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Ethnopharmacological relevance Cynanchum komarovii Al. Iljinski is a ethnomedicinal herb. This ethno-medicine is used mainly to treat arthritis, toothache, reducing phlegm, relieving cough. TACKI is the main active compound of Cynanchum komarovii Al. Iljinski. Previous investigations have revealed that TACKI can significantly inhibit rat foot swelling caused by carrageenan; it has a significant inhibitory effect on granulation tissue proliferation. Pharmacology study showed that Cynanchum komarovii Al. Iljinski has analgesia, anti-inflammatory, antibacterial, anti-tumor, relieving cough and relieving asthma. However, there is no any investigation on the mechanism of analgesia and anti-inflammation. Aim of the study To clarify the analgesic effect and material basis of Cynanchum komarovii Al. Iljinski, determine the analgesic effect of total alkaloids of Cynanchum komarovii Al. Iljinski (TACKI), and provide experimental data support for its traditional application in the treatment of various pains. Materials and methods TACKI were prepared by the traditional acid extraction and alkaline precipitation method, and TACKI was analyzed through classic animal models of acute antinociceptive animal models and chronic antinociceptive. Evaluation of analgesic effects, and preliminary discussion of the mechanism of its analgesic effects were performed in this work. Results Acute toxicity experiments showed that the LD50 of TACKI mice was 2960.88 mg/kg, and symptoms of poisoning appeared. Patholog of liver and kidney studies have shown that TACKI reduces eosinophils and increases basophils in kidney glomeruli. In the study of analgesic effects, TACKI had analgesic activity through the PWL, formalin test, and acetic acid writhing test. In the chronic inflammatory antinociceptive study, the latency of the withdrawal reflex in the TACKI group was prolonged, and the mechanical withdrawal reflex threshold was significantly increased. The protein expression of NMDA, GFAP and Iba-1 in rat brain tissue can be reduced significantly byTACKI. Meanwhile, the content of TNF-α and IL-6 in rat brain tissue is reduced. Conclusion TACKI has a significant analgesic activities. It may be related to inhibiting the activation of astrocytes and reducing the content of inflammatory mediators.

Imaging distance plays an essential role in image formation in computational ghost imaging (CGI). Uncertain or unknown imaging distance often leads to the deterioration of the image quality or, even worse, to the failure of imaging. Here we present a CGI technique that provides high-quality image reconstruction in an uncertain distance environment. We propose a method to generate a stable speckle field, where the size of the field remains invariant and the field does not distort during light transmission, and find that the use this field removes the constraint imposed by the imaging distance. We experimentally and numerically verify the performance of the technique by applying it to a single-detector CGI system. The results show that the proposed technique provides excellent imaging performance, even when the imaging distance is uncertain, and can be extended to existing computational-based ghost-imaging schemes.

Coptidis rhizoma (CR), also known as “Huanglian” in Chinese, is a traditional Chinese medicine commonly used in China, and it is an important species used in medicinal and food applications. It has been processed using a variety of methods, and the processed products have been widely used in clinical practice for thousands of years. However, few reports have focused on the systematic review of its processed products and quality control. In this study, a literature search on processing and quality control of CR was performed by using several literature resources including the Flora of China official website; various scientific databases such as PubMed, Google Scholar, the Web of Science, Science Direct, and China Knowledge Resource Integrated; and other web sources such as books and PhD and MS dissertations. Results showed that quality control for different processed products of CR received little or no attention. Its processing still followed ancient methods, and the quality of artifacts in different regions varied. Further attention should be paid to the study of processing technology and quality control with biomarkers. We suggest to establish a quality control mode based on traditional efficacy and with bioactive markers as detection indicators.

We propose a deep learning computational ghost imaging (CGI) scheme to achieve sub-Nyquist and high-quality image reconstruction. Unlike the second-order-correlation CGI and compressive-sensing CGI, which use lots of illumination patterns and a one-dimensional (1-D) light intensity sequence (LIS) for image reconstruction, a deep neural network (DAttNet) is proposed to restore the target image only using the 1-D LIS. The DAttNet is trained with simulation data and retrieves the target image from experimental data. The experimental results indicate that the proposed scheme can provide high-quality images with a sub-Nyquist sampling ratio and performs better than the conventional and compressive-sensing CGI methods in sub-Nyquist sampling ratio conditions (e.g., 5.45%). The proposed scheme has potential practical applications in underwater, real-time and dynamic CGI.

