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This paper designs a three-dimensional display system for intangible cultural heritage based on generative adversarial networks. The system function is realized through four modules: input module, data processing module, 3D model generation module, and model output module. Two 3D model reconstruction methods are used to realize the transformation from 2D images to 3D models. In the low-resolution Nuo surface 3D construction, multiresidual dense blocks are introduced and applied to the deep image super-resolution network. The experimental comparison results show that the quadratic optimization multifusion 3D construction model proposed in this paper can achieve considerable improvement and can improve the reconstruction accuracy by about 6.3%. In the high-resolution 3D construction of the Nuo surface, a generative adversarial network model is used to improve the generator, discriminator, and loss function of the original SRGAN model. Experimental results show that this method can generate super-resolution images with more realistic and natural depth maps. In addition, when it is used for high-resolution 3D Nuo surface sculpting, it can also generate 3D voxel Nuo surfaces with more details.

Light plays an important role in determining plant architecture, which greatly influences crop yield. However, the precise mechanisms by which light signaling regulates bud outgrowth remain to be identified. Here, we show that light regulates bud outgrowth via both HY5 and brassinosteroid (BR)-dependent pathways in tomato. Inactivation of the red-light photoreceptor PHYB, or deficiencies in PHYB or the blue-light photoreceptor CRY1a, inhibits bud outgrowth and leads to decreased accumulation of HY5 protein and increased transcript level of BRANCHED1 ( BRC1 ), a central integrator of branching signals. HY5, functioning as a mobile systemic signal from leaves, promotes bud outgrowth by directly suppressing BRC1 transcript and activating the transcript of BR biosynthesis genes within the lateral buds in tomato. Furthermore, BRC1 prevents the accumulation of cytokinin (CK) and gibberellin (GA) by directly inhibiting the transcript of CK synthesis gene LOG4 , while increasing the transcript levels of CK and GA degradation genes ( CKX7 , GA2ox4 , and GA2ox5 ), leading to an arrest of bud outgrowth. Moreover, bud outgrowth occurs predominantly in the day due to the suppression of BRC1 transcript by HY5. These findings demonstrate that light-inducible HY5 acts as a systemic signaling factor in fine-tuning the bud outgrowth of tomato.

Knowing methane desorption characteristics is essential to define the contribution of adsorbed gas to gas well production. To evaluate the synthetic effect of a clay stabilizer solution on methane desorption kinetics and isotherms pertaining to Longmaxi shale, an experimental setup was designed based on the volumetric method. The objective was to conduct experiments on methane adsorption and desorption kinetics and isotherms before and after clay stabilizer treatments. The experimental data were a good fit for both the intraparticle diffusion model and the Freundlich isotherm model. We analyzed the effect of the clay stabilizer on desorption kinetics and isotherms. Results show that clay stabilizer can obviously improve the diffusion rate constant and reduce the methane adsorption amount. Moreover, we analyzed the desorption efficiency before and after treatment as well as the adsorbed methane content. The results show that a higher desorption efficiency after treatment can be observed when the pressure is higher than 6.84 MPa. Meanwhile, the adsorbed methane content before and after treatment all increase when the pressure decreases, and clay stabilizer can obviously promote the adsorbed methane to free gas when the pressure is lower than 19 MPa. This can also be applied to the optimization formulation of slickwater and the design of gas well production.

Cordyceps sinensis (CS) is a traditional Chinese medicine that is known for treating various diseases, and particularly for exerting therapeutic effects in immune disorders. The adaptive immunoregulatory effects of CS aqueous extract (CSAE) on γ-irradiated mice have not been reported previously. The study aimed to evaluate the therapeutic effects of CSAE in mice immunosuppressed by irradiation. We observed that CSAE administration significantly increased body weight and spleen index, as well as the number of white blood cells, lymphocytes, and platelets in peripheral blood, T and B lymphocytes in spleen tissue, and total serum immunoglobulins in irradiated mice, whereas total serum pro-inflammatory cytokine levels were decreased. Collectively, CSAE maintained the structural integrity of spleen tissue and repaired its damage in irradiated mice as shown by hematoxylin and eosin staining, and decreased the number of terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling-positive splenocytes. Mechanistically, CSAE upregulated Bcl-2, and downregulated Bax and cleaved caspase-3 in spleen of irradiated mice. However, there were no significant differences in red blood cells and neutrophils in different groups. The results revealed that CSAE had protective effects against irradiation-induced immunosuppression, which was likely associated with an antiapoptotic effect and the regulation of adaptive immunity.

