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Tantalum disilicide (TaSi2) has been widely studied for its excellent physical properties such as high hardness, high temperature oxidation resistance and low resistivity. Here, we aim to investigate the effects of different sintering temperatures and pressures on the microstructure and physical properties of TaSi2ceramics. We successfully prepared dense TaSi2ceramics using high-pressure and high-temperature (HPHT) sintering techniques. Characterization results show that TaSi2ceramic properties are strongly influenced by the sintering temperature. The density, Vickers hardness and fracture toughness of TaSi2sintered samples reaches a maximum value of 9.182 g/cm3, 11.34 GPa and 11.97 MPa m1/2, respectively. The fracture toughness of TaSi2sintered samples was significantly improved and also exhibited excellent high-temperature oxidation resistance. Meanwhile, we also investigated the microstructure and grain size variation of TaSi2sintered samples with sintering conditions using scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The results show that HPHT sintering can effectively refine the grains of TaSi2ceramics. It provides effective data and ideas for more efficient utilization of TaSi2and preparation of other high-performance ceramics.

Due to the complex and changeable environment under water, the performance of traditional DOA estimation algorithms based on mathematical model, such as MUSIC, ESPRIT, etc., degrades greatly or even some mistakes can be made because of the mismatch between algorithm model and actual environment model. In addition, the neural network has the ability of generalization and mapping, it can consider the noise, transmission channel inconsistency and other factors of the objective environment. Therefore, this paper utilizes Back Propagation (BP) neural network as the basic framework of underwater DOA estimation. Furthermore, in order to improve the performance of DOA estimation of BP neural network, the following three improvements are proposed. (1) Aiming at the problem that the weight and threshold of traditional BP neural network converge slowly and easily fall into the local optimal value in the iterative process, PSO-BP-NN based on optimized particle swarm optimization (PSO) algorithm is proposed. (2) The Higher-order cumulant of the received signal is utilized to establish the training model. (3) A BP neural network training method for arbitrary number of sources is proposed. Finally, the effectiveness of the proposed algorithm is proved by comparing with the state-of-the-art algorithms and MUSIC algorithm.

Purpose: This study aims to evaluate a method of building a biomedical knowledge graph (KG). Design/methodology/approach: This research first constructs a COVID-19 KG on the COVID-19 Open Research Data Set, covering information over six categories (i.e. disease, drug, gene, species, therapy and symptom). The construction used open-source tools to extract entities, relations and triples. Then, the COVID-19 KG is evaluated on three data-quality dimensions: correctness, relatedness and comprehensiveness, using a semiautomatic approach. Finally, this study assesses the application of the KG by building a question answering (Q&A) system. Five queries regarding COVID-19 genomes, symptoms, transmissions and therapeutics were submitted to the system and the results were analyzed. Findings: With current extraction tools, the quality of the KG is moderate and difficult to improve, unless more efforts are made to improve the tools for entity extraction, relation extraction and others. This study finds that comprehensiveness and relatedness positively correlate with the data size. Furthermore, the results indicate the performances of the Q&A systems built on the larger-scale KGs are better than the smaller ones for most queries, proving the importance of relatedness and comprehensiveness to ensure the usefulness of the KG. Originality/value: The KG construction process, data-quality-based and application-based evaluations discussed in this paper provide valuable references for KG researchers and practitioners to build high-quality domain-specific knowledge discovery systems.

Zirconium disilicide (ZrSi2) has been investigated experimentally and theoretically for its structural and physical properties at high pressures. In situ compression experiments demonstrate that at low pressure, ZrSi2adopts the C49 structure (space group Cmcm), which persists up to 54.5 GPa at room temperature, and the unit cell of ZrSi2along b-axis is at least twice as compressible as along a- and c-axis. A bulk modulus of 170.0 ± 0.7 GPa (K′0= 4) is derived from the compression experiment employing methanol–ethanol mixture as the pressure-transmitting medium. Diffraction line-width analysis suggests a yield strength of about 3.0 GPa for ZrSi2under high pressures at room temperature. The first-principles calculations mostly agree with the experimental results, such as mechanical and dynamic stability and elastic anisotropy (Kc> Ka≫ Kb). However, predicted axial modulus Kbby modeling is significantly smaller than the experimentally determined value, resulting in a sizable discrepancy between experimental (170.0 GPa) and theoretical (121.0 GPa) bulk moduli.

