Genetic covariance among measures of information processing speed, working memory, and IQ

The genetic relationship between lower (information processing speed), intermediate (working memory), and higher levels (complex cognitive processes as indexed by IQ) of mental ability was studied in a classical twin design comprising 166 monozygotic and 190 dizygotic twin pairs. Processing speed was measured by a choice reaction time (RT) task (2-, 4-, and 8-choice), working memory by a visual-spatial delayed response task, and IQ by the Multidimensional Aptitude Battery. Multivariate analysis, adjusted for test-retest reliability, showed the presence of a genetic factor influencing all variables and a genetic factor influencing 4- and 8-choice RTs, working memory, and IQ. There were also genetic factors specific to 8-choice RT, working memory, and IQ. The results confirmed a strong relationship between choice RT and IQ (phenotypic correlations: -0.31 to -0.53 in females, -0.32 to -0.56 in males; genotypic correlations: -0.45 to -0.70) and a weaker but significant association between working memory and IQ (phenotypic: 0.26 in females, 0.13 in males; genotypic: 0.34). A significant part of the genetic variance (43%) in IQ was not related to either choice RT or delayed response performance, and may represent higher order cognitive processes.

A titrimetric respirometer measuring the nitrifiable nitrogen in wastewater using in-sensor-experiment

Measurement of nitrifiable nitrogen contained in wastewater by combining the existing respirometric and titrimetric principles is reported. During an in-sensor-experiment using nitrifying activated sludge. both the dissolved oxygen (DO) and pH in the mixed liquor were measured, and the FH was controlled at a set-point through titration of base or acid. A combination of the oxygen uptake rate (OUR), which was obtained from the measured DO signal, and the titration data allowed calculation of the nitrifiable nitrogen and the short-term biological oxygen demand (BOD) of the wastewater sample that was initially added to the sludge. The calculation was based solely on stoichiometric relationships. The approach was preliminarily tested with two types of wastewaters using a prototype sensor. Good correlation was obtained. (C) 2000 Elsevier Science Ltd. All rights reserved.

A systematic approach to error isolation in computerized wastewater simulation models

Activated sludge models are used extensively in the study of wastewater treatment processes. While various commercial implementations of these models are available, there are many people who need to code models themselves using the simulation packages available to them, Quality assurance of such models is difficult. While benchmarking problems have been developed and are available, the comparison of simulation data with that of commercial models leads only to the detection, not the isolation of errors. To identify the errors in the code is time-consuming. In this paper, we address the problem by developing a systematic and largely automated approach to the isolation of coding errors. There are three steps: firstly, possible errors are classified according to their place in the model structure and a feature matrix is established for each class of errors. Secondly, an observer is designed to generate residuals, such that each class of errors imposes a subspace, spanned by its feature matrix, on the residuals. Finally. localising the residuals in a subspace isolates coding errors. The algorithm proved capable of rapidly and reliably isolating a variety of single and simultaneous errors in a case study using the ASM 1 activated sludge model. In this paper a newly coded model was verified against a known implementation. The method is also applicable to simultaneous verification of any two independent implementations, hence is useful in commercial model development.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Recent advances in processing and characterization of periodic mesoporous MCM-41 silicate molecular sieves

The discovery of periodic mesoporous MCM-41 and related molecular sieves has attracted significant attention from a fundamental as well as applied perspective. They possess well-defined cylindrical/hexagonal mesopores with a simple geometry, tailored pore size, and reproducible surface properties. Hence, there is an ever-growing scientific interest in the challenges posed by their processing and characterization and by the refinement of various sorption models. Further, MCM-41-based materials are currently under intense investigation with respect to their utility as adsorbents, catalysts, supports, ion-exchangers, and molecular hosts. In this article, we provide a critical review of the developments in these areas with particular emphasis on adsorption characteristics, progress in controlling the pore sizes, and a comparison of pore size distributions using traditional and newer models. The model proposed by the authors for adsorption isotherms and criticalities in capillary condensation and hysteresis is found to explain unusual adsorption behavior in these materials while providing a convenient characterization tool.

Human cortical processing of colour and pattern

The present study investigates human visual processing of simple two-colour patterns using a delayed match to sample paradigm with positron emission tomography (PET). This study is unique in that we specifically designed the visual stimuli to be the same for both pattern and colour recognition with all patterns being abstract shapes not easily verbally coded composed of two-colour combinations. We did this to explore those brain regions required for both colour and pattern processing and to separate those areas of activation required for one or the other. We found that both tasks activated similar occipital regions, the major difference being more extensive activation in pattern recognition. A right-sided network that involved the inferior parietal lobule, the head of the caudate nucleus, and the pulvinar nucleus of the thalamus was common to both paradigms. Pattern recognition also activated the left temporal pole and right lateral orbital gyrus, whereas colour recognition activated the left fusiform gyrus and several right frontal regions. (C) 2001 Wiley-Liss, Inc.

Operating space diagrams: a tool for designers of wastewater treatment plants

Recent years have seen the introduction of new and varied designs of activated sludge plants. With increasing needs for higher efficiencies and lower costs, the possibility of a plant that operates more effectively has created the need for tools that can be used to evaluate and compare designs at the design stage. One such tool is the operating space diagram. It is the aim of this paper to present this tool and demonstrate its application and relevance to design using a simple case study. In the case study, use of the operating space diagram suggested changes in design that would improve the flexibility of the process. It also was useful for designing suitable control strategies.

Using the World Wide Web to revolutionise technology transfer and training in the water and wastewater industries

Industry professionals of the near future will be supported by an IT infrastructure that enables them to complete a task by drawing on resources and people with expertise anywhere in the world, and access to knowledge through specific training programs that address the task requirements. The increasing uptake of new technologies enables information to reach a diverse population and to provide flexible learning environments 24 hours a day, 7 days a week. This paper examines one of the key areas where the World Wide Web will impact on the water and wastewater industries, namely technology transfer and training. The authors will present their experiences of developing online training courses for wastewater industry professionals over the last two years. The perspective is that of two people working at the coalface.

Biodegradation of high strength phenolic wastewater using SBR

This investigation demonstrates the capability of a bench-scale sequencing batch reactor (SBR) to biodegrade an inhibitory substrate at a high loading rate. A SBR loading rate of 3.12 kg phenol.m(-3)d(-1) (2.1 g COD.g(-1) MLVSS d(-1)) with a COD removal efficiency of 97% at a SRT of 4 days and a HRT of 10 hours was achieved; this rate was not reached before. The SBR was operated at 4 hours cycle, including 3 hours react phase. The synthetic wastewater of 1300 mg/L phenol was the sole carbon source. Oxygen uptake rates (OUR) were monitored in-situ at various stages of the SBR. The oxygen mass transfer coefficient, K(L)a, of 12.6 h(-1) was derived from respirometry. Use of respirometry in SBR aided the tracking of the soluble substrate through OUR.