As a golden partner of recombinase polymerase amplification (RPA), CRISPR/Cas12a has been proven to solve the false-positive problem caused by nonspecific amplification perfectly; meanwhile, its

The extremely low abundance of circulating tumor DNA in blood samples has limited the development of liquid biopsy techniques for the early diagnosis of major diseases. In this study, we demonstrate a DRN-based screening technique, SCREEN, which achieves the specific capture and enrichment of low abundance SNV nucleic acid samples without selective amplification. The SCREEN technique achieved a 108-fold increase in the abundance of single-nucleotide variant (SNV) nucleic acids from highly homologous mixtures (from 0.01% to 1.08%) and has been shown to significantly increase the abundance of SNV nucleic acids from 0.1% to 51% further through two rounds of capture. As a highly effective pre-enrichment technique, SCREEN has demonstrated the ability to enhance NGS in detecting an ultralow abundance SNV nucleic acid powerfully and has high compatibility with existing molecular diagnostic methods.

The flank faces of diamond cutting tools are characterized by the groove wear when the tools are used to machine single crystal silicon workpieces precisely, which significantly affects the quality of the machined surface. Many researchers confirmed the existence of SiC hard particles and inferred that hard particles scratch led to the groove wear on tools flank face. However, little literature can be found to reveal the formation process of tools groove wear. Therefore, in this paper, a scratch model of SiC hard particles and diamond tool is proposed by molecular dynamics simulation method to investigate the formation mechanism of the groove wear on the tools flank face. The two basic scratch conditions, namely mechanical scratch and rolling scratch, are utilized to simulate hard particles motion on diamond tools surface respectively, and the tools wear are suggested by the variation in coordination numbers. It can be concluded that owing to the high temperature, the locally softened performance of diamond tools combined with continuous effects of SiC hard particles are the main factors that lead to the formation of the groove wear on the tools flank face.

High pressure is an environmental characteristic of the deep sea that may exert critical effects on the physiology and mental abilities of divers. In this study we evaluated the performance efficacy and mental ability of four divers during a 300-meter helium-oxygen saturation dive at sea. Spatial memory, 2D/3D mental rotation functioning, grip strength, and hand-eye coordination ability were examined for four divers during the pre-dive, compression, decompression, and post-dive phases. The results showed that both the reaction time and the correct responses for the mental rotation and hand-eye coordination were slightly fluctuated. In addition, there was a significant decline in the grip strength of the left hand. It is concluded that the performance efficacy and mental ability of divers were virtually unaffected during 300-meter helium-oxygen saturation diving at sea.

Saline-alkaline stress inhibits plant growth and reduces yield. Abscisic acid (ABA) is an important plant hormone in response to plant stress. However, the role of ABA under saline-alkaline stress is poorly understood. Therefore, the mechanisms of ABA accumulation and resistance improvement in tomato seedlings were studied under saline-alkaline stress. We investigated whether ABA accumulation improved the saline-alkaline stress resistance ability of tomato. Here, wild-type (Solanum lycopersicum cv. Ailsa Craig) and ABA-deficient mutant (notabilis) seedlings were used to determine the membrane lipid peroxidation, osmotic substance and chlorophyll contents. ABA synthesis and signal transduction changes and ABA roles regulating the antioxidation in tomato seedlings subject to saline-alkaline stress were further explored. Results showed that ABA synthesis and signal transduction were induced by saline-alkaline stress. Under saline-alkaline stress, tomato seedlings had decreased relative water content, increased relative electrical conductivity and malondialdehyde content, and these changes were alleviated by exogenous ABA treatment. Exogenous ABA alleviated the degradation of chlorophyll in the leaves of tomato seedlings caused by saline-alkaline stress, further promoted the accumulation of proline and soluble sugar, reduced the content of ROS and improved the ability of the antioxidant enzyme system. Moreover, notabilis appeared to be sensitive to saline-alkaline stress. Overall, ABA is involved in the resistance of tomato seedlings to saline-alkaline stress, and exogenous ABA improves the saline-alkaline tolerance of tomato seedlings.