Hafnium carbide (HfC) is a potential candidate of ultrahigh-temperature ceramics (UHTCs) and has attracted significantly widespread interest in recent years. Here, we have synthesized high-purity HfC samples with NaCl-type structure by using a high-pressure solid–solid reaction. The structural stability, equation of state, plastic deformation, yield strength, and bonding properties under high pressure are investigated by a series of in situ high-pressure synchrotron-radiation angle-dispersive X-ray diffraction experiments combined with first-principles calculations. The yield strength of HfC (∼18 GPa) is obtained from analyzing the plastic deformation behavior under high pressure. In addition, we have successfully prepared bulk HfC ceramics with high density using a high-pressure and high-temperature method. The synthesized sample possesses a desirable Vickers hardness of 24.2 GPa and an excellent fracture toughness of 5.0 MPa·m1/2. The present results offer insights into the achievable application of HfC ceramics under extreme conditions and provide a powerful guide for the further design and synthesis of other high-performance UHTCs.

Among the transition metal carbides, tantalum carbide (TaC) has gained significant interest due to its attractive mechanical and electronic properties. Here, we have performed high pressure and high temperature (HPHT) measurements on the physical properties of TaC under 5.5 GPa and rhythmically increased temperatures from 1000 to 1500 °C. The microscopic deviatoric strain, Vickers hardness, fracture toughness, grain size, and microstructures are characterized by X-ray diffraction (XRD), scanning electronic microscopy (SEM), transmission electron microscopy (TEM), and microhardness tests. The results reveal that the HPHT sintering causes the densification, which increases the mechanical properties of TaC. At 5.5 GPa and 1300 °C, the Vickers hardness, fracture toughness, relative density, and Young’s modulus of TaC are 21.0 GPa, 7.4 MPa m1/2, 457 GPa, and 97.7%, respectively, which are in good agreement with available experimental and theoretical values. It is found that the mechanical properties of TaC are highly impressible to the microstructures and microscopic deviatoric stress. Our cadent HPHT sintering technique will provide powerful guidance for further synthesis and design of other novel ultrahigh temperature ceramics (UHTCs).

Purpose: In a people-oriented society, it is necessary to understand the electronic word of mouth (eWOM) of information service of the government. Government affair microblogs (GAM), which play an important role in orienting online opinions, listening to public voices, establishing government image, is an ideal channel to achieve this goal. In essence, the application of GAM is to improve the communication efficiency between the government and the public. The purpose of this study is to the influence factors of GAM eWOM which will not only benefits the government in better understanding the information dissemination rules of microblogs but also provides directions for the government to improve the information service over microblogs. Design/methodology/approach: In this paper, the authors investigate and verify the regulating function, herd effect applied on GAM. The authors conduct an innovative empirical study based on perceived value theory, aiming to explore the factors that influence the eWOM of the Chinese Government. Findings: Experiments on 502 GAM users show that social identification positively affects perceived value while effort cost negatively affects perceived value, and perceived value positively influences the microblogs’ eWOM. The authors also find that the herd effect positively regulates the relationship between perceived value and GAM’s eWOM. Theoretical and practical implications of these findings are discussed. Originality/value: In this research, the regulating effect of herd effect on the relationship between perceived value and GAM’s eWOM has been explored. This study also provides inspirations for future government information service research and administrative measurement.

Trillions of microbes reside in the human body and participate in multiple physiological and pathophysiological processes that affect host health throughout the life cycle. The microbiome is hallmarked by distinctive compositional and functional features across different life periods. Accumulating evidence has shown that microbes residing in the human body may play fundamental roles in infant development and the maturation of the immune system. Gut microbes are thought to be essential for the facilitation of infantile and childhood development and immunityby assisting in breaking down food substances to liberate nutrients, protecting against pathogens, stimulating or modulating the immune system, and exerting control over the hypothalamic–pituitary–adrenal axis. This review aims to summarize the current understanding of the colonization and development of the gut microbiota in early life, highlighting the recent findings regarding the role of intestinal microbes in pediatric diseases. Furthermore, we also discuss the microbiota-mediated therapeutics that can reconfigure bacterial communities to treat dysbiosis.

