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The interaction mechanism between micropiles and soil landslides is comprehensively investigated through static model tests and numerical simulations. The results show that the deformation damage mode of micropiles is mainly bending and shear damage. Because of bending deformation, cracks appear at the rear and front of the pile, respectively, about three times the pile diameter from the sliding surface. In addition, the plastic damage becomes more severe when approaching the back edge of the landslide body. Micropiles in the landslide body play a significant role in load sharing; more importantly, there is a certain pattern between the miniature piles. According to the experimental and numerical simulation results, the recommended load-sharing ratio for micropile design under static conditions is as follows: rear-row pile:middle-row pile:front-row pile = 0.411:0.348:0.241. The research in this paper reveals the good effect of micropiles against landslides, explains the mechanism of pile–soil interaction, and provides a theoretical reference for the research and application of micropiles in engineering.

CD8+ T cells can recognize peptides presented by class I human leukocyte antigen (HLA-I) of nucleated cells. Exploring this immune mechanism is essential for identifying T-cell vaccine targets in cancer immunotherapy. Over the past decade, the wealth of data generated by experiments has spawned many computational approaches for predicting HLA-I binding, antigen presentation and T-cell immune responses. Nevertheless, existing HLA-I binding and antigen presentation prediction approaches suffer from low precision due to the absence of T-cell receptor (TCR) recognition. Direct modeling of T-cell immune responses is less effective as TCR recognition’s mechanism still remains underexplored. Therefore, directly applying these existing methods to screen cancer neoantigens is still challenging. Here, we propose a novel immune epitope prediction method termed IEPAPI by effectively incorporating antigen presentation and immunogenicity. First, IEPAPI employs a transformer-based feature extraction block to acquire representations of peptides and HLA-I proteins. Second, IEPAPI integrates the prediction of antigen presentation prediction into the input of immunogenicity prediction branch to simulate the connection between the biological processes in the T-cell immune response. Quantitative comparison results on an independent antigen presentation test dataset exhibit that IEPAPI outperformed the current state-of-the-art approaches NetMHCpan4.1 and mhcflurry2.0 on 100 (25/25) and 76% (19/25) of the HLA subtypes, respectively. Furthermore, IEPAPI demonstrates the best precision on two independent neoantigen datasets when compared with existing approaches, suggesting that IEPAPI provides a vital tool for T-cell vaccine design.

Appropriate vibration parameters can improve the efficiency of vibration harvesting, so the selection of vibration harvesting parameters is very important. In this paper, the stress of olive fruit is analyzed, and the vibration of olive tree is tested and simulated. Design-Expert 12.0 is used for experimental design, The diameter, height and angle of main branches were selected as the test factors, and the optimal vibration frequency and force were selected as the evaluation indexes. determines the optimal vibration frequency through modal analysis; the optimum vibration force is determined by harmonic response analysis and test. The quadratic polynomial response regression model of optimal vibration frequency and optimal vibration force is obtained. The research results can provide reference for the design of Vibrating harvester.

The Li-ion batteries (LIBs) with ultra-fast charge/discharge behavior and long-term cyclic performance are highly desirable for many applications. Herein, the three-dimensional graphene (3DG) with rich surface-pores, which was synthesized directly from Na-reduction of CO2, was demonstrated as an efficient anode for LIBs. The 3DG anode exhibited a very high discharge capacity of 972 mA h g−1 at 0.2C and an outstanding reversible capacity of 277 mA h g−1 at an extremely high current density of 150C (55.8 A g−1). Furthermore, a discharge capacity of 280 mA h g−1 was obtained after 10 000 cycles at 50C, reaching a high capacity retention of 91.9%. Such an excellent electrochemical performance was attributed to the large specific surface area of 3DG and its rich surface-micropores as well as its numerous oxygen-induced defects. This provides a new door to develop highly efficient electrodes from a greenhouse gas for long-life and ultrafast-charging LIBs.

Herein, an excellent anode material, which comprised the 3D fungus-structured carbon (3DFC) and the CuC2O4·xH2O nanocrystal, was demonstrated for lithium ion batteries (LIBs). The hierarchically porous carbon provided an ideal structure for rapid electron and ion transport and the unique redox properties of CuC2O4·xH2O nanocrystals inhibited the formation of a solid electrolyte interphase, leading to excellent C-rate capacity and cycling stability. The LIBs with the 3DFC@CuC2O4·xH2O anode exhibited reversible capacities of 1158.6 mA h g−1 at 0.5C rate, 593.1 mA h g−1 at 10C, and 250 mA h g−1 at 100C rate (1C = 372 mA h g−1). Furthermore, excellent capacity recycling stability was obtained even at very high C rates, namely, the capacity retention after 1000 cycles still achieved 93.8% at 10C rate and 92.4% at 100C rate. In addition, only 21.8 seconds at 100C was needed for the battery to complete the charging process.