In this paper, networked predictive control is investigated for a networked control system with quantizers by an event-driven strategy. An event generator is designed according to a deviation of state estimation between the current time and last trigger time. A predictive strategy is proposed to compensate effect of network-induced delays and packet dropouts. The quantizers are used to deal with signals by converting real-valued signals into effective ones in both feedback and forward channels. Based on a “zoom” strategy, sufficient conditions are given to ensure stabilization of the networked control system by solving linear matrix inequalities. A simulation example is proposed to exhibit advantages and availability of the developed techniques.

Cordyceps sinensis (CS) is a traditional Chinese medicine that is known for treating various diseases, and particularly for exerting therapeutic effects in immune disorders. The adaptive immunoregulatory effects of CS aqueous extract (CSAE) on γ-irradiated mice have not been reported previously. The study aimed to evaluate the therapeutic effects of CSAE in mice immunosuppressed by irradiation. We observed that CSAE administration significantly increased body weight and spleen index, as well as the number of white blood cells, lymphocytes, and platelets in peripheral blood, T and B lymphocytes in spleen tissue, and total serum immunoglobulins in irradiated mice, whereas total serum pro-inflammatory cytokine levels were decreased. Collectively, CSAE maintained the structural integrity of spleen tissue and repaired its damage in irradiated mice as shown by hematoxylin and eosin staining, and decreased the number of terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling-positive splenocytes. Mechanistically, CSAE upregulated Bcl-2, and downregulated Bax and cleaved caspase-3 in spleen of irradiated mice. However, there were no significant differences in red blood cells and neutrophils in different groups. The results revealed that CSAE had protective effects against irradiation-induced immunosuppression, which was likely associated with an antiapoptotic effect and the regulation of adaptive immunity.

Starch is the major storage carbohydrate in plants, and its metabolism in chloroplasts depends mainly on light. However, the mechanism through which photoreceptors regulate starch metabolism in chloroplasts is unclear. In this study, we found that the cryptochrome 1a (CRY1a)-mediated blue light signal is critical for regulating starch accumulation by inducing starch degradation through the transcription factor HY5 in chloroplasts in tomato. cry1a mutants and HY5-RNAi plants accumulated more starch and presented lower transcript levels of starch degradation-related genes in their leaves than wild-type plants. Blue light significantly induced the transcription of starch degradation-related genes in wild-type and CRY1a- or HY5-overexpressing plants but had little effect in cry1a and HY5-RNAi plants. Dual-luciferase assays, electrophoretic mobility shift assays, and chromatin immunoprecipitation–qPCR revealed that HY5 could activate the starch degradation-related genes PWD, BAM1, BAM3, BAM8, MEX1, and DPE1 by directly binding to their promoters. Silencing of HY5 and these starch degradation-related genes in CRY1a-overexpressing plants led to increased accumulation of starch and decreased accumulation of soluble sugars. The findings presented here not only deepen our understanding of how light controls starch degradation and sugar accumulation but also allow us to explore potential targets for improving crop quality.

Deep learning has brought great progress for the sequential recommendation (SR) tasks. With advanced network architectures, sequential recommender models can be stacked with many hidden layers, e.g., up to 100 layers on real-world recommendation datasets. Training such a deep network is difficult because it can be computationally very expensive and takes much longer time, especially in situations where there are tens of billions of user-item interactions. To deal with such a challenge, we present StackRec, a simple, yet very effective and efficient training framework for deep SR models by iterative layer stacking. Specifically, we first offer an important insight that hidden layers/blocks in a well-trained deep SR model have very similar distributions. Enlightened by this, we propose the stacking operation on the pre-trained layers/blocks to transfer knowledge from a shallower model to a deep model, then we perform iterative stacking so as to yield a much deeper but easier-to-train SR model. We validate the performance of StackRec by instantiating it with four state-of-the-art SR models in three practical scenarios with real-world datasets. Extensive experiments show that StackRec achieves not only comparable performance, but also substantial acceleration in training time, compared to SR models that are trained from scratch. Codes are available at https://github.com/wangjiachun0426/StackRec.

