Analysis of phosphorus removal and anaerobic selector performance in a full-scale activated sludge process in Singapore.

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.     

Probabilistic evaluation of lateral extent of soil liquefaction under earthquake loading

A Monte Carlo simulation method for calculating the probability of soil liquefaction of a finite area in which the ground motion is propagated upward from the bedrock through the soil layers is presented. The vertical propagation of the ground motion through the soil layers is analyzed using random vibration analysis. To account for the variability of soil properties with depth, the soil deposit is divided into layers. Within each layer the horizontal statistical correlation of the undrained cyclic shearing strength against liquefaction is taken into consideration by describing it as a two-dimensional homogeneous random field. The method computes the probability of liquefaction spreading over a specified area under a given earthquake loading considering the effects of spatial correlation of soil properties.     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load     

A model for the seismic reliability assessment of electric power transmission systems

A comprehensive model to evaluate the seismic reliability of electric power transmission systems is presented. The model provides information on the probability of structural failure of critical equipment at the major substations, from which the corresponding probabilities of power disruption to a given service area are determined. With the proposed methodology earthquake ground motions are defined as stochastic processes, and seismic capacities of electrical equipment are determined on the basis of available test data and simple modeling, from which fragility functions of critical equipment and specific substations are developed. Probabilities of power disruption resulting from network disconnectivity and abnormal power flow are assessed through Monte Carlo simulation. As a case study, the proposed model is applied to the electric power network in San Francisco and vicinity under the 1989 Loma Prieta earthquake, and the probabilities of power interruption are contrasted with the actual power failures observed during that earthquake.     

Induced magnetic fields as evidence for subsurface oceans in Europa and Callisto

The Galileo spacecraft has been orbiting Jupiter since 7 December 1995, and encounters one of the four galilean satellites-Io, Europa, Ganymede and Callisto-on each orbit. Initial results from the spacecraft's magnetometer have indicated that neither Europa nor Callisto have an appreciable internal magnetic field, in contrast to Ganymede and possibly Io. Here we report perturbations of the external magnetic fields (associated with Jupiter's inner magnetosphere) in the vicinity of both Europa and Callisto. We interpret these perturbations as arising from induced magnetic fields, generated by the moons in response to the periodically varying plasma environment. Electromagnetic induction requires eddy currents to flow within the moons, and our calculations show that the most probable explanation is that there are layers of significant electrical conductivity just beneath the surfaces of both moons. We argue that these conducting layers may best be explained by the presence of salty liquid-water oceans, for which there is already indirect geological evidence in the case of Europa.     

湖北黄麦岭沉积变质磷灰岩选矿技术研究

黄麦岭磷矿属较易选的低品位沉积变质磷灰岩矿,通过扩能改造、回水利用等措施,不仅提高了资源的综合利用率,也为公司每年降低生产成本4 000多万元,创造了可观的经济效益.     

新型锁相环在频率跟踪技术中的研究

在比较电力系统频率跟踪技术中软硬件同步优缺点的基础上,提出了一种基于FPGA的全数字锁相环(ADPLL)电路实现电力系统频率跟踪的技术;将FPGA技术运用于同步跟踪技术中,解决了软硬同步方法中的各个不足之处;全数字锁相环电路采用VHDL语言和FPGA设计,仿真波形和实验结果表明,该电路能够很好地跟踪电网频率的实时变化,相位误差仅为0.1%,频率测量误差仅为0.06%,实现了同频率同相位的锁定;速度快、精度高;对电网的谐波计算有较大的实际意义.     

A proposal for student modeling based on ontologies and diagnosis rules

The advances in the educational field and the high complexity of student modeling have provoked it to be one of the aspects more investigated in Intelligent Tutoring Systems (ITSs). The Student Models (SMs) should not only represent the student’s knowledge, but rather they should reflect, as faithfully as possible, the student’s reasoning process. To facilitate this goal, in this article a new approach to student modeling is proposed that benefits from the advantages of Ontological Engineering, advancing in the pursue of a more granular and complete knowledge representation. It’s focused, mainly, on the SM cognitive diagnosis process, and we present a method providing a rich diagnosis about the student’s knowledge state – especially, about the state of learning objectives reached or not. The main goal is to achieve SMs with a good adaptability to the student’s features and a high flexibility for its integration in varied ITSs.     

Phase characterisation of metalenses

Metalenses have emerged as a new optical element or system in recent years, showing superior performance and abundant applications. However, the phase distribut...     

Relevance of the skewness index in DTI exploration of multiple sclerosis

Object  To this day, no parameter can really monitor the progression of multiple sclerosis (MS). In this study, an index the skewness (S) derived from parameters calculated in diffusion tensor imaging (DTI) has been tested on MS patients for its ability to monitor the disease course. Materials and methods  Eighteen patients underwent two examinations within 3 months consisting of a clinical evaluation (EDSS) and DTI acquisitions on a 1.5 T imager. Tensor was calculated thanks to“home-made” software. Mean diffusivity (MD) and fractional anisotropy (FA) histograms were described for normal-appearing white matter (NAWM) and gray matter (GM) of patients with S and also with usually indices peak position (pp) and peak height (ph) for the whole group of patients and for two separate groups according to their clinical status (EDSS  ≤  3 and EDSS  > 3 at month 0). Results  Although no significant clinical evolution is observed over 3 months, S in GM showed a significant shift for both MD/FA histograms towards abnormal values for the whole group of patients (p = 0.02/p = 0.04) and for the group with EDSS  ≤  3 (p = 0.04/p = 0.007), while ph and pp do not. Conclusion  S in GM could be an alternative marker to monitor the disease course before the repercussion on the clinical score.