Search

Radon observation is an important measurement item of seismic precursor network observation. The radon detector calibration is a key technical link for ensuring radon observation accuracy. At present, the radon detector calibration in seismic systems in China is faced with a series of bottleneck problems, such as aging and scrap, acquisition difficulties, high supervision costs, and transportation limitations of radon sources. As a result, a large number of radon detectors cannot be accurately calibrated regularly, seriously affecting the accuracy and reliability of radon observation data in China. To solve this problem, a new calibration method for radon detectors was established. The advantage of this method is that the dangerous radioactive substance, i.e., the radon source, can be avoided, but only “standard instruments” and water samples with certain dissolved radon concentrations can be used to realize radon detector calibration. This method avoids the risk of radioactive leakage and solves the current widespread difficulties and bottleneck of radon detector calibration in seismic systems in China. The comparison experiment with the traditional calibration method shows that the error of the calibration coefficient obtained by the new method is less than 5% compared with that by the traditional method, which meets the requirements of seismic observation systems, confirming the reliability of the new method. This new method can completely replace the traditional calibration method of using a radon source in seismic systems.

Carbonaceous materials in seismic fault zones may considerably influence seismic fault slip; however, the formation mechanism of carbonaceous materials remains unclear. In this study, we proposed a novel hypothesis for the formation of carbonaceous materials in fault gouge. Thus, we conducted a CO2 hydrogenation experiment in a high-temperature reactor at a co-seismic temperature, with fault gouge formed during the Wenchuan earthquake as the catalyst. Our experimental results demonstrate that carbonaceous materials in fault zones are formed on the fault gouge during the chemical reaction process, suggesting that the carbonaceous materials are possibly generated from the catalytic hydrogenation of CO2, followed by thermal cracking of its products. The results of this study provide a theoretical basis for understanding fault behavior and earthquake physics.

Abstract Despite notable advancements in the investigation and management of lung adenocarcinoma (LUAD), the mortality rate for individuals afflicted with LUAD remains elevated, and attaining an accurate prognosis is challenging. LUAD exhibits intricate genetic and environmental components, and it is plausible that free fatty acid receptors (FFARs) may bridge the genetic and dietary aspects. The objective of this study is to ascertain whether a correlation exists between FFAR4, which functions as the primary receptor for dietary fatty acids, and various characteristics of LUAD, while also delving into the potential underlying mechanism. The findings of this study indicate a decrease in FFAR4 expression in LUAD, with a positive correlation (P

In biological micromanipulation, cell penetration is a typical procedure that precedes cell injection or oocyte enucleation. During this procedure, cells usually undergo significant deformation, which leads to cell damage. In this paper, we focus on modeling and evaluating the cell penetration process to reduce cell deformation and stress, thereby reducing cell damage. Initially, a finite element model (FEM) is established to simulate the cell penetration process. The effectiveness of the model is then verified through visual detection and comparison of cell deformation with experimental data. Next, various mechanical responses are analyzed, considering the influence of parameters, such as the radius and shape of the injection micropipettes, material properties, and size of the cells. Finally, the relationship between the intracellular stress and the cell penetration depth of biological cells is obtained. The evaluation results will be applied to develop optimized operation plans, enhancing the efficiency and safety of the cell penetration process.

The shear mechanical behavior of soils in the slip zone under cyclic loading is of great importance for the stability analysis of landslides. In this paper, an experimental device is developed to study the nonlinear deformation mechanism of soil in sliding zone under cyclic load. Based on field tests and model tests, the change of shear strength parameters of the soil in the slip zone with cyclic loading parameters was investigated. Based on the deformation characteristics of slip zone soils under cyclic dynamic loading, the unsteady creep transient model based on fractional derivative is established, and three deformation types of sliding zone soil are described: stable, critical and destructive. The Levenberg-Marquardt (LM) algorithm is used to fit the nonlinear curves, and the applicability of the model is also verified. This research method provides a test apparatus and a method for studying the deformation characteristics of slip zone soils under cumulative loading.