As a kind of special electromagnetic medium, femtosecond laser plasma has the potential of transmitting the electromagnetic wave. In this paper, a theoretical study on 6 GHz EM wave guiding performance of the plasma filament is carried out with the software XFDTD. Then, an experimental setup for the interaction between the EM wave and the plasma filaments is established. Based on the data measured by oscilloscope, the transmission properties of the EM wave along the filament are obtained. The results show the electric field is enhanced out of the waveguide with the plasma filament. The guiding performance of the plasma filament on the TE polarization wave is better than that on the TM one, which is consistent with the experimental results. For TE polarization wave, the plasma filament can reduce the transmission pulse energy greatly and the attenuation is up to 3.5 dB in the experiment. The research results show that the laser plasma filament can provide efficient transmission of the EM wave energy.

Personalized recommendation has been widely applied to many real-world services. Many of recent studies focus on collaborative filtering (CF) by deep neural networks, which pursue to predict users’ preference on items based on the past user–item interactions (e.g., a user rates an item). A general CF approach consists of two key modules, embedding representation learning and interaction modeling. In most existing methods, the embedding module is followed by the interaction modeling module, and the user–item interaction information is only emploited in interaction modeling directly. Existing methods, however, defectively overlook the correlation between users and items, as well as the inherent connection between embedding learning and the interaction information. To fill this gap, we propose neural graph personalized ranking (NGPR) which directly makes use of the user–item interaction information in embedding learning by incorporating the user–item interaction graph in embedding learning. Specifically, we construct the user–item interaction graph using de facto interaction between a user and an item. Correlation between users and items can also be reserved by concatenating representations of users and items in the entire procedure of embedding learning. Moreover, more complicated structures like multilayer perceptron (MLP) can be used in interaction modeling to make the most use of the representations, rather than simple linear transformation. We conduct extensive experiments on three public benchmarks and demonstrate the superior performance of the proposed NGPR model on personalized ranking task. In addition, our ablation studies verify that our novel design to incorporate the user–item interaction graph in embedding learning is effective.

The crystallization of amorphous and cutting process of nanocrystalline copper was investigated by the use of a molecular dynamics (MD) simulation. Stress-induced crystallization of amorphous in cutting process was observed. By the common neighbor analysis (CNA), it was found that nuclei were first formed in the larger stress region around the rake face and tip of the tool and then they grew quickly under stress. The growth and consolidation process of grains was analyzed, using relative atomic displacement vector method. When grains grew in contact with each other, a merger occurred. Grains were combined firstly in a local area, and rotated to discharge the excess free volume out of boundaries before the merging process completed. Through calculating the shear strain of atoms in the cutting process, the serrated chips and four shear bands were observed clearly. The radius distribution function (RDF) curve of the shear band shows that the cutting of crystalline was carried out in the amorphous state. The shear angle of less than 45° was observed in the simulation, which is consistent with the experiments reported and validates the simulation results in this paper.

Rectangles commonly appear in man-made environments. This paper presents an approach for rapid detection of objects with rectangular structures. Considering that the object to be detected may have different textures, colors or other characteristics, only geometric structure information can be used for identification. Therefore, the key task in detecting rectangles is to acquire correct line correspondences. We analyze the reason why a basic frame of 2D homography computation and verification cannot meet the practical requirement for detection speed and then propose a two-step algorithm to solve the problem. First, we utilize a unified expression of homography between an unknown size rectangle and a quadrangle on the image to simplify the homography computation. Second, we propose a rotated cuboid bound constraint of the camera centre to rapidly remove incorrect homographies with unknown size parameters. Experiments with simulated and real data verify the correctness of our method.

