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    Experimental testing and modeling of partial nitrification at different temperatures

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    Nitrogen in wastewater treatment plant effluents has adverse environmental effects on aquatic systems. Excessive concentrations of nitrogen in water bodies can result in the depletion of dissolved oxygen, deterioration of water quality, and shifts of biotic community. Conventional biological nitrogen removal (BNR) processes consume high energy for nitrification and require external carbon for denitrification. Alternatively, partial nitrification is of interest as an emerging technology for its lower need of organic carbon addition and cost savings in aeration. In this study, the main objectives are: 1- developing a mathematical model involving operational parameters for the determination of successful partial nitrification conditions; 2- analyzing the factors affecting the performance of partial nitrification in a sequencing batch reactor (SBR) using kinetic models at 35oC; 3- investigating the effect of dissolved oxygen (DO) on nitrification in a sequencing batch reactor (SBR) treating low ammonia wastewater (40 mg N/L) at low temperature (14oC); 4- investigating the effect of nickel on nitrification in a sequencing batch reactor (SBR) treating low ammonia wastewater (40 mg N/L) at low temperature (10 oC). First, a mathematical model based on the minimum DO concentration (DOmin), minimum/maximum substrate concentration (Smin and Smax), was developed. The model evaluated the influence of pH (7-9), temperature (10oC-35oC), and solids retention time (SRT) (5days-infinity) on the minimum/maximum substrate concentration (MSC) values. In addition, specific application for shortcut nitrification-anammox process at 10oC was analyzed. Furthermore, experimental data from different literature studies was used for model simulation ii and the model prediction fitted experimental data well. The model provides a method to identify feasible combinations of pH, DO, total ammonium nitrogen (TAN), total nitrite nitrogen (TNN), and solids retention time (SRT) for successful shortcut nitrification. Second, to meet objective 2, a sequencing batch reactor (SBR) was operated at 35oC for over 4 months with dissolved oxygen (DO) and influent ammonia concentration as operating variables to evaluate nitrite accumulation. Stable partial nitrification was observed at two conditions, influent ammonia concentration of 190 mg N/L and a DO of 0.6-3.0 mg/L as well as influent ammonia concentration of 100 mg N/L and a DO of 0.15-2.0 mg/L with intermittent aeration. Kinetic parameters were determined or estimated with batch tests and model simulation. The kinetic model predicted the SBR performance well. Third, a sequencing batch reactor (SBR) treating low ammonia wastewater (40 mg N/L) at a low temperature (14 °C) was operated for 130 days. Three dissolved oxygen levels (5–6 mg O2/L, 2–3 mg O2/L, and 0.8–1.0 O2/L) were tested. Dissolved oxygen reduction resulted in lower ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) activity, with decreasing ammonia conversion ratio (ACR) and increasing nitrite accumulation ratio (NAR). The maximum growth rates of AOB and NOB determined in this study (0.28 and 0.38 d-1 ) were below the median literature values (0.47 and 0.62 d-1 ), whereas the oxygen half-saturation coefficients of AOB and NOB (1.36 and 2.79 mg/L) were higher than those found in the literature. The kinetic model explained the SBR performance well. Low dissolved oxygen, together with long solids retention time, was recommended for partial nitrification at a low temperature. Lastly, acute and chronic toxicity of nickel to nitrifiers was inverstigated. Chronic toxicity of nickel to nitrification of low ammonia synthetic wastewater was investigated at 10oC in two iii SBRs with 1 mg/L nickel dosing either from the beginning or after biomass concentration decreased to 300 mg/L. Significant nickel inhibition occurred at Ni/MLSS ratio of 2.7 mg Ni/ g MLSS. At a Ni/MLSS ratio of 4-7 mg Ni/g MLSS, ammonia oxidizing bacteria (AOB) activity was inhibited by 47%-58% after acclimatization. After long-term acclimatization to nickel at 10oC, high DO(~7mg/L) and SRT of 63-70 days, the µmax, b and Ko of AOB and NOB were determined as 0.16 d-1 , 0.098 d-1 and 2.08 mg O2/L, and 0.16 d-1 , 0.098 d-1 and 2.12 mg O2/L, respectively. Acute toxicity of nickel to nitrification at 10oC, 23oC, and 35oC was evaluated by short-term batch tests. The nickel inhibition constants based on a modified noncompetitive model for nitrification at 10oC, 23oC, and 35oC were determined. Long-term SBRs operation and short-term batch tests results were consistent. Short-term nickel inhibition of nitrifying bacteria was completely reversible

    On the Depth of Deep Neural Networks: A Theoretical View

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    People believe that depth plays an important role in success of deep neural networks (DNN). However, this belief lacks solid theoretical justifications as far as we know. We investigate role of depth from perspective of margin bound. In margin bound, expected error is upper bounded by empirical margin error plus Rademacher Average (RA) based capacity term. First, we derive an upper bound for RA of DNN, and show that it increases with increasing depth. This indicates negative impact of depth on test performance. Second, we show that deeper networks tend to have larger representation power (measured by Betti numbers based complexity) than shallower networks in multi-class setting, and thus can lead to smaller empirical margin error. This implies positive impact of depth. The combination of these two results shows that for DNN with restricted number of hidden units, increasing depth is not always good since there is a tradeoff between positive and negative impacts. These results inspire us to seek alternative ways to achieve positive impact of depth, e.g., imposing margin-based penalty terms to cross entropy loss so as to reduce empirical margin error without increasing depth. Our experiments show that in this way, we achieve significantly better test performance.Comment: AAAI 201
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