The intriguing electronic bonding properties of transition-metal-doped boron clusters have made them the subject of increased attention. However, the structures and stabilities of boron clusters doped with Mo remain elusive, and reports on Mo-doped boron clusters in the literature are still rare. Here, medium-sized MoBn0/–(n= 10–20) clusters were investigated by utilizing the unbiased CALYPSO structure searching method with subsequent DFT optimization at the PBE0/Mo/LANL2DZ/B/6-311+G(d) level. Three types of geometries were found for the ground-state structures of the MoBn0/–(n= 10–20) clusters: half-sandwich, drumlike, and tubular. Furthermore, the stability of the ground-state structures was quantified and analyzed based on three effective criteria. The simulated photoelectron spectra served as electronic “fingerprints” of the clusters for comparison with experimental spectra. Subsequent molecular orbital and adaptive natural density partitioning analyses revealed that the enhanced stability of MoB18resulted from strong interactions between the 4d orbitals of the Mo atoms and the 2p orbitals of the B atoms, as well as the B–B σ bonds in the B18shell.

Purpose:The high mortality rate of malignant tumors is often attributable to the loss of surgical opportunities due to late diagnosis when invasion and metastasis have significantly affected the patient. A hypoxic microenvironment can promote the progression of malignant tumors. This study explored the invasion resistance and migration ability of luteolin-Zn complexes. Methods:We created a low-oxygen environment using a 3-atmosphere incubator. The appropriate drug concentration was determined using the CCK8 experiment. We determined its role in cell invasion and migration through scratch and transwell experiments. Western blotting, polymerase chain reaction, and cellular immunity experiments were used to study the mechanism and its impact on the secretion of invasion and migration factors. Results:Our results indicated that the luteolin-Zn complex significantly reduced MMP2, MMP9, N-Ca,and HIF-1ɑexpression. It also upregulated TIMP1and E-Caexpression. Moreover, its capabilities may be achieved by regulating the AMPK/mTORand PI3K/Akt/mTORsignaling pathways. Conclusions:The luteolin-Zn complex was highly resistant to the invasion and migration of M2-like tumor-related macrophages. This may exert a unique influence on mTOR by integrating various signals. This study suggests that the luteolin-Zn complex has a strong anticancer effect under hypoxic conditions.

Fluorine-containing fluoroquinolones are cumulative toxins and pose a grave threat to health of animals and human beings, and an effective and feasible strategy to the defluorination by breaking C-F bond to decrease toxicity is in an urgent requirement. Herein, Ti(III)-laden TiO2nanotube arrays (RTNA) were deliberately fabricated for electrochemical degradation and defluorination of levofloxacin (LVF). Characterizations verified that Ti(III) and oxygen vacancies were generated on RTNA via electrochemical reduction of TiO2nanotube arrays (TNA). The degradation kinetics of LVF on RTNA (0.85 h−1) was increased by about 15 times as compared with that on TNA (0.06 h−1); the corresponding degradation and defluorination efficiencies by RTNA were also dramatically increased. Moreover, the effect of electrolyte on the defluorination efficiency suggests the significant role of sulfate; that is, abundant sulfate radical (SO4-•) was generated in the media of sodium sulfate during the electrochemical oxidation process, and it served as the dominant radical to break C-F bond for the defluorination of LVF, whereas it is not the case for hydroxyl radical (•OH) in sodium carbonate. The pathways and mechanisms of degradation and defluorination in electrolyte of sodium sulfate or carbonate were proposed and further confirmed the difference in the electrolyte-dependent degradation mechanisms.

The effect of complexation temperature (30, 60, and 90°C) on the gelatinization properties, glass transition, enzymatic hydrolysis, and crystalline structure of high-amylose corn starch–oleic acid (HACS-OA) complexes created by a dimethyl sulfoxide (DMSO)-based complexation method and of normal corn starch–oleic acid (NCS-OA) complexes created by an alkaline-based complexation method were investigated by using differential scanning calorimetry, thermogravimetric analysis, and X-ray diffractometry. The results indicated that the highest complex indices were found in the complexes created at 30 and 60°C with the DMSO-based complexation method and alkaline-based complexation method, respectively. The X-ray diffraction patterns of both HACS-OA complexes and NCS-OA complexes created at different complexation temperatures were the V-type pattern. For the complexes created by the two methods, both the melting temperature and the glass transition temperature increased obviously with increasing complexation temperature. Complexation temperature also influenced the enzymatic hydrolysis rate of starch-OA complexes.