Planar parallel three-degrees-of-freedom (3-DOF) nanopositioning systems have been widely applied in scanning probe microscopy, micro-/nanomanipulation, nanoimprint lithography, and precision machining. Two effective optimization approaches are proposed to enhance the system performance in this paper. First, seven indexes are involved in modeling a nanopositioning platform to evaluate the mechanism performance. Four constraints are also considered. A general analysis, optimization, and decision-making method to select better structure parameters is presented. Prototype test results demonstrate high accuracy of the proposed modeling approach and efficiency of the optimization method. Second, precision, accuracy, and velocity are three main indexes to evaluate a nanopositioning system. Different simulated loads are added to test the system performance. Servocontrol parameters of both three input ports and the end effector are optimized using a multiobjective particle swarm optimization algorithm. Experimental results validate the performance of the optimization module and selected parameters. Two parameters optimization approaches are helpful to enhance the performance of a planar parallel 3-DOF nanopositioning system.

Planar parallel three-degrees-of-freedom (3-DOF) nanopositioners have been used for sample scanner in scanning probe microscopy (SPM), wafer positioner in nanoimprint lithography, micro/nano manipulation, and precision machining. The performance evaluation indexes involve workspace, natural frequency, input coupling ratio, precision/accuracy, speed, payload capability, and output compliance. The tradeoff of multiple indexes is an important factor needing to be considered in the process of designing a nanopositioner. Stress, input stiffness, fatigue reliability, and force transmission are also the main constraints. This paper describes an optimal approach of selecting 16 key parameters of a planar parallel 3-DOF nanopositioner. Seven performance indexes and four constraints are involved in modelling the nanopositioner. A general analysis, optimization, and decision-making method is presented. All the modified-Pareto-optimality solutions are obtained using a multi-objective particle swarm optimization (MOPSO) algorithm. Different applications select preferred Pareto solutions from the same Pareto front. Several optimization cases are given to show the high efficiency of the proposed modelling and optimization method. Two design examples are given based on the corresponding demand of two typical application cases, respectively. The simulation and experimental results validate the proposed modelling and optimization method. The research results of this paper are helpful to design a planar parallel 3-DOF nanopositioner for different applications.

We propose a deep learning denoising computational ghost imaging (CGI) method to obtain a clear object image with a sub-Nyquist sampling ratio. We develop an end-to-end deep neural network (DDANet) for CGI image reconstruction. DDANet uses a one-dimensional (1-D) bucket signals (BSs) and multiple tunable noise-level maps as input, and outputs a clear image. We train DDANet with simulated BSs and ground-truth pairs, and then retrieve the object image directly from an experimental obtained 1-D BSs. The effectiveness of the proposed method is experimentally investigated. The proposed method has practical applications in image denoising and enhancement of the CGI and single-pixel computational imaging.

We propose a computational ghost imaging system based on the Hadamard patterns. A 4-connected-region-based method is proposed to optimize the Hadamard pattern sequence and a differential decomposition method is developed to construct a sequence that can be shown on the light modulation devices with the optimized pattern sequence. Finally, the image is reconstructed by the second-order correlation algorithm. Both numerical model and experimental setup are established and a series of experiments are implemented. The imaging performance of the proposed method is validated by comparing with the results from the default order of the Hadamard pattern sequence, Russian-dolls ordering and fast Walsh-Hadamard transform. The proposed system can realize high quality imaging with a low sampling ratio (5%–10%), and it requires much less measurement numbers for imaging.

Multi-degree-of-freedom (multi-DOF) nanopositioning stages (NPSs) have rapidly growing applications in the spatial micro-/nano-machining and manipulation. Compliant parallel mechanisms (CPMs) demonstrate advantages to achieve a large output stiffness and high payload. A four-DOF NPS based on six-branched-chain CPMs is proposed in this paper. First, a mechanism design approach is introduced. One primary vertical DOF is generated using three parallel-kinematic lever amplifiers. A three-revolute-revolute-revolute mechanism acts as the kinematic configuration to produce three secondary planar DOFs. Three types of single-axis and one type of double-axis notch flexure hinges (NFHs) are employed to realize the nanoscale displacement/movement guiding, transferring, and decoupling. Second, a stiffness modeling approach is derived. Combined with exact compliance matrices of 54 NFHs and 95 flexible beams, a four-DOF high-efficiency stiffness model of the six-branched-chain CPM is built. The calculation procedure of the whole input/output stiffnesses and coupling ratios takes 12.06 ms. Simulation and prototype test results validate the calculation accuracy. For example, the maximum calculation deviation of input stiffnesses is verified to be 4.52% and 8.18%, respectively. The two proposed approaches contribute to the statics parameter optimization of spatial multi-DOF NPSs.