Abstract The power quality and efficiency of the hydro-power station depend on the stable operation of the hydro-generator unit, which needs to continue to operate and it is prone to axis failure. Therefore, to adopt effective axis adjustment technology to eliminate faults. This paper proposes a new method for axis adjustment of hydro-generator unit based on an improved grey prediction model and swarms intelligence optimization neural network. First of all, it proposes a sequence acceleration translation and mean value transformation method, which is used to pre-process the axis net total swing sequence that exhibits oscillating fluctuations. It uses e 1 and e 2 factor transformation to establish an improved axis net total swing gray prediction model. Then, the advanced flamingo search algorithm is used to search the maximum value of the sine function of the net total pendulum of the axis, and the axis adjustment orientation is obtained. This method solves the problem that GM(1, 1) can only be predicted by monotone sequence in the past and the problem that the search algorithm is easy to fall into local optimum, effectively improves the calculation efficiency of axis and shorts the search time. Simulation examples show that the proposed method can significantly improve accuracy of axis adjustment. This method greatly improves the efficiency of azimuth search for axis adjustment.

The power cyber–physical system (CPS) realizes the wide-area interconnection of new energy sources and multiple loads and the dynamic interaction of information and energy flows; however it faces increasingly severe security threats of false data injection attacks (FDIAs). In this context, the active defense methods against power CPS FDIAs from the multiple spatiotemporal perspective are summarized and analyzed in this paper. First, the architecture of a power CPS is abstracted and its multiple spatiotemporal coordination characteristic and FDIAs security risk are expounded upon. Then, the active defense system against FDIAs is conceived in the spatiotemporal coordinate system, and based on different spatiotemporal intersections, the six active defense methods and application examples – namely network deception, data encryption protection, vulnerability policy protection, false identification correction, traffic anomaly detection, and fault prevention control – are summarized. Finally, the limitations of existing active defense methods against FDIAs are discussed, and the linked defense methods with multiple spatiotemporal coordination are prospected.

Cell models play a crucial role in analyzing the mechanical response of cells and quantifying cellular damage incurred during micromanipulation. While traditional models can capture the overall mechanical behavior of cells, they often lack the ability to discern among distinct cellular components. Consequently, by employing dissipative particle dynamics, this study constructed a triangular network-like representation of the cell membrane along with cross-linked cytoskeletal chains. The mechanical properties of both the membrane and cytoskeleton were then analyzed through a series of simulated mechanical tests, validated against real-world experiments. The investigation utilized particle-tracking rheology to monitor changes in the mean square displacements of membrane particles over time, facilitating the analysis of the membrane’s storage and loss moduli. Additionally, the cytoskeletal network’s storage and loss moduli were examined via a double-plate oscillatory shear experiment. The simulation results revealed that both the membrane and cytoskeleton exhibit viscoelastic behavior, as evidenced by the power-law dependency of their storage and loss moduli on frequency. Furthermore, indentation and microinjection simulations were conducted to examine the overall mechanical properties of cells. In the indentation experiments, an increase in the shear modulus of the membrane’s WLCs correlated with a higher Young’s modulus for the entire cell. Regarding the microinjection experiment, augmenting the microinjection speed resulted in reduced deformation of the cell at the point of membrane rupture and a lower percentage of high strain.

Abstract Taking account of the fact that the existing knowledge‐driven detection process for false data injection attacks (FDIAs) has been in a passive detection state for a long time and ignores the advantages of data‐driven active capture of features, an active and passive hybrid detection method for power cyber‐physical systems (CPS) FDIAs with improved adaptive Kalman filter (AKF) and convolutional neural networks (CNN) is proposed in this paper. First, the shortcomings of the traditional AKF algorithm in terms of filtering divergence and calculation speed are analyzed. The state estimation algorithm based on non‐negative positive‐definite adaptive Kalman filter (NDAKF) is improved, and a passive detection method of FDIAs is constructed, with similarity Euclidean distance detection and residual detection at its core. Then, combined with the advantages of gate recurrent unit (GRU) and CNN in terms of temporal memory and feature‐expression ability, an active detection method of FDIAs based on a GRU‐CNN hybrid neural network is proposed. Finally, the results of joint knowledge‐driven and data‐driven parallel detection are used to define a mixed fixed‐calculation formula, and an active and passive hybrid detection method of FDIAs is established, considering the characteristic constraints of the parallel mode.