This paper proposes a visual teleoperation with human–robot posture-consistent based on deep neural network. A multi-stage structure of visual teleoperation network, in which the angles of robotic joints are obtained from human, is deduced. Furthermore, a novel human–robot posture-consistent mapping method is developed to generate dataset of the visual teleoperation network by solving constrained nonlinear matrix functions. Based on the designed framework, the data generator and a well trained multi-stage visual teleoperation network are presented. Finally teleoperation experiments are implemented to demonstrate that the proposed method is effectiveness and reliable.

Gaussian processes (GPs) are powerful Bayesian nonparametric tools widely used in probabilistic modeling, and the mixture of GPs (MGPs) were introduced afterwards to make data modeling more flexible. However, MGPs are not directly applicable to multiview learning. In order to improve the modeling ability of MGPs, in this paper, we propose a new framework of multiview learning for the MGPs and instantiate it for classification. We make the divergence between views as small as possible while ensuring that the posterior probability of each view is as large as possible. Specifically, we regularize the posterior distribution of latent variables with the consistency of posterior distributions of the latent functions between different views. Since it is intractable to solve the model analytically, the variational inference and optimization algorithms of the classification model are also presented in this paper. Experimental results on multiple real-world datasets have shown that the proposed method has outperformed the original MGP model and several state-of-the-art multiview learning methods, which indicate the effectiveness of the proposed multiview learning framework for MGPs.

Slice sampling provides an automatical adjustment to match the characteristics of the distribution. Although this method has made great success in many situations, it becomes limited when the distribution is complex. Inspired by Higdon [1], in this paper, we present a decomposed sampling framework based on slice sampling called decomposed slice sampling (DSS). We suppose that the target distribution can be divided into two multipliers so that information in each term can be used, respectively. The first multiplier is used in the first step of DSS to obtain horizontal slices and the last term is used in the second step. Simulations on four simple distributions indicate the effectiveness of our method. Compared with slice sampling and Hamiltonian Monte Carlo on Gaussian distributions in different dimensions and ten real-world datasets, the proposed method achieves better performance.

For college students majoring in English, English writing is a relatively difficult project. How to effectively improve the English writing ability of students of English majors in vocational colleges is an important issue that every college teacher needs to pay attention to. As a teaching tool, the intelligent computer automated essay evaluation system can help students improve their English writing ability more objectively, efficiently and accurately. This paper employs the intelligent computer automated essay evaluation system as a teaching tool, taking college students as the research object, and carried out an 18-week online self-writing teaching experiment and traditional writing experiment. This paper conducts a comparative study on the washback effects of teacher feedback plus intelligent feedback versus teacher feedback on English writing teaching in higher vocational college, which provides a prominent research value and research significance for the reform and innovation of English writing teaching in higher vocational colleges.

As machine learning evolves, it is significant to apply machine learning techniques to the intelligent analysis on educational data and the establishment of more intelligent academic early warning system. In this paper, we use Gaussian process (GP)-based models to discover valuable inherent information in the educational data and make intelligent predictions. Specifically, the mixtures of GP regression model is adopted to select personalized key courses and the GP regression model is applied to predict the course scores. We conduct experiments on real-world data which are collected from two grades in a certain university. The experimental results show that our approaches can make reasonable analysis on educational data and provide prediction information about the unknown scores, thus helping to make more precise academic early warning.

