Research on plasma modified fly ash denitration.

The effects of reactor parameters and process parameters on the denitration rate of modified fly ash in different gas atmospheres were studied by using a dielectric barrier plasma reactor and using orthogonal experiments. The characteristics of modified fly ash were analyzed using scanning electron microscope, specific surface area analyzer, X-ray diffraction, Boehm titration and Fourier transform infrared spectroscopy. The experimental data were processed by variance analysis and linear regression to induce the denitration mechanism. R2 of the linear regression analysis model is 0.789, which means that the adsorption pore size, acid groups and basic group can explain 78.9% of the change in denitration rate. The basic group will have a significant positive impact on the denitration rate, and the adsorption pore size and acidic group will have a significant negative impact on the denitration rate. Through variance analysis of the experimental data, it was found that the input power and discharge gap have a significant effect on the denitration rate, but the ionization time and discharge length have no significant effect. The input power affects the denitration rate by impacting the basic group, and the discharge gap affects the denitration rate by influencing the adsorption pore size. There are three denitration mechanisms on the surface of fly ash: physical adsorption, chemical adsorption and absorption process. Among them, chemical adsorption is the main mechanism of action, accounting for approximately 60.86%.

Spatiotemporal informer: A new approach based on spatiotemporal embedding and attention for air quality forecasting.

Accurate prediction of air pollution is essential for public health protection. Air quality, however, is difficult to predict due to the complex dynamics, and its accurate forecast still remains a challenge. This study suggests a spatiotemporal Informer model, which uses a new spatiotemporal embedding and spatiotemporal attention, to improve AQI forecast accuracy. In the first phase of the proposed forecast mechanism, the input data is transformed by the spatiotemporal embedding. Next, the spatiotemporal attention is applied to extract spatiotemporal features from the embedded data. The final forecast is obtained based on the attention tensors. In the proposed forecast model, the input is a 3-dimensional data that consists of air quality data (AQI, PM2.5, O3, SO2, NO2, CO) and geographic information, and the output is a multi-positional, multi-temporal data that shows the AQI forecast result of all the monitoring stations in the study area. The proposed forecast model was evaluated by air quality data of 34 monitoring stations in Beijing, China. Experiments showed that the proposed forecast model could provide highly accurate AQI forecast: the average of MAPE values for from 1 h to 20 h ahead forecast was 11.61%, and it was much smaller than other models. Moreover, the proposed model provided a highly accurate and stable forecast even at the extreme points. These results demonstrated that the proposed spatiotemporal embedding and attention techniques could sufficiently capture the spatiotemporal correlation characteristics of air quality data, and that the proposed spatiotemporal Informer could be successfully applied for air quality forecasting.

MASR: A novel monitoring method coupled with interpretation platform for near-term management in thermal stratified reservoirs.

Good water quality is critical to public health and aquatic ecological security of global reservoirs. In stratified reservoirs, increasing near-term management demands foster extremely high monitoring and forecasting needs. In this study, a management assistant for stratified reservoirs (MASR) was developed, including a wave-driven monitoring platform and interpretation platform for multiple reservoir water quality variables. The wave-driven platform can adapt to the characteristics of water level changes and transmit the monitoring data through a mobile network to the reservoir manager, which are processed by the interpretation platform in real time for near-term management. After several months of application, MASR monitored 1237 groups of valid profile water quality data with an acceptable error, which showed a strong capacity for capturing the water quality dynamics in a stratified reservoir. The effective identification of thermal stratification structures and anoxic zones can help managers to design withdrawal schemes for reservoirs. Moreover, the prediction of algae state based on the back propagation (BP) neural network provided the basis for making operation plans to proactively control algae blooms. Our study provides an economical and convenient solution for stratified reservoirs to address near-term management issues.

Mesenchymal stem cells induced regulatory dendritic cells from hemopoietic progenitor cells through Notch pathway and TGF-ß synergistically.

Mesenchymal stem cells (MSCs) are one of the attractive candidates in regenerative medicine of many clinical applications because of their low immunogenicity and immunomodulatory property. Our previous studies provided that mouse bone marrow-derived Sca-1+MSCs could drive the differentiation of regulatory DC (regDCs) (Scal-1+ BM-MSC-driven DC [sBM-DCs]) from hemopoietic progenitor cells (HPCs) and the Notch pathway played a critical role in maintaining the immunomodulatory property. However, the detailed mechanisms of their immunoregulatory capacity are not fully defined. In the present study, we show that BM-MSCs expressed high levels of Jagged 1 while sBM-DCs expressed high levels of Notch1. Jagged1 expressed on the surface of BM-MSCs initiated Notch signaling to maintain the immunomodulatory property of the sBM-DCs. The level of TGF-ß is high in MSCs, either alone or coculture with HPCs medium. TGF-ß plays a vital role in the proliferation and differentiation of sBM-DCs and inhibition of TGF-ß reduce the number and increase the percentage of CD34, CD117, CD135 of generation cells. Thus, MSCs induced the regDCs from HPCs via the Notch signaling pathway and TGF-ß synergistically. This study further broadens our understanding of the immunomodulatory mechanism and the potential therapeutic efficacy of MSCs.

Effects of non-sinusoidal pitching motion on the propulsion performance of an oscillating foil.

Numerical simulations have been used in this paper to study the propulsion device of a wave glider based on an oscillating hydrofoil, in which the profile of the pitching and heaving motion have been prescribed for the sake of simplicity. A grid model for a two-dimensional NACA0012 hydrofoil was built by using the dynamic and moving mesh technology of the Computational Fluid Dynamics (CFD) software FLUENT and the corresponding mathematical model has also been established. First, for the sinusoidal pitching, the effects of the pitching amplitude and the reduced frequency were investigated. As the reduced frequency increased, both the mean output power coefficient and the optimal pitching amplitude increased. Then non-sinusoidal pitching was studied, with a gradual change from a sinusoid to a square wave as the value of ß was increased from 1. It was found that when the pitching amplitude was small, the trapezoidal pitching profile could indeed improve the mean output power coefficient of the flapping foil. However, when the pitching amplitude was larger than the optimal value, the non-sinusoidal pitching motion negatively contributed to the propulsion performance. Finally, the overall results suggested that a trapezoidal-like pitching profile was effective for the oscillating foil of a wave glider when the pitching amplitude was less than the optimal value.

Study of Flexural Response in Strain Hardening Cementitious Composites Based on Proposed Parametric Model.

Strain hardening cementitious composites (SHCCs) are widely used in projects due to their excellent deformation resistance and large energy absorption capacity. However, determining tensile strain capacity is still a challenge for engineers. The current popular approach is to use inverse methods to predict the tensile behavior of SHCCs, such as the UM method (Qian and Li) and the JCI (Japan Concrete Institute) method. The key to these two approaches is to acquire the exact relationship between the bending and the uniaxial response. In this paper, a reasonable linear constitutive model of the SHCCs is modified. Initially, the moment-curvature diagrams are discussed by material parameters. The results reveal that the moment-curvature response is quite sensitive to the variations in the parameter of transition strain α, post-cracking tensile stiffness η, and strain softening stiffness µ, however, for the compressive parameters, the moment-curvature responses influence on flexural behavior is insignificant. Moreover, the load-deflection curve in the mid-span of SHCC, based on the consideration of shear effect, is simulated under a four-point bending test (FPBT). The results show a remarkable consistency with the experimental data when compared to the previous simulations. It is expected that this modified method can enhance an accurate program in order to obtain the tensile capacity.