In particular, we calculate the phyiscal electron spectral function. By using the functional integral approach, we developed a self-consistent scheme for the physical electron spectral function. A bandwidth of 8t in the incoherent part of the electron spectral function is obtained both at half-filling and away from half-filling. At half-filling, we found a double-peak structure in the incoherent background of the electron spectral function and this structure persists to small doping regime. The spin-charge interaction also renormalises the holon quasiparticle bandwidth to scale with J. Upon small doping, the electron spectral function contains two dominant distinct features, namely a low-energy quasiparticle peak with bandwidth of order J, and broad valence peaks at energies of order t. The structure in the incoherent background is interpreted due to the strong spin-charge interaction near the points (0,0) and ([pi, pi]) of the first Brillouin zone. The instability of bose-condensation of holon is also examined. We found that the spin-charge interaction is not strong enough to destroy the bose-condenation and a large fraction of holon still condense at zero temperature.