Contraction and relaxation are important functions of cardiomyocytes, and measuring their characteristics provides an evaluation index to explore the effects of drugs on cardiomyocytes. In addition, cardiomyocytes have an innate advantage in acting as a biopower by virtue of their ability to contract and relax, which also requires the detection of cardiomyocyte actions. However, existing measurement methods, such as mechanosensor measurements and calcium concentration measurements, have high requirements for experimental equipment and operation and are challenging to perform simultaneously with other cellular manipulations. Here, we propose a simple visual detection method for cardiomyocyte contraction and relaxation. We first recorded the contraction and relaxation of cardiomyocytes under a bright-field microscope, then used the optical flow method to track the sampling points on the cardiomyocytes in the video, and obtained the frequency of cardiomyocyte contraction and relaxation by analyzing the optical flow matrices. This method does not require the use of additional equipment or additional processing of cardiomyocytes, which significantly reduces the operational difficulty of detection and provides a method to achieve real-time detection of cardiomyocyte contraction and relaxation.

Intracellular pressure, a key physical parameter of the intracellular environment, has been found to regulate multiple cell physiological activities and impact cell micromanipulation results. The intracellular pressure may reveal the mechanism of these cells’ physiological activities or improve the micro-manipulation accuracy for cells. The involvement of specialized and expensive devices and the significant damage to cell viability that the current intracellular pressure measurement methods cause significantly limit their wide applications. This paper proposes a robotic intracellular pressure measurement method using a traditional micropipette electrode system setup. First, the measured resistance of the micropipette inside the culture medium is modeled to analyze its variation trend when the pressure inside the micropipette increases. Then, the concentration of KCl solution filled inside the micropipette electrode that is suitable for intracellular pressure measurement is determined according to the tested electrode resistance–pressure relationship; 1 mol/L KCl solution is our final choice. Further, the measurement resistance of the micropipette electrode inside the cell is modeled to measure the intracellular pressure through the difference in key pressure before and after the release of the intracellular pressure. Based on the above work, a robotic measurement procedure of the intracellular pressure is established based on a traditional micropipette electrode system. The experimental results on porcine oocytes demonstrate that the proposed method can operate on cells at an average speed of 20~40 cells/day with measurement efficiency comparable to the related work. The average repeated error of the relationship between the measured electrode resistance and the pressure inside the micropipette electrode is less than 5%, and no observable intracellular pressure leakage was found during the measurement process, both guaranteeing the measurement accuracy of intracellular pressure. The measured results of the porcine oocytes are in accordance with those reported in related work. Moreover, a 90% survival rate of operated oocytes was obtained after measurement, proving limited damage to cell viability. Our method does not rely on expensive instruments and is conducive to promotion in daily laboratories.

Building an integrated energy system (IES) is an excellent solution to environmental pollution and energy consumption currently. However, there are usually various IES configurations with different performances, and it is usually difficult for the decision-makers to select the most sustainable IES solution among multiple choices. In this paper, we attempt to design an evaluation method that considers the renewable energy and energy system model for evaluating the benefit of an IES. Firstly, this paper constructs an evaluation index system including four dimensions of technology, economy, environment, and society, based on the physical architecture of IES and its benefit influencing factors. It focuses on multiple energy sources or systems, and satisfies the overall evaluation of IES, resulting in accurate benefit evaluation results. Secondly, the subjective weight is determined by combining the triangular fuzzy number (TFN) and the analytic hierarchy process (AHP). The objective weight is determined by the entropy method. The combined weight is obtained by combining the subjective and objective weights, which solves the problem of the weight calculation error caused by the mutual influence between the indexes. Finally, the fuzzy comprehensive evaluation method is used to conduct the benefit evaluation of the IES, which solves the problem that the qualitative index cannot be calculated. This paper takes an IES project in a city in northern China as a case study. Through sensitivity analysis and comparative analysis, the reliability and feasibility of the evaluation results and proposed method are verified. The analysis results show that the model evaluation results are intuitive and consistent with reality, and the data information utilization rate is high.