A new class of aryl trifluorovinyl ether monomers were designed and synthesized, and novel fluorinated polymers containing perfluorocyclobutane and 1H-1,2,3-triazole units were prepared from these monomers. These polymers were characterized by nuclear magnetic resonance spectroscopy, thermo-gravimetric analysis and differential scanning calorimetry. The temperatures of 5% weight loss of the polymers under nitrogen were up to ~290?°C, and the glass transition temperatures of the polymers were in the range of 79–110?°C. These new polymers showed good solubility in common organic solvents such as dimethyl sulfoxide and N,N-dimethylacetamide. In addition, the proton conductivity of the polymers was measured under anhydrous conditions using impedance spectroscopy, and a maximum conductivity of 2.85?µS?cm-1was obtained at 200?°C.

The traditional limited feedback scheme can use imperfect channel state information to achieve interference alignment (IA) in a fully connected situation. But these solutions could no longer be used directly in heterogeneous networks where partial connectivity is considered. To solve this problem, this article proposes an IA scheme based on limited feedback with differentiation for the two‐tiered heterogeneous network. First, users who are affected by different types and numbers of interference and corresponding base stations are divided into different units according to the partial connectivity of heterogeneous networks. Then, we design interference alignment algorithm for each unit separately. Next, considering the imperfect channel state information, we derive the leakage of interference caused by the limited feedback, and give expressions for the upper bound of sum rate loss in various units. Finally, dynamic feedback bit allocation is carried out to each unit with the goal of minimizing the throughput loss in the limited feedback system. The simulation results show that the proposed IA scheme can eliminate interference well and efficiency of limited feedback can be improved through dynamic feedback bit allocation, so that system can obtain higher sum rate than other schemes. Considering the partial connectivity of heterogeneous networks, we propose an interference alignment scheme based on limited feedback with differentiation. The proposed scheme can eliminate interference in these networks effectively and reduce performance loss caused by limited feedback.

Summary:Monodisperse carboxy polystyrene (PS) spheres were synthesized and utilized as an interface to increase the detection sensitivity of some biomolecules. The binding behavior of dacarbazine (DTIC), an anticancer drug, with DNA bases in the absence and presence of the PS spheres was investigated. The results indicated a remarkable effect of PS on the binding behavior of DTIC to DNA bases and significantly enhanced detection sensitivity for the relative biomolecular recognition.

• Combine three different semantic distance algorithms (WordNet, Google Distance, and ESA) with three re-ranking algorithms (MMR, xQuAD, and Score Difference algorithms) for image result diversification. • Data: 269,648 images selected from NUS-WIDE datasets with manually annotated subtopics. • Affirm the effectiveness of this combination of nine algorithms for improving result diversification in image retrieval under different indicators. • The WordNet based semantic distance combined with the Score Difference (WordNet-DivScore) algorithm outperformed the other algorithms. User requirements for result diversification in image retrieval have been increasing with the explosion of image resources. Result diversification requires that image retrieval systems are made capable of handling semantic gaps between image visual features and semantic concepts, and providing both relevant and diversified image results. Context information, such as captions, descriptions, and tags, provides opportunities for image retrieval systems to improve their result diversification. This study explores a mechanism for improving result diversification using the semantic distance of image social tags. We design and compare nine strategies that combine three different semantic distance algorithms (WordNet, Google Distance, and Explicit Semantic Analysis) with three re-ranking algorithms (MMR, xQuAD, and Score Difference) for result diversification. In order to better prove the effectiveness of our strategy of applying semantic information, we also make use of visual features of images for result diversification experiment and make comparison. Our data for experimentation were extracted from 269,648 images selected from the NUS-WIDE datasets with manually annotated subtopics. Experimental results affirm the effectiveness of applying semantic information for improving result diversification in image retrieval. In particular, WordNet-based semantic distance combined with the Score Difference (WordNet-DivScore) outperformed other strategies in diversifying image retrieval results. [ABSTRACT FROM AUTHOR]