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In order to improve the precision of phase recognition and reduce the rate of misdetection, this paper applies the deep learning method to automatic phase recognition. In this paper, an automatic seismic phase recognition model based on the Bi-LSTM network is designed. To test the performance of this model, the STEAD dataset is used for training and testing, and this model is compared with the traditional STA/LTA and AIC methods. The experimental results show that, compared to STA/LTA and AIC methods, the Bi-LSTM network can reduce the misdetection rate by about 8–15%, and improve the RSEM; especially, the prediction error of S-wave is greatly reduced.

Most space shuttle fuel tanks use a center column to hold the Propellant Management Device (PMD). This paper analyzes the gas–liquid interface state in the tanks with a central column during microgravity experiments conducted in the Chinese Space Station. It launches an extended study to investigate the gas–liquid interface state under different gravity conditions. Using the perturbation method and boundary layer theory, we numerically calculated the morphology of the gas–liquid interface under varying gravity conditions based on the Young–Laplace equation. The results were then compared to those obtained from existing commercial software and were found to be consistent. Based on this, the study develops two types of calculation procedures. The first procedure generates the corresponding shape of the liquid surface by inputting the height of the liquid surface endpoints and the gravity level. The second procedure is based on the targeting method and generates the corresponding liquid surface by inputting the volume of the liquid in the storage tank and the gravity level. The procedures were used to analyze the variation of gas–liquid interface properties under different gravity conditions. This study offers theoretical support for liquid management in aerospace engineering fuel tanks.

Abstract One challenge for realizing high-efficiency electrocatalysts for CO2 electroreduction is lacking in comprehensive understanding of potential-driven chemical state and dynamic atomic-configuration evolutions. Herein, by using a complementary combination of in situ/operando methods and employing copper single-atom electrocatalyst as a model system, we provide evidence on how the complex interplay among dynamic atomic-configuration, chemical state change and surface coulombic charging determines the resulting product profiles. We further demonstrate an informative indicator of atomic surface charge (φ e) for evaluating the CO2RR performance, and validate potential-driven dynamic low-coordinated Cu centers for performing significantly high selectivity and activity toward CO product over the well-known four N-coordinated counterparts. It indicates that the structural reconstruction only involved the dynamic breaking of Cu–N bond is partially reversible, whereas Cu–Cu bond formation is clearly irreversible. For all single-atom electrocatalysts (Cu, Fe and Co), the φ e value for efficient CO production has been revealed closely correlated with the configuration transformation to generate dynamic low-coordinated configuration. A universal explication can be concluded that the dynamic low-coordinated configuration is the active form to efficiently catalyze CO2-to-CO conversion.

Based on the self-made Zr0.5Hf0.5C precursor and commercial liquid polycarbosilane, C/Zr0.5Hf0.5C-SiC composite was successfully prepared by the precursor impregnation and pyrolysis(PIP) process. The influence of the thickness of pyrolytic C coating on the structure and bending properties of composite materials was studied. The results show that the self-made Zr0.5Hf0.5C precursor can be converted into Zr0.5Hf0.5C solid solution at a relatively low temperature of 1400 ℃. Because of its good permeability, the transformed Zr0.5Hf0.5C matrix exists in both the inter-bundle and intra-bundle regions of the C/Zr0.5Hf0.5C-SiC composite, which presents as a layered structure on SiC matrix. The phase composition of C/Zr0.5Hf0.5C-SiC composite mainly includes C, SiC and Zr0.5Hf0.5C. The densities of three groups of composites with different thicknesses of pyrolytic C coating (0.67, 0.84, 1.36 μm) are 2.07, 1.99, 1.98 g/cm3, respectively. SiC content in the composite decreases with the increase of the thickness of pyrolytic C coating. The three groups of composites with different thicknesses show pseudoplastic fracture mode during bending loading tests, bending strength, bending modulus and fracture toughness are above 410 MPa, 60 GPa and 15.6 MPa·m1/2, respectively. Good interface bonding and pre-introduced SiC matrix are the keys to obtaining excellent bending properties of C/Zr0.5Hf0.5C-SiC composites.

Using carbon fiber cloth with different areal densities and tow sizes, two kinds of carbon fiber preforms with same carbon cloth laminated structure were produced through different z-direction stitching methods. Then, C/C-SiC composites were prepared by combining chemical vapor infiltration (CVI) with gas silicon infiltration (GSI). The influence of carbon fiber preform structure on the microstructure and mechanical properties of CVI-GSI C/C-SiC composites was studied. The results show that the density, phase composition, structure, and properties of the two composites prepared from preforms with the same fiber volume fraction and C/C preform density are significantly different. The smaller carbon fiber tow (1K) and carbon cloth surface density (92 g/m2), as well as the larger voids left by lock stitching, provide more sufficient channels for the infiltration of Si vapor in the GSI reaction process. Thus T1 composite finally prepared has low porosity, uniform structure, and higher performance, with bending strength, modulus, and fracture toughness of 300.97 MPa, 51.75 GPa, and 11.32 MPa·m1/2, respectively. The comprehensive control of the initial preform structure and the C/C intermediate structure is the key to the preparation of high performance C/C-SiC composites by the CVI-GSI process.