To extend the shelf life and retain bioactive proteins in milk, this study utilized microfiltration (MF) combined with ultrasonication to treat skim milk and investigated its efficiency in removing bacteria and retaining bioactive proteins compared with HTST pasteurization and microfiltration alone. Results showed that microfiltration combined with ultrasonication at 1296 J/mL could completely remove the bacteria in skim milk. Ultrasonication further extended the shelf life (4 °C) of microfiltered skim milk, which could reach at least 40 days when MF was combined with ˃1296 J/mL ultrasonication. In addition, ELISA showed that HTST pasteurization significantly decreased the levels of IgG by ~30%, IgA by ~ 50%, IgM by ~60%, and lactoferrin by ~40%, whereas the activity of the enzymes lactoperoxidase and xanthine oxidase were also decreased by ~ 20%. Compared with HTST, MF alone or combined with ultrasonication retained these bioactive proteins to a larger degree. On the other hand, proteomics indicated both damage to casein micelle and fat globule structures in milk when ultrasonication at >1296 J/mL was applied, as shown by increases in caseins and milk fat globular proteins. Simultaneously, this ultrasound intensity also decreased levels of bioactive proteins, such as complement factors. Taken together, this study provided new insights that may help to implement this novel combination of non-thermal technologies for the dairy industry aimed at improving milk quality and functionality.

The early steps of embryogenesis are controlled exclusively by the quality of oocyte that linked closely to its mechanical properties. The mechanical properties of an oocyte were commonly characterized by assuming it was homogeneous such that the result deviated significantly from the true fact that it was composed of subcellular components. In this work, we accessed and characterized the subcellular components of the oocytes and developed a layered high-fidelity finite element model for describing the viscoelastic responses of an oocyte under loading. The zona pellucida (ZP) and cytoplasm were isolated from an oocyte using an in-house robotic micromanipulation platform and placed on AFM to separately characterizing their mechanical profiling by analyzing the creep behavior with the force clamping technique. The spring and damping parameters of a Kelvin–Voigt model were derived by fitting the creeping curve to the model, which were used to define the shear relaxation modulus and relaxation time of ZP or cytoplasm in the ZP and cytoplasm model. In the micropipette aspiration experiment, the model was accurate sufficiently to deliver the time-varying aspiration depth of the oocytes under the step negative pressure of a micropipette. In the micropipette microinjection experiment, the model accurately described the intracellular strain introduced by the penetration. The developed oocyte FEM model has implications for further investigating the viscoelastic responses of the oocytes under different loading settings.

In this paper, robust H∞ control for fractional-order switched systems (FOSSs) with uncertainty is studied. Firstly, the fractional-order switching law for FOSSs is proposed. Then, H∞ control for FOSSs is proven based on the switching law and linear matrix inequalities (LMIs). Moreover, H∞ control for FOSSs with a state feedback controller is extended. Furthermore, the LMI-based condition of robust H∞ control for FOSSs with uncertainty is proven. Furthermore, the condition of robust H∞ control is proposed to design the state feedback controller. Finally, four simulation examples verified the effectiveness of the proposed methods.

In the paper, H∞ and robust H∞ control for fractional order systems (FOS) with order 0<α<1 are studied. Firstly, necessary and sufficient conditions of H∞ control and state feedback controller design are proposed. Then, robust H∞ control for FOS with uncertainty is studied, and state feedback controller is designed. These conditions are based on linear matrix inequalities (LMI) and can be easily solved by the LMI toolbox. Finally, the effectiveness of these conditions is verified by two numerical examples.

