This paper analyses the performance of the anaerobic selector (A/O process) in a full-scale activated sludge process receiving mostly industrial sewage discharge (> 60%) in Singapore. In addition to the sludge settleability, enhanced biological phosphorus removal (EBPR) was studied. The sludge volume index (SVI) reduced from 200 to 80 ml g(-1) and foaming was suppressed significantly, indicating the effectiveness of the anaerobic selector in improving sludge settleability. The phosphorus removal efficiency was 66%, and 7.5 mg HAc-COD was consumed per mg PO4(3-) -P removed. In the anaerobic compartment, 31% of the SCOD and 73% of the acetic acid in the settled sewage were removed with PO4(3-) -P release of 14.1 mg PO4(3-)-P l(-1). The linear correlation between PO4(3-) -P release in the anaerobic compartment and PO4(3-) -P uptake in the aerobic compartment indicates that there is about 0.8 mg PO4(3-) -P release in the anaerobic compartment per mg PO34(3-) -P uptake in the aerobic compartment. The fates of volatile fatty acids (VFAs) and its short chain acids (SCAs) in the process were studied and discussed. 相似文献
A detailed survey on the motivations, design, applications, current status, and limitations of computers designed for symbolic processing is provided. Symbolic processing computations are performed at the word, relation, or meaning levels, and the knowledge used in symbolic applications may be fuzzy, uncertain, indeterminate, and ill represented. Various techniques for knowledge representation and processing are discussed from both the designers' and users' points of view. The design and choice of a suitable language for symbolic processing and the mapping of applications into a software architecture are then considered. The process of refining the application requirements into hardware and software architectures is treated, and state-of-art sequential and parallel computers designed for symbolic processing are discussed 相似文献
High level expression of recombinant human tumour necrosis factor β (rh TNF-β) in Escherichia coli results in the formation of two portions of protein, namely soluble active protein and insoluble protein which is inactive and aggregates in the form of inclusion bodies (IBs). In this study, a procedure for purification and renaturation of rh TNF-β from inclusion bodies has been designed and verified experimentally with a product purity of more than 90% and a recovery of about 30%. The procedure includes washing of IBs with specific wash buffer (Triton X-100/EDTA/lysozyme/PMSF), their solubilization with 8 mol dm?3 alkaline urea, purification with ion-exchange columns, refolding with renaturation buffer and finally concentration and desalination with an ultrafiltration membrane. The characteristics of the renatured protein were identical with those of purified protein from the soluble fraction as demonstrated by (1) SDS-PAGE, (2) cytotoxic activity on mouse L929 cells, (3) N-terminal amino acid sequence, and (4) gel filtration chromatography. 相似文献
Speech emotion recognition (SER) systems identify emotions from the human voice in the areas of smart healthcare, driving a vehicle, call centers, automatic translation systems, and human-machine interaction. In the classical SER process, discriminative acoustic feature extraction is the most important and challenging step because discriminative features influence the classifier performance and decrease the computational time. Nonetheless, current handcrafted acoustic features suffer from limited capability and accuracy in constructing a SER system for real-time implementation. Therefore, to overcome the limitations of handcrafted features, in recent years, variety of deep learning techniques have been proposed and employed for automatic feature extraction in the field of emotion prediction from speech signals. However, to the best of our knowledge, there is no in-depth review study is available that critically appraises and summarizes the existing deep learning techniques with their strengths and weaknesses for SER. Hence, this study aims to present a comprehensive review of deep learning techniques, uniqueness, benefits and their limitations for SER. Moreover, this review study also presents speech processing techniques, performance measures and publicly available emotional speech databases. Furthermore, this review also discusses the significance of the findings of the primary studies. Finally, it also presents open research issues and challenges that need significant research efforts and enhancements in the field of SER systems.
By using an approximate formulation due to Berger it is shown that the vibration of rectangular plates with large amplitudes may be treated in a simple and unified manner. Numerical results are given for various boundary conditions. 相似文献
A study into the structural postbuckling response of symmetric laminated composite plates subjected to in-plane compressive load is presented in this contribution. Various cases of support conditions are investigated: loaded ends are either simply supported or clamped, while the unloaded edges are a combination of simple support, clamp, and free. The method of analysis used is the combination of the semienergy approach using the semianalytical finite-strip methodology and the well-known von Karman large-deflection equations. Extensive validation of the analytical solution with published theoretical solutions and experimental data are presented. The final form of the expression is quite versatile and can be readily used for design purposes. 相似文献