Phosphorus removal and recovery from domestic wastewater is urgent nowadays. A novel process of nutrients removal coupled with phosphorus recovery from domestic sewage was proposed and optimization of induced crystallization reaction was performed in this study. The results showed that 92.3% of phosphorus recovery via induced Hydroxyapatite crystallization was achieved at the optimum process parameters: reaction time of 80 min, seed crystal loads of 60 g/L, pH of 8.5, Ca/P mole ratio of 2.0 and 4.0 L/min aeration rate when the PO43--P concentration was 10 mg/L in the influent, displaying an excellent phosphorus recovery performance. Importantly, it was found that the effect of reaction temperature on induced Hydroxyapatite crystallization was slight, thus favoring practical application of phosphorus recovery method described in this study. From these results, the proposed method of induced HAP crystallization to recover phosphorus combined with nutrients removal can be an economical and effective technology, probably favoring the water pollution control and phosphate rock recycle.
Dye wastewater is one of typically non-biodegradable industrial effluents. A new process linking Fenton’s oxidation with biological oxidation proposed in this study was investigated to degrade the organic substances from real dye wastewater. During the combination process, the Fenton’s oxidation process can reduce the organic load and enhance biodegradability of dye wastewater, which is followed by biological aerated filter (BAF) system to further remove organic substances in terms of discharge requirement. The results showed that 97.6% of chemical oxygen demand (COD) removal by the combination process was achieved at the optimum process parameters: pH of 3.5, H2O2 of 2.0 mL/L, Fe(II) of 500 mg/L, 2.0 h treatment time in the Fenton’s oxidation process and hydraulic retention time (HRT) of 5 h in the BAF system. Under these conditions, COD concentration of effluent was 72.6 mg/L whereas 3020 mg/L in the influent, thus meeting the requirement of treated dye wastewater discharge performed by Chinese government (less than 100 mg/L). These results obtained here suggest that the new process combining Fenton’s oxidation with biological oxidation may provide an economical and effective alternative for treatment of non-biodegradable industrial wastewater.
Azo dye wastewater treatment is urgent necessary nowadays. Electrochemical technologies commonly enable more efﬁcient degradation of recalcitrant organic contaminants than biological methods, but those rely greatly on the energy consumption. A novel process of bioﬁlm coupled with electrolysis, i.e., bioelectrochemical system (BES), for methyl orange (MO) dye wastewater treatment was proposed and optimization of main inﬂuence factors was performed in this study. The results showed that BES had a positive effect on enhancement of color removal of MO wastewater and 81.9% of color removal efﬁciency was achieved at the optimum process parameters: applied voltage of 2.0 V, initial MO concentration of 20 mg/L, glucose loads of 0.5 g/L and pH of 8.0 when the hydraulic retention time (HRT) was maintained at 3 d, displaying an excellent color removal performance. Importantly, a wide range of effective pH, ranging from 6 to 9, was found, thus greatly favoring the practical application of BES described here. The absence of a peak at 463 nm showed that the azo bond of MO was almost completely cleaved after degradation in BES. From these results, the proposed method of biodegradation combined with electrochemical technique can be an effective technology for dye wastewater treatment and may hopefully be also applied for treatment of other recalcitrant compounds in water and wastewater.
In this paper, we propose and experimentally demonstrate a new method for optical frequency transfer over fibre. Instead of dual acousto-optic modulators (AOMs) as adopted in the traditional fibre phase noise compensation setup, here an active fibre phase noise compensation scheme with a single acousto-optic modulator (AOM) is used. The configuration simplifies the equipment of the user end while maintaining a high-performance optical frequency transfer stability. We demonstrate an actively stabilized coherent transfer at an optical frequency of 193.55THz over 10-km spooled fibre, obtaining a relative frequency stability (Allan deviation) of 3:84 #2; 10��16/1 s and 4:08 #2; 10��18/104 s, which is improved by about 2#24;3 orders of magnitude in comparison with the one without any phase noise compensation that achieves a relative frequency stability of 1:81 #2; 10��14/1 s and 2:48 #2; 10��15/104 s.
Based on real-time multi-domain communication signal analysis architecture, a high-efficiency blind carrier frequency estimation algorithm using the power spectrum symmetry of the measured modulated signal is presented. The proposed algorithm, which utilizes the moving averaged power spectrum achieved by the realtime spectrum analysis, iteratively identifies the carrier frequency in according to the power difference between the upper sideband and lower sideband, which is defined and revised by the estimated carrier frequency in each iteration. When the power difference of the two sidebands converges to the preset threshold, the carrier frequency can be obtained. For the modulation analysis, the measured signal can be coarsely compensated by the estimated result, and the residual carrier frequency error is eliminated by a following carrier synchronization loop. Compared with previous works, owing to the moving averaged power spectrum normalization and the smart iterative step variation mechanism for the two sidebands definition, the carrier frequency estimation accuracy and speed can be significantly improved without increasing the computational effort. Experimental results are included to demonstrate the outstanding performance of the proposed algorithm.
Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.