Paclitaxel is a widely used anti-tumor drug. Currently, paclitaxel can only be extracted from plants or synthesized by chemical semi-synthesis, which cause environmental damage and cannot meet the growing demand. However, the complete biosynthetic pathway of paclitaxel is still not clear, which greatly limits the production of paclitaxel using methods such as synthetic biology. Here, we deduced the paclitaxel biosynthetic pathway by searching all possible intermediates in the paclitaxel synthesis pathway from the natural product databases. In addition, we performed the transcriptome sequencing of Taxus brevifolia and performed co-expression analysis of the identified genes in the paclitaxel synthesis pathway. All these results laid a solid foundation for the elucidation of paclitaxel biosynthetic pathway.

It is important to obtain accurate information about kiwifruit vines to monitoring their physiological states and undertake precise orchard operations. However, because vines are small and cling to trellises, and have branches laying on the ground, numerous challenges exist in the acquisition of accurate data for kiwifruit vines. In this paper, a kiwifruit canopy distribution prediction model is proposed on the basis of low-altitude unmanned aerial vehicle (UAV) images and deep learning techniques. First, the location of the kiwifruit plants and vine distribution are extracted from high-precision images collected by UAV. The canopy gradient distribution maps with different noise reduction and distribution effects are generated by modifying the threshold and sampling size using the resampling normalization method. The results showed that the accuracies of the vine segmentation using PSPnet, support vector machine, and random forest classification were 71.2%, 85.8%, and 75.26%, respectively. However, the segmentation image obtained using depth semantic segmentation had a higher signal-to-noise ratio and was closer to the real situation. The average intersection over union of the deep semantic segmentation was more than or equal to 80% in distribution maps, whereas, in traditional machine learning, the average intersection was between 20% and 60%. This indicates the proposed model can quickly extract the vine distribution and plant position, and is thus able to perform dynamic monitoring of orchards to provide real-time operation guidance.

Extraction and segmentation of kiwifruit vine range is an important part of precision agriculture in kiwifruit orchard. In this paper, depth semantic segmentation and traditional machine learning are used to segment and extract kiwifruit vines from orthophoto images, and the accuracy and image quality of vine segmentation based on pspnet, SVM and random forest classification in another test set are compared. Experimental results show that although the mean pixel accuracy of deep semantic segmentation is slightly lower than that of traditional machine learning segmentation, the segmentation image quality of deep semantic segmentation is better and the pixels are more continuous. The deep learning method effectively developed UAV remote sensing image data, improved the usability of remote sensing image, and provided necessary plant information for orchard precision agriculture.

Mesoporous silica has aroused lots of interest in biomedical fields, in which novel kinds of mesoporous silica with tunable mesoporosity and size have attracted much attention, but functionalization or multi-functionalization inside the mesopores of these structures is still rarely detected. Among all the functionalized molecules, beta cyclodextrin hydrate (β-CD), a kind of hydrophilic non-toxic carrier for hydrophobic drugs, can increase the solubility and bioavailability of drugs, acting as a pH responsive "gate" when functionalized on the surface of mesoporous silica. Herein, we functionalized β-CD inside novel kinds of mesoporous silica or magnetic mesoporous silica as the physical binding sites for the model drug curcumin through an out-inside two step bifunctionalization process including a vacuum pumping recrystallization drug loading process. According to the physical characterization with XRD, FT-IR, XPS, solid state NMR, BET, TG, DTA, TEM and DLS, the drug delivery nanosystems were successfully fabricated and contained nano-formulations of curcumin. In vitro cell testing, including Cell Counting Kit-8, Hoechst 33342 staining, hemolysis experiments and cell apoptosis, indicated that through the bifunctionalization, the biocompatibility of the mesoporous silica with cells could be improved, and the toxicity of the drug delivery nano-formulations towards two kinds of cancer cells, SK-HEP1 and HepG2, was significantly increased compared with free curcumin. In vitro release studies revealed that the nano-formulations contained more suspended curcumin molecules as described by the Higuchi models and showed enhanced pH responsive release properties, and that the magnetic nano-formulations exhibited alternating magnetically controlled release properties. The confocal microscopy analysis results revealed the obviously increasing intercellular release and uptake of both nano-formulations of curcumin by SK-HEP1 cells and the "on" and "off" stages of the alternating magnetism responsive intercellular release properties of the fabricated magnetic nano-formulations. The bifunctionalization process combined with the nanostar structure has immense potential in the drug delivery field, especially for hydrophobic drugs.

