Bone, as a mineralized composite of inorganic (mostly carbonated hydroxyapatite) and organic (mainly type I collagen) phases, possesses a unique combination of remarkable strength and toughness. Its ...excellent mechanical properties are related to its hierarchical structures and precise organization of the inorganic and organic phases at the nanoscale: Nanometer‐sized hydroxyapatite crystals periodically deposit within the gap zones of collagen fibrils during bone biomineralization process. This hierarchical arrangement produces nanomechanical heterogeneities, which enable a mechanism for high energy dissipation and resistance to fracture. The excellent mechanical properties integrated with the hierarchical nanostructure of bone have inspired chemists and material scientists to develop biomimetic strategies for artificial bone grafts in tissue engineering (TE). This critical review provides a broad overview of the current mechanisms involved in bone biomineralization, and the relationship between bone hierarchical structures and the deformation mechanism. Our goal in this review is to inspire the application of these principles toward bone TE.
Bone is a hierarchical nanocomposite with excellent mechanical and biological functions that inspires the development of future high‐performance biomaterials. Here, we clarify the hierarchical structures and formation mechanism of bone. Recent progress in the synthesis of biomimetic materials and their potential applications in tissue engineering are also summarized. This review provides a comprehensive perspective for the future fabrication of artificial bone grafts.
The dynamics, duration, and nature of immunity produced during SARS-CoV-2 infection are still unclear. Here, we longitudinally measured virus-neutralising antibody, specific antibodies against the ...spike (S) protein, receptor-binding domain (RBD), and the nucleoprotein (N) of SARS-CoV-2, as well as T cell responses, in 25 SARS-CoV-2-infected patients up to 121 days post-symptom onset (PSO). All patients seroconvert for IgG against N, S, or RBD, as well as IgM against RBD, and produce neutralising antibodies (NAb) by 14 days PSO, with the peak levels attained by 15-30 days PSO. Anti-SARS-CoV-2 IgG and NAb remain detectable and relatively stable 3-4 months PSO, whereas IgM antibody rapidly decay. Approximately 65% of patients have detectable SARS-CoV-2-specific CD4
or CD8
T cell responses 3-4 months PSO. Our results thus provide critical evidence that IgG, NAb, and T cell responses persist in the majority of patients for at least 3-4 months after infection.
The sustainability challenge is increasingly driving the adoption of supercritical water gasification (SCWG) technology to ensure the elimination and recovery of pollution produced by sewage sludge ...treatment (SST). Risk evaluation by failure mode and effects analysis (FMEA) plays a crucial role in guaranteeing the reliability and safety of SCWG systems. However, some limitations in existing FMEA methods need to be ameliorated. Multiple risk factors are involved in prioritizing risk levels for failure modes in SCWG systems, it is essential a multiple criteria decision making (MCDM) process, in which overall assessments of failure modes should be provided according to their performances from several points during a system operation period. Due to differences in knowledge backgrounds and experiences, FMEA team members prefer to utilize multi-granular linguistic term sets to express their assessments of system risk. A hybrid risk evaluation model by FMEA is exploited with multi-granular linguistic distribution assessments to suit practical case. Best-worst and maximizing derivation methods are adopted to determine subjective and objective combined weights for distinguishing the importance of risk factors. Complex proportional assessment method is used to prioritize failure modes for explicitly and effectively reflecting the risk level of each failure mode. The proposed model is applied in a practical case of an SCWG system used in SST. Results derived from comparative and sensitivity analyses fully demonstrate the reliability and validity of the model.
