Evaluating two concepts for the modelling of intermediates accumulation during biological denitrification in wastewater treatment

The accumulation of the denitrification intermediates in wastewater treatment systems is highly undesirable, since both nitrite and nitric oxide (NO) are known to be toxic to bacteria, and nitrous oxide (N2O) is a potent greenhouse gas and an ozone depleting substance. To date, two distinct concepts for the modelling of denitrification have been proposed, which are represented by the Activated Sludge Model for Nitrogen (ASMN) and the Activated Sludge Model with Indirect Coupling of Electrons (ASM-ICE), respectively. The two models are fundamentally different in describing the electron allocation among different steps of denitrification. In this study, the two models were examined and compared in their ability to predict the accumulation of denitrification intermediates reported in four different experimental datasets in literature. The N-oxide accumulation predicted by the ASM-ICE model was in good agreement with values measured in all four cases, while the ASMN model was only able to reproduce one of the four cases. The better performance of the ASM-ICE model is due to that it adopts an “indirect coupling” modelling concept through electron carriers to link the carbon oxidation and the nitrogen reduction processes, which describes the electron competition well. The ASMN model, on the other hand, is inherently limited by its structural deficiency in assuming that carbon oxidation is always able to meet the electron demand by all denitrification steps, therefore discounting electron competition among these steps. ASM-ICE therefore offers a better tool for predicting and understanding intermediates accumulation in biological denitrification

Voltage Balancing Control of Diode-Clamped Multilevel Rectifier/Inverter Systems

This paper presents a new voltage balancing control for the diode-clamped multilevel rectifier/inverter system. A complete analysis of the voltage balance theory for a 5-level back-to-back system is given. The analysis is based on fundamental frequency switching control and then extended to pulse-width modulation. The method involves obtaining optimal switching angles; a process which is described in detail in this paper. The proposed control strategy regulates the DC bus voltage, balances the capacitors, and decreases the harmonic components of the voltage and current. Simulation and experimental results demonstrate the validity of the optimizing method and control theory

From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited

Graph-based semi-supervised learning (GSSL) has long been a hot research topic. Traditional methods are generally shallow learners, based on the cluster assumption. Recently, graph convolutional networks (GCNs) have become the predominant techniques for their promising performance. In this paper, we theoretically discuss the relationship between these two types of methods in a unified optimization framework. One of the most intriguing findings is that, unlike traditional ones, typical GCNs may not jointly consider the graph structure and label information at each layer. Motivated by this, we further propose three simple but powerful graph convolution methods. The first is a supervised method OGC which guides the graph convolution process with labels. The others are two unsupervised methods: GGC and its multi-scale version GGCM, both aiming to preserve the graph structure information during the convolution process. Finally, we conduct extensive experiments to show the effectiveness of our methods

Photocatalytic oxidation of methane over silver decorated zinc oxide nanocatalysts

The search for active catalysts that efficiently oxidize methane under ambient conditions remains a challenging task for both C1 utilization and atmospheric cleansing. Here, we show that when the particle size of zinc oxide is reduced down to the nanoscale, it exhibits high activity for methane oxidation under simulated sunlight illumination, and nano silver decoration further enhances the photo-activity via the surface plasmon resonance. The high quantum yield of 8% at wavelengths \u3c 400 nm and over 0.1% at wavelengths ¿ 470 nm achieved on the silver decorated zinc oxide nanostructures shows great promise for atmospheric methane oxidation. Moreover, the nano-particulate composites can efficiently photo-oxidize other small molecular hydrocarbons such as ethane, propane and ethylene, and in particular, can dehydrogenize methane to generate ethane, ethylene and so on. On the basis of the experimental results, a two-step photocatalytic reaction process is suggested to account for the methane photo-oxidation

3-D Hybrid VLC-RF Indoor IoT Systems with Light Energy Harvesting

In this paper, a 3-dimensional (3-D) hybrid visible light communication (VLC)-radio frequency (RF) indoor internet of things system with spatially random terminals with one photodiode (e.g., indoor sensors: temperature sensors, humidity sensors, and indoor air quality sensors) is considered. Specifically, homogeneous Poisson point process is adopted to model to the distribution of the terminals, which means that the number of the terminals obeys Poisson distribution, and the positions of the terminals are uniformly distributed. VLC and RF communications are employed over downlink and uplink, respectively. Meanwhile, the terminals are designed to harvest the energy from the light emitted by the light-emitting diode over the downlink, which is used for the transmissions over the uplink. The light energy harvesting model is considered after introducing the line of sight propagation model for VLC. Then, the outage performance has been studied for the VLC downlink and non-orthogonal multiple access schemes over the RF uplink, respectively, by using stochastic geometry theory, while considering the randomness of the number of the terminals, and all terminals are spatially and randomly distributed in the 3-D room and all RF uplinks follow Rician fading. Finally, the approximated analytical expressions for the outage probability are derived and verified through Monte Carlo simulations

