No abstract

Aim To investigate the potential application of concentrated growth factor (CGF) to promote pulp regeneration within immature teeth. Methodology Concentrated growth factor clots produced from peripheral blood samples were investigated histologically by haematoxylin–eosin (HE) staining and evaluated morphologically by scanning electron microscope (SEM). The cytokines were extracted from the CGF, and representative cytokines were quantified by enzyme‐linked immunosorbent assay (ELISA). The biological effects of the CGF on human stem cells from the apical papilla (SCAPs) were then investigated and quantified, including cell proliferation, cell migration, mineralized nodule formation, and the gene expression of alkaline phosphatase (ALP), dentine sialophosphoprotein (DSPP) and dentine matrix protein (DMP)‐1. The results were analysed statistically using one‐way analysis of variance (anova). Results Concentrated growth factor had a complex three‐dimensional structure with a high density of platelets and nucleated cells. Representative growth factors including PDGF‐BB, IGF‐1, TGF‐β1, bFGF and VEGF were detected. The growth rate and migratory cell numbers of the CGF groups were significantly greater than those in the control groups (P < 0.05). The mineralization areas in the CGF groups were significantly larger than those in the control groups (P < 0.05). The expression levels of ALP, DSPP and DMP‐1 were significantly up‐regulated after induction by CGF (P < 0.05). Conclusions Concentrated growth factor promoted the proliferation, migration and differentiation of SCAPs and could be a promising biomaterial applied in regenerative endodontics.

7A controller is usually used to maximize the energy absorption of wave energy converter. Despite the 8 development of various control strategies, the practical implementation of wave energy control is still 9 difficult since the control inputs are the future wave forces. In this work, the artificial intelligence 10 technique is adopted to tackle this problem. A multi-layer artificial neural network is developed and 11 trained by the deep machine learning algorithm to forecast the short-term wave forces. The model 12 predictive control strategy is used to implement real-time latching control action to a heaving point-13 absorber. Simulation results show that the average energy absorption is increased substantially with 14 the controller. Since the future wave forces are predicted, the controller is applicable to a full-scale 15 wave energy converter in practice. Further analysis indicates that the prediction error has a negative 16 effect on the control performance, leading to the reduction of energy absorption. 17 Keywords: wave energy converter; wave energy control; energy absorption; neural network; deep 18 machine learning; wave force prediction. 19 Henriques [6] presented a review on the oscillating-water-column WEC. Stansby et al. [7] examined 29 the dynamics of multi-float WEC concept M4. 30Although a set of WEC concepts have been developed, the energy harvesting efficiency is still not 31 satisfactory, especially in the off-resonance state. One of the solutions is the usage of a non-linear 32 power take-off (PTO) system. Zhang and Yang [8] showed that a PTO system with nonlinear spring 33 could harvest more energy in random waves. Xiao et al. [9] investigated the power capture of an 34Eq. (4) is a first-order, one-variable differential formula, which is easier to handle. Given the initial 112 condition x(0) = 0, it becomes a classical initial-value problem and the time series of floater 113

The cleavage property of hemagglutinin (HA) by different proteases was the prime determinant for influenza A virus pathogenicity. In order to understand the cleavage mechanism, molecular modeling tools were utilized to study the coupled model systems of the proteases, i.e., trypsin and furin and peptides of the cleavage sites specific to H5N1 and H1 HAs, which constitute models of HA precursor in complex with cleavage proteases. The peptide segments 'RERRRKKR downward arrow G' and 'SIQSR downward arrow G' from the high pathogenic H5N1 H5 and the low pathogenic H1N1 H1 cleavage sites were docking to the trypsin and furin active pockets, respectively. It was observed through the docking studies that trypsin was able to recognize and cleave both the high pathogenic and low pathogenic hemagglutinin, while furin could only cleave the high pathogenic hemagglutinin. An analysis of binding energies indicated that furin got most of its selectivity due to the interactions with P(1), P(4), and P(6), while having less interaction with P(2) and little interactions with P(3), P(5), P(7), and P(8). Some mutations of H5N1 H5 cleavage sequence fitted less well into furin and would reduce high pathogenicity of the virus. These findings hint that we should focus at the subsites P(1), P(4), and P(6) for developing drugs against H5N1 viruses.

This study deals with the hydro-aero-mooring coupled dynamic analysis of a new offshore floating renewable energy system, which integrates an offshore floating wind turbine (OFWT), a wave energy converter (WEC) and tidal turbines. The primary objective is to enhance the power production and reduce the platform motions through the combination of the three types of renewable energy systems. Simulation results show that the combined concept achieves a synergy between the floating wind turbine, the wave energy converter and the tidal turbines. Compared with a single floating wind turbine, the combined concept undertakes reduced surge and pitch motions. The overall power production increases by approximately 22%e45% depending on the environmental conditions. Moreover, the power production of the wind turbine is more stable due to the reduced platform motions and the combined concept is less sensitive to the transient effect induced by an emergency shutdown of the wind turbin