In this paper, firstly, the average prediction rating of interest points is performed by a recommendation model incorporating multiple factors through probabilistic matrix decomposition to improve ...the accuracy of the beauty teaching features obtained by matrix decomposition. Then, we combine the collaborative filtering recommendation algorithm and propose a recommendation model called TGSS-MF, and optimize the TGSS-MF recommendation model through the model of neural network for the sparse data problem faced by the interest point recommendation and the hidden feature vector representation problem of users and interest points, and finally use the TGSS-MF recommendation model to analyze the user needs of teachers, students and system administrators who are involved in teaching and learning. Finally, the TGSS-MF recommendation model is used to analyze the needs of users such as teachers, students, and system administrators involved in teaching and learning. A mobile teaching platform is designed to meet the characteristics of American voice teaching in colleges and universities. The performance analysis of the TGSS-MF recommendation model shows that when k=10, the accuracy and recall of the TGSS-MF model in the two data sets are 0.095 and 0.113, respectively, which are better than the other three algorithms in both accuracy and recall. This study can present more rich resources to students through modern Internet technology, which can help students learn effectiveness.
We must seize the chance for growth in the big data era for innovation and optimization to efficiently optimize music education instruction in colleges and universities. This paper applies the SVM ...method to studying vocal recognition in popular music to build a music learning aid system. The system gives the exact location of the intro, bridge, and outro through the recognition of vocals in pop music, which helps learners to practice in a targeted way. MFCC features are used, and low-pass filtering is applied to the classification results later, resulting in a recognition rate of 85.74% on a frame-by-frame basis. From the test results, SVM has a better generalization ability than other classifiers, including ANN, GMM, and HMM, with a recognition rate of at least 8.84% higher. In the practicality test, the experimental class applied the music-assisted system for learning, and the comparison class used the traditional teaching method. 46 more people in the experimental class rated good music ability than the control class, 68 more rated good innovation status than the control class, and 71 more rated good independent learning ability than the control class. Therefore, big data technology must be used to innovate music education in colleges and universities to increase teaching efficacy successfully.
Mudstone not only swells and deforms but also be softened during water absorption because it contains many hydrophilic clay minerals. To study the influence of water on the swelling characteristics ...and mechanical behavior of mudstone, the water softening effect is first considered in the moisture diffusion-fracture coupling model based on the finite-discrete element method (FDEM). Then, the micro parameters of mudstone are calibrated by uniaxial, triaxial compression, and swelling tests. Subsequently, the coupling model is employed to perform uniaxial compression and triaxial compression numerical tests on the water-soaked mudstone. Results indicate that the mechanical strength decreases with the increase of water content, and the modeling results are consistent with the laboratory results. Besides, the failure pattern under uniaxial compression changes from shear failure to tensile failure as water content increases from 0% to 6%, while that of mudstone under triaxial compression tends to conjugate shear failure with the increase of water content and confining pressure. For all mudstones with different water content, the proportion of shear cracks increases with the increase of confining pressure. Finally, the effects of homogeneity index and swelling coefficient on the deformation, mechanical properties, and failure patterns of mudstone are discussed. The results in this paper provide a reference for understanding the mechanism of swelling characteristics and strength degradation of soft rock.
•A FDEM coupling model is first employed to investigate the mechanical behavior of mudstone after encountering water.•Confining pressure reduces the water softening effect.•The failure patterns of mudstone with different water content are described.
Metal–organic frameworks (MOFs), built from organic linkers and metal ions/clusters, have emerged as highly promising materials for wide applications. Combining highly porous crystalline MOFs with ...the surface‐enhanced Raman scattering (SERS) technique can achieve unprecedented advantages of high selectivity, high sensitivity, and expedience in analysis and detection. In this critical review, the aim is to present a comprehensive review of recent advances in understanding of the roles of MOFs in MOF‐SERS systems, particularly their structure‐to‐property correlation. Key examples are selected from representative literature to illustrate critical concepts and the MOF‐based property‐dependent applications are particularly emphasized. Finally, the barriers, future trends, and prospects for further advances in MOF‐SERS platforms are also discussed.
Combining highly porous crystalline metal–organic frameworks (MOFs) with the surface‐enhanced Raman scattering (SERS) technique can achieve unprecedented advantages of high selectivity, high sensitivity, and expedience in analysis and detection. Herein, recent advances in research on the roles of MOFs in MOF‐SERS systems, particularly their structure‐to‐property correlation, are systematically highlighted.