The rapid development of Internet of vehicles (IoV) depends on the safe and reliable infrastructure for storing and sharing large amounts of data. Blockchain, a kind of distributed data storage technology that cannot be forged and tampered with, can solve the security and privacy issues of IoV. However, the low throughput of blockchain hinders its wide application in IoV. The current research on blockchain throughput optimization has poor scalability because of its action space explosion. Aiming at the above problems, a blockchain throughput optimi-zation method in IoV based on deep reinforcement learning (DRL) is proposed to maximize the transaction throughput, and optimize the throughput of the blockchain by choosing block producers and consensus algorithms, adjusting block size and block interval while ensuring the decentralization, low delay and high security of the underlying blockchain system. This method introduces the branching dueling Q-network (BDQ) framework in DRL, carries out fine-grained division for action space, and solves the problem of action space explosion of traditional deep reinforcement learning methods. Simulation results show that the proposed method can improve the throughput of blockchain in IoV effectively.

The microthruster is generally chosen as the actuator of the drag-free satellite control system, and the layout directly affects the stability of the satellite control. Due to the extremely rigorous objectives of drag-free control, a design method for the redundant thruster layout is proposed in this paper to improve the control stability of the satellite and reduce the allocation error of the control system. First, the factors corresponding to the allocation errors of redundant thruster layouts are analyzed. And the minimum number of thrusters required for satellite control is determined through the calculation method of thruster redundancy. Then, the design criterion of reducing the allocation error and increasing the satellite control stability is put forward. To demonstrate the effectiveness and feasibility of the design method proposed in this paper, the space gravitational wave detection satellite is taken as a simulation case. Thrust distribution models corresponding to the designed thruster layouts are established, and the results show that a proper layout can not only improve stability but also reduce fuel consumption. The research is looking forward to providing a reference for designing the microthruster layout of the gravitational wave detection satellite in the future.

The chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing (CMTM) family includes CMTM1–8 and CKLF, and they play key roles in the hematopoietic, immune, cardiovascular, and male reproductive systems, participating in the physiological functions, cancer, and other diseases associated with these systems. CMTM family members activate and chemoattract immune cells to affect the proliferation and invasion of tumor cells through a similar mechanism, the structural characteristics typical of chemokines and transmembrane 4 superfamily (TM4SF). In this review, we discuss each CMTM family member’s chromosomal location, involved signaling pathways, expression patterns, and potential roles, and mechanisms of action in pancreatic, breast, gastric and liver cancers. Furthermore, we discuss several clinically applied tumor therapies targeted at the CMTM family, indicating that CMTM family members could be novel immune checkpoints and potential targets effective in tumor treatment.

In view of the future development trend of ocean altimetry satellites, the design idea of Ka/C dual frequency combination system is proposed, that is, the mode of using an altimeter antenna to contain Ka and C frequencies (35.7 and 5.3 GHz, respectively) for combined ranging. First, the random error model of altimeter measuring the distance from the altimeter phase center to the sea surface is given, and the analysis shows that the ionospheric correction error is one of the important factors. Second, the calculation of typical ionospheric parameters shows that the influence of ionospheric higher order terms on altimeter ranging is below the mm level, and its influence can be ignored. The rigorous expression for the first-order and second-order term correction of ionosphere error are given, respectively, by using dual frequency and three frequencies. The computational experiment of Jason-2 and SARAL satellite show that the maximum magnitude of ionospheric error correction in Ku band can reach 11 cm, while the maximum magnitude of ionospheric error correction in Ka band can reach 2 cm. For high-precision applications, ionospheric corrections must be made for single Ka frequency. After Ka/C dual frequency combination is adopted, error correction can be directly conducted without global ionospheric map (GIM) model, and its accuracy will be further improved than GIM model. Under 1 Hz sampling conditions, the ionospheric correction accuracy of Ka/C combination can be better than 2.5 mm, basically eliminating the influence of the ionosphere, and the total ranging accuracy can reach 3.5 cm considering the propagation error.