It has been shown that the regulatory mechanisms of Ca(2+) signaling between tumor and normal cells are different, providing new insight into the pharmacological modulation of anticancer drugs. However, it remains unclear whether there is any difference between hepatoma and normal hepatic cells in their response to extracellular Ca(2+) ([Ca(2+)]e). In the present study, the growth inhibition, apoptosis and necrosis rates of human normal embryo hepatic L02 and human hepatoma HepG2 cells exposed to additional calcium ([Ca(2+)]a)and adriamycin (ADM), a chemotherapeutic agent to treat hepatocellular carcinoma, were measured by MTT and annexin V/PI assays, respectively. The results showed that the growth inhibition, necrosis and apoptosis rates, as well as intracellular Ca(2+) concentrations ([Ca(2+)]i) induced by [Ca(2+)]e in HepG2 cells were higher than those in L02 cells. Moreover, [Ca(2+)]e was able to selectively enhance ADM-induced growth inhibition, apoptosis and necrosis in HepG2 cells, but not in L02 cells. ADM and [Ca(2+)]a co-treatment had a significant interaction effect to increase [Ca(2+)]i in both cell lines, although there was no significant difference in [Ca(2+)]i between the two cells. To further elucidate the mechanisms involved in the selective promotion of [Ca(2+)]e in HepG2 and L02 cells, the levels of these apoptosis regulatory proteins (bcl-2, bax and procaspase-3) and the caspase-3 activity following treatment of HepG2 and L02 cells with ADM or/and [Ca(2+)]a were investigated. The results showed that treating HepG2 cells with [Ca(2+)]a and ADM increased the level of bax protein and caspase-3 activity while decreasing the level of bcl-2 protein, compared with treatment with ADM alone. However, no significant change was noted in L02 cells. These results indicate that hepatoma HepG2 cells are more sensitive to [Ca2+]e than normal hepatic L02 cells and that [Ca(2+)]a can selectively enhance ADM-induced cell death in HepG2 cells. The mechanism of this intensive pro-apoptotic effect can be ascribed to up-regulation of bax and the simultaneous down-regulation of bcl-2, followed by the switch from procaspase-3 to caspase-3, which executed apoptosis. The present data suggest the potency of the calcium ion as an enhancer of ADM.

With the development of social networks and wireless communication technology, location-based social networks (LBSNs) are developing rapidly. Personalized location service in location-based social networks can provide users with a new point-of-interest (POI). Compared to traditional recommendation, point-of-interest recommendation integrates the social network with the location that connects online users and physical places. In current studies, user preference, social influence and geographical influence are mostly taken into consideration to recommend satisfying point-of-interests to users. Although geographical context is significant, most articles only consider spatial properties of geographical influence. In addition to spatial properties of geographical influence, we put a special emphasis on sequence properties of that to exploit implicit dependencies between POIs. We model spatial properties using a kernel density estimation approach to generate a unique distribution for each user. Furthermore, user preference, social influence, and sequence properties of geographical influence are integrated into a random walk model on graph. Finally, we conduct a comprehensive performance evaluation over two real-world datasets collected from Brightkite and Gowalla. Experimental results show that the proposed recommendation approach performs better than other methods.

Alpha-lipoic acid (α-LA) is an important antioxidant that is capable of regenerating other antioxidants, such as glutathione (GSH). However, the underlying molecular mechanism by which α-LA regenerates GSH remains poorly understood. The current study aimed to investigate whether α-LA regenerates GSH by activation of Nrf2 to alleviate cadmium-induced cytotoxicity in HepG2 cells. In the present study, we found that cadmium induced cell death by depletion of GSH through inactivation of Nrf2. Addition of α-LA to cadmium-treated cells reactivated Nrf2 and regenerated GSH through elevating the Nrf2-downstream genes γ-glutamate-cysteine ligase (γ-GCL) and GR, both of which are key enzymes for GSH synthesis. However, blocking Nrf2 with brusatol in the cells co-treated with α-LA and cadmium reduced the mRNA and the protein levels of γ-GCL and GR, thus suppressed GSH regeneration by α-LA. Our results indicated that α-LA activated Nrf2 signaling pathway, which upregulated the transcription of the enzymes for GSH synthesis and therefore GSH contents to alleviate cadmium-induced cytotoxicity in HepG2 cells.