We propose an online adaptive computational ghost imaging (CGI) scheme that offers high quality imaging with few measurement numbers. Different from the conventional second-order correlation CGI, the proposed scheme utilizes an online imaging method for image reconstruction, where the object image is recovered immediately after the light intensity is acquired. An adaptive measurement termination method is proposed to terminate the online imaging when the quality of the recovered image is satisfied. The effectiveness of the proposed scheme is verified by numerical simulations and experiments and its imaging performance is assessed by comparing the results with state-of-the-art FWHTGI (fast Walsh-Hadamard transform CGI) and RDCGI (Russian dolls ordering CGI). The results demonstrate that the proposed scheme can achieve high-quality imaging with few measurements, and imaging quality is better than that with FWHTGI and RDCGI under low measurement number conditions. The proposed scheme may be helpful for high-resolution and real-time CGI.

Many clinical diseases are accompanied by the symptoms of pain, and the degree of pain is closely related to the patients’ suffering. Therefore, effectively relieving pain has become one of the vital concerns of clinical treatment and analgesic drug research. Non-opioid drugs are mainly used for the clinical treatment of mild to moderate pain, whereas opioid drugs are mainly used for treating moderate to severe pain. However, opioid drugs easily elicit adverse reactions, such as gastrointestinal discomfort, addiction, dependence, and so on. Traditional Chinese medicine and its active ingredients have unique advantages in the treatment of pain for quite a long time, and many analgesic drugs directly or indirectly were isolatiedfrom Chinese medicine or natural products, such as Liu Suan Yan Hu Suo Yi Su Pian and aspirin. With the development and modernization of research on herbal medicine more and more studies have been conducted on the active ingredients and mechanisms of traditional Chinese medicine analgesics. However, no review has been done on analgesic active components and their mechanisms. In this paper, 81 active components with clear chemical structure and definite analgesic effects in vivo and in vitro of traditional Chinese medicine and mechanisms of action reported in recent literatures are reviewed and summarized to provide reference for clinical analgesia and analgesics research.

Packaged piezoelectric ceramic actuators (PPCAs) and compliant mechanisms are attractive for nanopositioning and nanomanipulation due to their ultra-high precision. The way to create and keep a proper and steady connection between both ends of the PPCA and the compliant mechanism is an essential step to achieve such a high accuracy. The connection status affects the initial position of the terminal moving plate, the positioning accuracy and the dynamic performance of the nanopositioning platform, especially during a long-time or high-frequency positioning procedure. This paper presents a novel external preload mechanism and tests it in a 1-degree of freedom (1-DOF) compliant nanopositioning platform. The 1-DOF platform utilizes a parallelogram guiding mechanism and a parallelogram load mechanism to provide a more accurate actual input displacement and output displacement. The simulation results verify the proposed stiffness model and dynamic model of the platform. The values of the preload displacement, actual input displacement and output displacement can be measured by three capacitive sensors during the whole positioning procedure. The test results show the preload characteristics vary with different types or control modes of the PPCA. Some fitting formulas are derived to describe the preload displacement, actual input displacement and output displacement using the nominal elongation signal of the PPCA. With the identification of the preload characteristics, the actual and comprehensive output characteristics of the PPCA can be obtained by the strain gauge sensor (SGS) embedded in the PPCA.

Ethnopharmacological relevance Sophora alopecuroides L., which is called Kudouzi in China, is a medicinal plant distributed in Western and Central Asia, especially in China, and has been used for decades to treat fever, bacterial infection, heart disease, rheumatism, and gastrointestinal diseases. Aim of the review This review aims to provide up-to-date information on S. alopecuroides, including its botanical characterization, medicinal resources, traditional uses, phytochemistry, pharmacological research, and toxicology, in exploring future therapeutic and scientific potentials. Materials and methods The information related to this article was systematically collected from the scientific literature databases including PubMed, Google Scholar, Web of Science, Science Direct, Springer, China National Knowledge Infrastructure, published books, PhD and MS dissertations, and other web sources, such as the official website of Flora of China and Yao Zhi website ( https://db.yaozh.com/ ). Results A total of 128 compounds, such as alkaloids, flavonoids, steroids, and polysaccharides, were isolated from S. alopecuroides. Among these compounds, the effects of alkaloids, such as matrine and oxymatrine, were extensively studied and developed into new drugs. S. alopecuroides and its active components had a wide range of pharmacological activities, such as anticancer, antiviral, anti-inflammatory, antimicrobial, analgesic, and neuroprotective functions, as well as protective properties against pulmonary fibrosis and cardiac fibroblast proliferation. Conclusions As an important traditional Chinese medicine, modern pharmacological studies have demonstrated that S. alopecuroides has prominent bioactivities, especially on gynecological inflammation and hepatitis B, and anticancer activities. These activities provide prospects for novel drug development for cancer and some chronic diseases. Nevertheless, the comprehensive evaluation, quality control, understanding of the multitarget network pharmacology, long-term in vivo toxicity, and clinical efficacy of S. alopecuroides require further detailed research.