Oocyte penetration is an essential step for many biological technologies, such as animal cloning, embryo microinjection, and intracytoplasmic sperm injection (ICSI). Although the success rate of robotic cell penetration is very high now, the development potential of oocytes after penetration has not been significantly improved compared with manual operation. In this paper, we optimized the oocyte penetration speed based on the intracellular strain. We firstly analyzed the intracellular strain at different penetration speeds and performed the penetration experiments on porcine oocytes. Secondly, we studied the cell development potential after penetration at different penetration speeds. The statistical results showed that the percentage of large intracellular strain decreased by 80% and the maximum and average intracellular strain decreased by 25–38% at the penetration speed of 50 μm/s compared to at 10 μm/s. Experiment results showed that the cleavage rates of the oocytes after penetration increased from 65.56% to 86.36%, as the penetration speed increased from 10 to 50 μm/s. Finally, we verified the gene expression of oocytes after penetration at different speeds. The experimental results showed that the totipotency and antiapoptotic genes of oocytes were significantly higher after penetration at the speed of 50 μm/s, which verified the effectiveness of the optimization method at the gene level.

β-lactoglobulin is important fraction in bovine milk. Selenium is an essential nutrient element. The apoptosis and autophagy induction of Se-β-Lg combined selenic acid in β-lactoglobulin on Hep G2 and Hep 3B cells were investigated in this study. MTT assay showed Se-β-Lg inhibited cells viability. Annexin V-FITC/PI and PI staining indicated Se-β-Lg triggered cells apoptosis and cell cycle arrest. Western blot of caspase-cascade suggested Hep G2 and Hep 3B cells occurred irreversible extrinsic apoptosis. TEM and protein expression of LC3 indicated Se-β-Lg induced cells autophagy. Further explore found Se-β-Lg induced up-regulation of p53 and Fas/FasL in Hep G2 cells. Simultaneously, N-acetyl-L-cysteine, pifithrin-α, Z-VAD-FMK and 3-MA were used. These results further demonstrated Se-β-Lg triggered autophagy and receptor-related apoptosis via p53-mediated Fas/FasL pathway in Hep G2 cells and induced autophagy and p53/Fas-independent caspase activation in Hep 3B cells. Our research revealed that Se-β-Lg had potential to act as chemopreventive compounds in HCC therapy.

The mechanical properties of biological cells, especially the elastic modulus and viscosity of cells, have been identified to reflect cell viability and cell states. The existing measuring techniques need additional equipment or operation condition. This paper presents a cell’s viscoelasticity measurement method based on the spheroidization process of non-spherical shaped cell. The viscoelasticity of porcine fetal fibroblast was measured. Firstly, we introduced the process of recording the spheroidization process of porcine fetal fibroblast. Secondly, we built the viscoelastic model for simulating a cell’s spheroidization process. Then, we simulated the spheroidization process of porcine fetal fibroblast and got the simulated spheroidization process. By identifying the parameters in the viscoelastic model, we got the elasticity (500 Pa) and viscosity (10 Pa·s) of porcine fetal fibroblast. The results showed that the magnitude of the elasticity and viscosity were in agreement with those measured by traditional method. To verify the accuracy of the proposed method, we imitated the spheroidization process with silicone oil, a kind of viscous and uniform liquid with determined viscosity. We did the silicone oil’s spheroidization experiment and simulated this process. The simulation results also fitted the experimental results well.

Oocyte enucleation is a critical procedure for somatic cell nuclear transfer. Yet, the main steps of oocyte enucleation are still manually operated, which presents several drawbacks such as low precision, high repetition error, and long training time for operators. For improving the operation efficiency and success rate, a robotic precise oocyte blind enucleation method is presented in this paper. The proposed method involves the following key techniques: oocyte translation control, oocyte immobilization and penetration control, and enucleation volume control based on the adaptive slide mode. Compared with the manual blind enucleation method, the proposed robotic blind enucleation method reduced the operation time by 44.5% (manual method: 62 s vs. proposed method: 34.4 s), increased the accuracy of enucleation by 83.1% (manual method: 30.7 vs. proposed method: 5.2), increased the success rate from 80% to 93.3%, and increased the cleavage rate from 41.7% to 63.3%.