The propagation of electromagnetic (EM) wave along a plasma filament induced by the sufficiently intense femtosecond laser pulse is studied with the commercial simulation software XFDTD. The simulated results show that the EM wave can propagate along the plasma filament, with the electric field enhanced out of the waveguide and attenuated in the waveguide. Besides, we can conclude that the relative direction between the plasma filament and the electric field can influence the guiding performance of the plasma filament. Furthermore, a maximum EM wave intensity enhancement more than threefold the free space propagation is realized. The research results imply that the laser-induced plasma filament can provide efficient transmission of the EM wave energy. Keywords: EM wave, Femtosecond laser, Plasma filament, Propagation, XFDTD

The curing temperature is known to influence the rate of mechanical properties development of early age concrete. In realistic sites the temperature of concrete is not isothermal 20 0C, so the paper measured adiabatic temperature increases of four different concretes to understand heat emission during hydration at early age. The temperature-matching curing schedule in accordance with adiabatic temperature increase is adopted to simulate the situation in real massive concrete. The specimens under temperature-matching curing are subjected to realistic temperature for first few days as well as adiabatic condition. The mechanical properties including compressive strength, splitting strength and modulus of elasticity of concretes cured under both temperature-matching curing and isothermal 20 0C curing are investigated. The results denote that comparing temperature-matching curing with isothermal 20 0C curing, the early age concretes mechanical properties are obviously improved, but the later mechanical properties of concretes with pure Portland and containing silica fume are decreased a little and still increased for concretes containing fly ash and slag. On this basement using an equivalent age approach evaluates mechanical properties of early age concrete in real structures, the model parameters are defined by the compressive strength test, and can predict the compressive strength, splitting strength and elasticity modulus through measuring or calculating by finite element method the concreted temperature at early age, and the method is valid, which is applied in a concrete wall for evaluation of crack risking.

Radar, as the main detection means, plays an extremely important role in modern warfare. However, it is easily attacked by the electromagnetic pulse (EMP) weapon. In order to defense the threat, a radome formed by plasma is designed. The plasma radome is used to protect the radar systems against EMP coupling through both ‘front door’ and ‘back door’. What’s more, the damage effects of EMP to the radar systems are analyzed, and the protection mechanism of plasma to EMP weapon is discussed. In addition, a simulation experiment is carried out to verify the feasibility of the plasma radome to defense against EMP. The results indicate that the structure performs well, which makes it a new method against EMP weapon.

In the process of cutting silicon by natural diamond tools, groove wear happens on the flank face of cutting tool frequently.Scholars believe that one of the wear reasons is mechanical scratching effect by hard particles like SiC. To reveal the mechanical scratching mechanism, it is essential to study changes in the mechanical properties of hard particles and diamond, especially the effect of cutting temperature on hardness of diamond and hard particles. Molecular dynamics (MD) model that contact-zone temperature between tool and workpiece was calculated by dividing zone while nano-cutting monocrystalline silicon was established, cutting temperature values in different regions were computed as the simulation was carried out.On this basis, the models of molecular dynamics simulation of SiC and diamond were established separately with setting the initial temperature to room temperature. The laws of length change of C-C bond and Si-C bond varing with increase of simulation temperature were studied. And drawing on predecessors' research on theoretical calculation of hardness of covalent crystals and the relationship between crystal valence electron density and bond length, the curves that the hardness of diamond and SiC varing with bond length were obtained. The effect of temperature on the hardness was calculated. Results show that, local cutting temperature can reach 1300K.The rise in cutting temperature leaded to a decrease in the diamond local atomic clusters hardness,SiC local atomic clusters hardness increased. As the cutting temperature was more than 1100K,diamond began to soften, the local clusters hardness was less than that of SiC.

α-Lipoic acid (α-LA) is a potent natural antioxidant, which is capable of regenerating glutathione (GSH). However, the mechanisms by which α-LA regenerates reduced glutathione (rGSH) via the reduction of oxidized glutathione (GSSG) by glutathione reductase (GR) are still not well understood. In the present study, we investigated if α-LA replenished rGSH by GR via Nrf2/ARE signaling pathway in cadmium-treated HepG2 cells. We found that α-LA antagonized the oxidative damage and alleviated the cytotoxicity in cadmium-induced HepG2 cells by regeneration of rGSH. α-LA regenerated rGSH by activating Nrf2 signaling pathway via promoting the nuclear translocation of Nrf2, which upregulates the transcription of GR, and thus increased the activity of GR. Our results indicated that α-LA was an effective agent to antagonize the oxidative stress and alleviate the cytotoxicity in cadmium-treated HepG2 cells by regenerating rGSH through activating Nrf2 signaling pathway.