We propose a computational ghost imaging (CGI) scheme based on a rearranged Hadamard matrix (HCGI). A decomposition method is first introduced to construct a speckle pattern sequence that can be displayed on the digital micromirror device. Then a speckle pattern sequence rearrangement method is proposed, which makes the large intensity fluctuation values concentrate on the front part of the intensity fluctuation sequence. Finally, a HCGI model is established and a series of numerical experiments are conducted. The influence of intensity fluctuations on HCGI is studied and analyzed by comparing the numerical results which are respectively recovered by the proposed method and fast Walsh–Hadamard transform. The results demonstrate that large intensity fluctuation values play the key role in HCGI and provide maximum contribution to high quality imaging. The proposed method provides a way to improve the imaging quality and speed of CGI from the perspective of intensity fluctuations.

This paper presents the design, analysis and test of a novel planar 3-DOF (degree of freedom) precision positioning platform. Three two-level lever amplifiers are utilized to get a large amplification ratio. A more accurate flexible bending model of the lever amplifier is created to calculate the displacement loss relative to the PRBM (pseudo-rigid-body model). The displacement loss factor, the drift displacement loss factor and the bending displacement loss factor of a lever amplifier are defined, respectively. This model is verified by the simulation on the amplification ratio. A dynamics model is established by simplifying the flexure hinge into the ideal revolute joint with a constant torsional stiffness. This model is verified by the simulation and prototype test on the natural frequency. Above two accurate models can well predict the performance of the platform. The prototype test on the workspace and resolution shows that this platform possesses a large magnification with a high positioning resolution.

Piezo-actuated flexure-based precision positioning platforms have been widely used in micro/nano manipulation. A conventional major challenge is the trade-off between high rigidity, large magnification, high-precision tracking, and high-accuracy positioning. A compact planar three-degrees-of-freedom (3-DOF) nanopositioning platform is described in which three two-level lever amplifiers are arranged symmetrically to achieve large magnification. The parallel-kinematic configuration with optimised sizes increases the rigidity. Displacement loss models (DLM) are proposed for the external preload port of the actuator, the input port of the platform and the flexible lever mechanism. The kinematic and dynamic modelling accuracies are improved by the compensation afforded by the three DLMs. Experimental results validate the proposed design and modelling methods. The proposed platform possesses high rigidity, large magnification, high-precision circle tracking and high-accuracy positioning.

Nanopositioners are widely applied in micro/nano manipulation, atomic force microscope (AFM), nanoimprint lithography, and precision machining. With a rapid increasing demand of the manufacture of the complex non-rotationally symmetric (NRS) optical freeform surface, different tool servo mechanisms for the ultra-precision machining have been developed in recent years. Multi-DOF nanopositioners based on the compliant parallel mechanisms (CPMs) provide an efficient solution. A compact spatial 3-Degree of Freedom (DOF) compliant parallel nanopositioner is proposed in this paper. The nanopositioner possesses three translational DOFs of the orthogonal coordinates. Three two-level tiny displacement amplifiers are arranged to obtain large magnification. Sufficient output stiffness is a prior design consideration. Combined with three single-DOF nanopositioning stages (NPSs) and one shared end-effector, a 3-DOF stiffness modeling approach is presented to obtain the whole input/output stiffness and coupling ratio. Simulation results validate the precision, accuracy, and high-efficiency of the presented stiffness modeling method using a simple design example. The design and stiffness modeling approaches provide the foundation of the performance indexes optimization, and are helpful to fulfill the rapid increasing demand of the multi-axis tool servo for the ultra-precision machining.