In this study, we propose outside-in stepwise functionalization of MCM-41-type mesoporous silica for use as a high-efficiency matrix drug delivery nanosystem aimed at the insoluble antibacterial agent fluoroquinolone. Thiol (–SH) modification on the surface of the nanocarrier and aminopropyl groups (–NH2) in the channels give the system a framework for sustained drug release for 72 h with drug loading capacity of 58.64% as a result of the completely opposite electrostatic interaction between drug molecules of thiol and amino. Unusually, abundant crystals of drug molecules were observed by transmission electron microscopy (TEM) in channels of the nanocarriers, caused by self-organization under the electrostatic attraction of the grafting groups. The elevated crystallinity of drug molecules loaded in the functional mesoporous MCM-41 nanoparticles was proved also through wide-angle XRD. Analysis of the release profiles highlighted the low cytotoxicity and excellent biocompatibility of the modified nanocarriers in vitro. Compared with single functionalization, the outside-in stepwise process can completely modify the deep inner of the channel and achieve effective internal drug loading of mesoporous materials. We believe that this method is not only of use for framework sustained-release tablets, but also other clinical medicine and chemical engineering.

In order to offer a scientific basis for cultivation and management of forests, effects of light radiation intensity on photosynthetic characteristics and water use efficiency of Platycladus orientalis and Pinus tabulaeformis were studied under different soil moisture contents. By adopting artificial control methods to soil moisture, and under simulated photosynthetic radiation (SPR), the net photosynthetic rate (P N), transpiration rate (T r), water use efficiency (WUE) and intercellular CO2 concentration (C i) of Platycladus orientalis and Pinus tabulaeformis in the semi-arid region of the Loess Plateau, were studied. Results are as follows: within the photon range of 0–2,200 μmol/(m2·s), P N, T r and WUE were enhanced with an increase in SPR in both species. P N and WUE of Platycladus orientalis and Pinus tabulaeformis, however, declined with continued increase in SPR. P N, T r, WUE and light saturation point (LSP) of Platycladus orientalis were higher than those of Pinus tabulaeformis, while light compensation point (LCP) of Platycladus orientalis was lower than that of Pinus tabulaeformis at the same soil moisture content. The efficiency of light energy utilization of Platycladus orientalis was higher than that of Pinus tabulaeformis; P N, T r and C i of Platycladus orientalis and Pinus tabulaeformis were enhanced by increasing soil moisture content, whereas WUE declined. At soil moistures of 7.90%, 13.00% and 19.99%, LSP of Platycladus orientalis was 1,275, 1,450 and 1,675 μmol/(m2·s) respectively, and LCP was 42, 25 and 13 μmol/(m2·s) respectively, with corresponding maximal net CO2 photosynthetic rates (P max) of 3.04, 4.06 and 5.53 μmol/(m2·s). At soil moistures of 7.83%, 13.04% and 20.15%, the LSP of Pinus tabulaeformis was 1,100, 1,325 and 1,500 μmol/(m2·s) respectively, and LCP was 60, 30 and 23 μmol/(m2·s), with P max of 1.08, 3.35 and 4.36 μmol/(m2·s) respectively.

The past decade has witnessed dramatic changes and impressive progress in interpreter training in China due to technological innovations, policy support from the Ministry of Education, increasing demand for qualified interpreters in the market, and ceaseless efforts from interpreting trainers and researchers. Meanwhile, research efforts have been made in the integration of information and communication technology (ICT) into interpreter training. Chinese researchers have explored a wide range of pedagogical factors in this regard, including training models, principles, materials and strategies as well as autonomous learning, assessment and trainer/trainee roles. This paper reviews the major studies in this field and may serve as a reference for international interpreting practice and research. It argues that more attention should be focused on micro-perspectives, more empirical research methods are to be adopted, and more professional training tools are to be developed and tried out.