Upland cotton accounts for a high percentage (95%) of the world’s cotton production. Plant height (PH) and branch number (BN) are two important agronomic traits that have an impact on improving the level of cotton mechanical harvesting and cotton yield. In this research, a recombinant inbred line (RIL) population with 250 lines developed from the variety CCRI70 was used for constructing a high-density genetic map and identification of quantitative trait locus (QTL). The results showed that the map harbored 8298 single nucleotide polymorphism (SNP) markers, spanning a total distance of 4876.70 centimorgans (cMs). A total of 69 QTLs for PH (9 stable) and 63 for BN (11 stable) were identified and only one for PH was reported in previous studies. The QTLs for PH and BN harbored 495 and 446 genes, respectively. Combining the annotation information, expression patterns and previous studies of these genes, six genes could be considered as potential candidate genes for PH and BN. The results could be helpful for cotton researchers to better understand the genetic mechanism of PH and BN development, as well as provide valuable genetic resources for cotton breeders to manipulate cotton plant architecture to meet future demands.

In this study, alumina ceramics with hierarchical pores were successfully fabricated using freeze casting. Experimental studies show that both the solid loading of the slurry and the thermal insulation layer at the interface of the slurry and cooling plate can influence the pore characteristics of cast samples. In order to examine the pore characteristics and evaluate the permeability of the freeze-cast samples fabricated under different conditions, a generative adversarial network (GAN) method was employed to reconstruct the three-dimensional (3D) microstructure from two-dimensional (2D) scanning electron microscopy (SEM) images of the samples. Furthermore, GAN 3D reconstruction was validated against X-ray tomography 3D reconstruction results. Based on the GAN reconstructed microstructures, the permeability and pore distribution of the various samples were analyzed. The sample cast with 35 wt.% solid loading shows an optimal permeability.

Background: Iodiene-131 (131I) treatment is the primary therapeutic approach for imaging 131I-avid pulmonary metastases. The response to radioiodine (RAI) treatment is an important prognostic factor in patients with pulmonary metastases from differentiated thyroid cancer (DTC). Patients who achieve an excellent response (ER) to 131I treatment show significantly reduced disease-related mortality. This study aimed to retrospectively analyse the clinical data and therapeutic effects of 131I treatment in patients with DTC and pulmonary metastases and to screen out the clinical factors affecting ER. Materials and methods: The study included a total of 75 patients with exclusively Iodine-131 avid (131I-avid) pulmonary metastases who underwent 131I treatment. Relevant clinical data for these patients were collected. Following treatment, the status of DTC metastatic lesions was categorized as follows: excellent response (ER), biochemical incomplete response (BIR), structural incomplete response (SIR), or indeterminate response (IDR). Gender, age at diagnosis, pathological type, stages (TNM), stimulated thyroglobulin (sTg) value before initial 131I treatment, metastatic nodule size, and type of post-treatment whole body scan (Rx-WBS) were recorded. Mono-factor analysis and binary logistic regression analyses were used to identify the factors that might affect the ER in DTC pulmonary metastases. The receiver operating characteristic (ROC) curve of the sTg value was used to predict the ER of 131I treatment. Results: All 75 patients with exclusively 131I-avid pulmonary metastases received 131I treatment and underwent follow-up. Out of the 75 patients, 26 achieved ER, resulting in an excellent response rate of 34.7 % (26/75). Among them, 25 (25/26, 96.2 %) achieved an ER after undergoing two rounds of 131I treatment. Binary logistic regression analysis showed that the factors influencing DTC pulmonary metastases excellent response were lower sTg levels [odds ratio (OR) = 0.998, P

Human cancers induce a chaotic, dysfunctional vasculature that promotes tumor growth and blunts most current therapies; however, the mechanisms underlying the induction of a dysfunctional vasculature have been unclear. Here, we show that split end (SPEN), a transcription repressor, coordinates rRNA synthesis in endothelial cells (ECs) and is required for physiological and tumor angiogenesis. SPEN deficiency attenuated EC proliferation and blunted retinal angiogenesis, which was attributed to p53 activation. Furthermore, SPEN knockdown activated p53 by upregulating noncoding promoter RNA (pRNA), which represses rRNA transcription and triggers p53-mediated nucleolar stress. In human cancer biopsies, a low endothelial SPEN level correlated with extended overall survival. In mice, endothelial SPEN deficiency compromised rRNA expression and repressed tumor growth and metastasis by normalizing tumor vessels, and this was abrogated by p53 haploinsufficiency. rRNA gene transcription is driven by RNA polymerase I (RNPI). We found that CX-5461, an RNPI inhibitor, recapitulated the effect of Spen ablation on tumor vessel normalization and combining CX-5461 with cisplatin substantially improved the efficacy of treating tumors in mice. Together, these results demonstrate that SPEN is required for angiogenesis by repressing pRNA to enable rRNA gene transcription and ribosomal biogenesis and that RNPI represents a target for tumor vessel normalization therapy of cancer.