As there are significant variations of cell elasticity among individual cells, measuring the elasticity of batch cells is required for obtaining statistical results of cell elasticity. At present, the micropipette aspiration (MA) technique is the most widely used cell elasticity measurement method. Due to a lack of effective cell storage and delivery methods, the existing manual and robotic MA methods are only capable of measuring a single cell at a time, making the MA of batch cells low efficiency. To address this problem, we developed a robotic MA system capable of storing multiple cells with a feeder micropipette (FM), picking up cells one-by-one to measure their elasticity with a measurement micropipette (MM). This system involved the following key techniques: Maximum permissible tilt angle of MM and FM determination, automated cell adhesion detection and cell adhesion break, and automated cell aspiration. The experimental results demonstrated that our system was able to continuously measure more than 20 cells with a manipulation speed quadrupled in comparison to existing methods. With the batch cell measurement ability, cell elasticity of pig ovum cultured in different environmental conditions was measured to find optimized culturing protocols for oocyte maturation.

Polar-body detection is an essential and crucial procedure in various automatic cell manipulations. The polar body can only be observed when it is located near the focal plane of the microscope, so we need to detect the polar body during cell rotation in cell manipulations. However, three-dimensional cell rotation by micropipette causes polar-body defocus and cell/polar-body deformation, which have not been discussed in existing image-level polar-body-detection approaches. Moreover, varying sizes of the polar bodies increase the difficulty of polar-body detection. In this paper, we propose a deep-learning-based framework to realize polar-body detection in cell rotation. The detection problem is interpreted as image segmentation, which separates the polar body from the background. Then, we improve U-net, which is a typical convolutional neural network (CNN) for medical-image segmentation, so that the network can be applied to polar-body detection, especially for the detection of defocused polar bodies and polar bodies of different sizes. For CNN training, we also designed a particular image-transformation method to simulate more cell-rotation situations, including cell- and polar-body deformation, so that the deformed polar body in cell rotation would be detected by the proposed method. Experiment results show that our method achieves high detection accuracy of 98.7% on a test dataset of 1000 images, and performs well in cell-rotation processes. This method can be applied to various automatic cell manipulations in the future.

It is essential to have three-dimensional orientation of cells under a microscope for biological manipulation. Conventional manual cell manipulation is highly dependent on the operator’s experience. It has some problems of low repeatability, low efficiency, and contamination. The current popular robotic method uses an injection micropipette to rotate cells. However, the optimal poking direction of the injection micropipette has not been established. In this paper, a strategy of robotic cell rotation based on optimal poking direction is proposed to move the specific structure of the cell to the desired orientation. First, analysis of the force applied to the cell during rotation was done to find the optimal poking direction, where we had the biggest moment of force. Then, the moving trajectory of the injection micropipette was designed to exert rotation force based on optimal poking direction. Finally, the strategy was applied to oocyte rotation in nuclear transfer. Experimental results show that the average completion time was up to 23.6 s and the success rate was 93.3% when the moving speed of the injection micropipette was 100 μm/s, which demonstrates that our strategy could overcome slippage effectively and with high efficiency.

Microinjection is a promising tool for microdroplet generation, while the microinjection for microdroplets generation still remains a challenging issue due to the Laplace pressure at the micropipette opening. Here, we apply a simple and robust substrate-contacting microinjection method to microdroplet generation, presenting a size-adjustable microdroplets generation method based on a critical injection (CI) model. Firstly, the micropipette is adjusted to a preset injection pressure. Secondly, the micropipette is moved down to contact the substrate, then, the Laplace pressure in the droplet is no longer relevant and the liquid flows out in time. The liquid constantly flows out until the micropipette is lifted, ending the substrate-contacting situation, which results in the recovery of the Laplace pressure at the micropipette opening, and the liquid injection is terminated. We carry out five groups of experiments whereupon 1600 images are captured within each group and the microdroplet radius of each image is detected. Then we determine the relationship among microdroplet radius, radius at the micropipette opening, time, and pressure, and, two more experiments are conducted to verify the relationship. To verify the effectiveness of the substrate-contacting method and the relationship, we conducted two experiments with six desired microdroplet radii are set in each experiment, by adjusting the injection time with a given pressure, and adjusting the injection pressure with a given time. Then, six arrays of microdroplets are obtained in each experiment. The results of the experiments show that the standard errors of the microdroplet radii are less than 2% and the experimental errors fall in the range of ±5%. The average operating speed is 20 microdroplets/min and the minimum radius of the microdroplets is 25 μm. This method has a simple experimental setup that enables easy manipulation and lower cost.