Surface enhanced Raman scattering (SERS) is a trace detection technique that extends even to single molecule detection. Its potential application to the noninvasive recognition of lung malignancies ...by detecting volatile organic compounds (VOCs) that serve as biomarkers would be a breakthrough in early cancer diagnostics. This application, however, is currently limited by two main factors: (1) most VOC biomarkers exhibit only weak Raman scattering; and (2) the high mobility of gaseous molecules results in a low adsorptivity on solid substrates. To enhance the adsorption of gaseous molecules, a ZIF‐8 layer is coated onto a self‐assembly of gold superparticles (GSPs) in order to slow the flow rate of gaseous biomarkers and depress the exponential decay of the electromagnetic field around the GSP surfaces. Gaseous aldehydes that are released as a result of tumor‐specific tissue composition and metabolism, thereby acting as indicators of lung cancer, are guided onto SERS‐active GSPs substrates through a ZIF‐8 channel. Through a Schiff base reaction with 4‐aminothiophenol pregrafted onto gold GSPs, gaseous aldehydes are captured with a 10 ppb limit of detection, demonstrating tremendous prospects for in vitro diagnoses of early stage lung cancer.
A high‐sensitivity surface enhanced Raman scattering (SERS) substrate is used for volatile organic compounds (VOCs) detection in exhaled breath, wherein ordered gold superparticles act as SERS hotspots and a metal‐organic‐framework layer is employed to slow the flow rate and strengthen the adsorption of gaseous analytes. Gaseous aldehyde VOCs are captured with a parts per billion limit of detection in this analyte‐detection system.
Probabilistic interval‐valued hesitant fuzzy sets (PIV‐HFSs) are suitable for aggregating information from different groups because the probabilistic information of all the groups can be included by ...using interval values. Moreover, decision makers (DMs) prefer to use interval values to provide evaluation information. Furthermore, the traditional multi‐criteria group decision‐making (MCGDM) approach has some limitations, such as obtaining the DMs' weights with inappropriate methods and neglecting the interactions amongst the criteria and the psychological characteristics of DMs. Motivated by these research background, the main contents of this study are as follows. First, PIV‐HFSs are proposed, and the convex combination operation is extended into PIV‐HFSs. Second, a hybrid MCGDM approach with PIV‐HFSs is suggested that is based on the maximizing deviation method, fuzzy analytic network process (FANP) and TODIM (an acronym in Portuguese for interactive and multi‐criteria decision‐making model). Third, an evaluation case of health management centres based on the service‐specific failure mode and effect analysis (FMEA) is considered. The results show that the most crucial secondary factor is frequency (0.35775) and that the most serious failure mode is the inaccurate check‐in. The results demonstrate that the proposed model can evaluate service quality effectively and that it performs better than other methods.
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•A FDEM coupling model is fist applied to deformation and failure of soft rock induced by humidity.•The damage zone and failure pattern of soft rock roadway are significantly affected ...by humidity.•Effects of element size and humidity diffusion coefficient on humidity damage zone are studied.
In underground space engineering, the humidity in the environment has a great influence on the structural performance of soft rock roadway. It not only changes the stress state of rock mass, but also weakens the physical and mechanical properties of surrounding rock, resulting in many accidents such as swelling deformation and even collapse of the roadway. In this paper, the deformation and failure process of soft rock roadway in high humidity environment are simulated by using the humidity diffusion-deformation-fracture coupling model based on the finite-discrete element method (FDEM). Firstly, the coupling model is verified through two simple examples with analytical solutions. Then, the humidity diffusion and floor heave of soft rock roadway after excavation are studied by using the coupling model. The results show that only the humidity of the surrounding rock surface changes greatly at the beginning of excavation and the roadway floor heave caused by humidity is small but with a large change rate. However, with further diffusion of humidity, the displacement of the floor increases slowly at a constant rate. Besides, several main factors affecting floor heave are studied, including humidity swelling coefficient, initial elastic modulus, and initial humidity of floor. Finally, the coupling model is used to simulate the roadway failure process induced by humidity diffusion. The numerical results provide a better understanding of the deformation and failure behavior of soft rock roadway in high humidity environment.
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