Abstract Cellular senescence plays a pivotal role in wound healing. At the initiation of liver fibrosis regression, accumulated senescent cells were detected and genes of senescence were upregulated. Flow cytometry combined with single‐cell RNA sequencing analyses revealed that most of senescent cells were liver nonparenchymal cells. Removing senescent cells by dasatinib and quercetin (DQ), alleviated hepatic cellular senescence, impeded fibrosis regression, and disrupted liver sinusoids. Clearance of senescent cells not only decreased senescent macrophages but also shrank the proportion of anti‐inflammatory M2 macrophages through apoptotic pathway. Subsequently, macrophages were depleted by clodronate, which diminished hepatic senescent cells and impaired fibrosis regression. Mechanistically, the change of the epigenetic regulator enhancer of zeste homolog2 (EZH2) accompanied with the emergence of hepatic senescent cells while liver fibrosis regressed. Blocking EZH2 signaling by EPZ6438 reduced hepatic senescent cells and macrophages, decelerating liver fibrosis regression. Moreover, the promoter region of EZH2 was transcriptionally suppressed by Notch‐Hes1 (hairy and enhancer of split 1) signaling. Disruption of Notch in macrophages using Lyz2 (lysozyme 2) Cre‐RBP‐J (recombination signal binding protein Jκ) f/f transgenic mice, enhanced hepatic cellular senescence, and facilitated fibrosis regression by upregulating EZH2 and blocking EZH2 abrogated the above effects caused by Notch deficiency. Ultimately, adopting Notch inhibitor Ly3039478 or exosome‐mediated RBP‐J decoy oligodeoxynucleotides accelerated liver fibrosis regression by augmenting hepatic cellular senescence.

For improving the colour diversity and corrosion resistance of current zinc-copper-titanium alloys for the construction industry，the corrosion resistance of the surface film of Zn-Cu-Ti alloy after anodic oxidation treatment was analyzed and investigated by means of polarization curve，AC impedance，simulated seawater immersion experiment and salt spray test.Results showed that the quality of the anodic oxide film increased and then decreased with the increase of the current density and the concentration of NaOH in the electrolyte.When the current density was 10 A/dm2 and the NaOH concentration was 20 g/L，the as-obtained film had the most positive self-corrosion potential and the smallest self-corrosion current density.Additionally，the anodized film layer could significantly enhance its corrosion resistance in the simulated seawater corrosion test environment.

Objective To screen non-invasive indicators for predicting poor response to ursodeoxycholic acid in patients with primary biliary cholangitis（PBC）and establish a logistic regression model. Methods A total of 106 patients with PBC were selected in the modeling group. Clinical data of PBC patients before and after receiving 1 year ursodeoxycholic acid therapy were retrospectively analyzed. According to ParisⅡcriteria， all patients were divided into two groups： poor response group （n = 38） and complete response group （n = 68）. The general condition， laboratory indicators and ultrasound examination results of the patients were analyzed by non-conditional logistic regression model before and after treatment. Non-invasive indicators for predicting poor response to ursodeoxycholic acid were screened， and the regression model was established. To validate this model， 47 patients with PBC who visited Ditan Hospital for the first time were selected in the validation group， and were treated with ursodeoxycholic acid for 1 year. Results Univariate analysis showed that in the modeling group， there were significant differences in cholinesterase， alkaline phosphatase， direct bilirubin， γ-glutamyltranspeptidase， globulin， total triglyceride， total cholesterol， low-density lipoprotein cholesterol， erythrocyte sedimentation rate， CD4+T cell count and CD8+T cell count between the poor response and complete response groups before treatment （all P < 0.05）. Multivariate unconditional logistic analysis showed that cholinesterase， alkaline phosphatase and direct bilirubin before treatment were effective predictors of poor response. The regression model was： Y = 0.000339× cholinesterase （U/L） +2.227292× （whether the ALP is lower than 2 times of normalupper limit； 1= yes， 2= no） +0.024151×DBIL （μmol/L）. The sensitivity and specificity of the model for predicting poor response were 88.6% and 84.8%， respectively. In this validation cohort， the area under the receiver operating characteristic curve was 0.81（95% CI 0.69-0.94）. Conclusion Cholinesterase， alkaline phosphatase and direct bilirubin before treatment can predict poor response to ursodeoxycholic acid in PBC patients.

CD8+CD25+Treg can inhibit immune response and induce immune tolerance. This article reviews the changes and underlying mechanisms of CD8+CD25+Treg in pathogenesis of malignant tumors, autoimmune diseases and other common diseases such as asthma, allergic diseases, type 2 diabetes, and pre-eclampsia. The changes of CD8+CD25+Treg in different diseases are inconsistent, cell counting increased in malignant diseases but decreased in autoimmune diseases. Further understanding of CD8+CD25+Treg would supporte a basis for the prevention, treatment and improving prognosis of these diseases.