Design Synthesis of Nitrogen-Doped TiO2@Carbon Nanosheets toward Selective Nitroaromatics Reduction under Mild Conditions

The development of a facile, low-cost, and ecofriendly approach to the synthesis of aromatic amines remains a great scientific challenge. TiO2, as a low-cost and earth abundant metal oxide, is usually not active for thermo-catalyzed nitro reduction. Herein, we report a composite nanosheet catalyst, composed of nitrogen-doped TiO2 and carbon (N-TiO2@C), which exhibits highly efficient, thermo-catalytic performance for selective nitroaromatic reduction at room temperature. The NTiO2@C nanosheet catalyst is synthesized via a facile approach where C3N4 nanosheets are utilized not only as a structuredirecting agent to control the shape, size, and crystal phase of TiO2 but also as a source of nitrogen for doping into both TiO2 and carbon nanosheets. Furthermore, the origin of the superior performance of the N-TiO2@C nanosheet composite catalyst, along with a possible nitroaromatic reduction mechanism, has also been explored.This work was financially supported by the National Key Project on Basic Research (Grant No. 2013CB933203), the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB20000000), the Natural Science Foundation of China (Grants No. 21607153, 21373224 and 21577143), the Natural Science Foundation of Fujian Province (Grant No. 2015J05044), and the Frontier Science Key Project of the Chinese Academy of Sciences (QYZDB-SSW-JSC027). The work at ORNL was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division (STEM-EELS), and through a user project supported by ORNL’s Center for Nanophase Materials Sciences, which is sponsored by the Scientific User Facilities Division of U.S. DOE

Xuebijing injection alleviates liver injury by inhibiting secretory function of Kupffer cells in heat stroke rats

AbstractObjectiveTo evaluate the effects of Xuebijing (XBJ) injection in heat stroke (HS) rats and to investigate the mechanisms underlying these effects.MethodsSixty anesthetized rats were randomized into three groups and intravenously injected twice daily for 3 days with 4 mL XBJ (XBJ group) or phosphate buffered saline (HS and Sham groups) per kg body weight. HS was initiated in the HS and XBJ groups by placing rats in a simulated climate chamber (ambient temperature 40°C, humidity 60%). Rectal temperature, aterial pressure, and heart rate were monitored and recorded. Time to HS onset and survival were determined, and serum concentrations of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, alanine-aminotransferase (ALT), and aspartate-aminotransferase (AST) were measured. Hepatic tissue was harvested for pathological examination and electron microscopic examination. Kupffer cells (KCs) were separated from liver at HS initiation, and the concentrations of secreted TNF-α, IL-β and IL-6 were measured.ResultsTime to HS onset and survival were significantly longer in the XBJ than in the HS group. Moreover, the concentrations of TNF-α, IL-1β, IL-6, ALT and AST were lower and liver injury was milder in the XBJ than in the HS group. Heat-stress induced structural changes in KCs and hepatic cells were more severe in the HS than in the XBJ group and the concentrations of TNF-α, IL-β and IL-6 secreted by KCs were lower in the XBJ than in the HS group.ConclusionXBJ can alleviate HS-induced systemic inflammatory response syndrome and liver injury in rats, and improve outcomes. These protective effects may be due to the ability of XBJ to inhibit cytokine secretion by KCs

Unravelling the spatial variation of nitrous oxide emissions from a step-feed plug-flow full scale wastewater treatment plant

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/Plug-flow activated sludge reactors (ASR) that are step-feed with wastewater are widely adopted in wastewater treatment plants (WWTPs) due to their ability to maximise the use of the organic carbon in wastewater for denitrification. Nitrous oxide (N2O) emissions are expected to vary along these reactors due to pronounced spatial variations in both biomass and substrate concentrations. However, to date, no detailed studies have characterised the impact of the step-feed configuration on emission variability. Here we report on the results from a comprehensive online N2O monitoring campaign, which used multiple gas collection hoods to simultaneously measure emission along the length of a full-scale, stepfed, plug-flow ASR in Australia. The measured N2O fluxes exhibited strong spatial-temporal variation along the reactor path. The step-feed configuration had a substantial influence on the N2O emissions, where the N2O emission factors in sections following the first and second step feed were 0.68% ± 0.09% and 3.5% ± 0.49% of the nitrogen load applied to each section. The relatively high biomass-specific nitrogen loading rate in the second section of the reactor was most likely cause of the high emissions from this section