Development of a novel titration and off-gas analysis (TOGA) sensor for study of biological processes in wastewater treatment systems

The development of the new TOGA (titration and off-gas analysis) sensor for the detailed study of biological processes in wastewater treatment systems is outlined. The main innovation of the sensor is the amalgamation of titrimetric and off-gas measurement techniques. The resulting measured signals are: hydrogen ion production rate (HPR), oxygen transfer rate (OTR), nitrogen transfer rate (NTR), and carbon dioxide transfer rate (CTR). While OTR and NTR are applicable to aerobic and anoxic conditions, respectively, HPR and CTR are useful signals under all of the conditions found in biological wastewater treatment systems, namely, aerobic, anoxic and anaerobic. The sensor is therefore a powerful tool for studying the key biological processes under all these conditions. A major benefit from the integration of the titrimetric and off-gas analysis methods is that the acid/base buffering systems, in particular the bicarbonate system, are properly accounted for. Experimental data resulting from the TOGA sensor in aerobic, anoxic, and anaerobic conditions demonstrates the strength of the new sensor. In the aerobic environment, carbon oxidation (using acetate as an example carbon source) and nitrification are studied. Both the carbon and ammonia removal rates measured by the sensor compare very well with those obtained from off-line chemical analysis. Further, the aerobic acetate removal process is examined at a fundamental level using the metabolic pathway and stoichiometry established in the literature, whereby the rate of formation of storage products is identified. Under anoxic conditions, the denitrification process is monitored and, again, the measured rate of nitrogen gas transfer (NTR) matches well with the removal of the oxidised nitrogen compounds (measured chemically). In the anaerobic environment, the enhanced biological phosphorus process was investigated. In this case, the measured sensor signals (HPR and CTR) resulting from acetate uptake were used to determine the ratio of the rates of carbon dioxide production by competing groups of microorganisms, which consequently is a measure of the activity of these organisms. The sensor involves the use of expensive equipment such as a mass spectrometer and requires special gases to operate, thus incurring significant capital and operational costs. This makes the sensor more an advanced laboratory tool than an on-line sensor. (C) 2003 Wiley Periodicals, Inc.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Combined hydraulic and biological modelling and full-scale validation of SBR process

The biological reactions during the settling and decant periods of Sequencing Batch Reactors (SBRs) are generally ignored as they are not easily measured or described by modelling approaches. However, important processes are taking place, and in particular when the influent is fed into the bottom of the reactor at the same time (one of the main features of the UniFed process), the inclusion of these stages is crucial for accurate process predictions. Due to the vertical stratification of both liquid and solid components, a one-dimensional hydraulic model is combined with a modified ASM2d biological model to allow the prediction of settling velocity, sludge concentration, soluble components and biological processes during the non-mixed periods of the SBR. The model is calibrated on a full-scale UniFed SBR system with tracer breakthrough tests, depth profiles of particulate and soluble compounds and measurements of the key components during the mixed aerobic period. This model is then validated against results from an independent experimental period with considerably different operating parameters. In both cases, the model is able to accurately predict the stratification and most of the biological reactions occurring in the sludge blanket and the supernatant during the non-mixed periods. Together with a correct description of the mixed aerobic period, a good prediction of the overall SBR performance can be achieved.

Repeatability of surface EMG variables in the sternocleidomastoid and anterior scalene muscles

In this study we examined the repeatability and reliability of the surface electromyographic (sEMG) signal mean frequency (MNF), average rectified value (ARV) and conduction velocity (CV) measured for the sternocleidomastoid (SCM) and the anterior scalene (AS) muscles in nine healthy volunteers during 15-s isometric cervical flexion contractions at 50% of the maximal voluntary contraction level over 3 non-consecutive days. Repeatability and reliability estimates were obtained for the initial values and rates of change of each sEMG variable by using both the Intraclass Correlation Coefficient (ICC) and the normalised standard error of the mean (nSEM). Results from SCM indicated good levels of repeatability for the initial value and slope of ARV (ICC > 65%). For the AS, high levels of repeatability were identified for the initial value of MNF (ICC > 70%) and the slope of ARV (ICC > 75%). Values of nSEM in the range 2.8-7.2% were obtained for the initial values of MNF and CV for both SCM and AS, indicating clinically acceptable measurement precision. The low value obtained for the nSEM of the initial value of MNF for the AS, in combination with the high ICC, indicates that of all of the variables examined, this variable could offer the best normative index to distinguish between subjects with and without neck pain, and represents the sEMG variable of choice for future evaluation purposes.

Novel application of biological glue in the management of a complicated pneumothorax in cystic fibrosis

Spontaneous pneumothorax is a frequent complication in advanced lung disease of cystic fibrosis. We describe a case of a complicated pneumothorax in a 21-year old-woman with cystic fibrosis who was effectively treated with the application of biological glue via a minithoracotomy. (C) 2002 Wiley-Liss, Inc.

Children's body knowledge: Understanding 'life' as a biological goal

Two studies assessed the development of children's understanding of life as a biological goal of body functioning. In Study 1, 4-to-10-year-old children were given an interview consisting of a series of structured questions about the location and function of various body organs. Their responses were coded both for factual correctness and for appeals to the goal of maintaining life. The results showed a gradual increase in children's factual knowledge across this age range but an abrupt increase in appeals to life between the ages of 4 and 6. Analyses of the 4-year-olds' responses suggested that appeals to life were associated with increased knowledge of organ function, but not of organ location. Study 2 was designed to replicate the pattern found in Study I. A continuous sample of 4-to 5-year-old children was administered an abbreviated version of the interview from Study 1. Children's understanding of life as a biological goal was again found to be predictive of their knowledge of organ function, but not of organ location. These results indicate a reorganization in children's understanding of the body between the ages of 4 and 6, which coincides with children's discovery of 'life' as a biological goal for bodily function.

Acute stress hyperglycemia in cats is associated with struggling and increased concentrations of lactate and norepinephrine

We characterized the changes in blood glucose concentrations in healthy cats exposed to a short stressor and determined the associations between glucose concentrations, behavioral indicators of stress, and blood variables implicated in stress hyperglycemia (plasma glucose, lactate, insulin, glucagon, cortisol, epinephrine, and norepinephrine concentrations). Twenty healthy adult cats with normal glucose tolerance had a 5-minute spray bath. Struggling and vocalization were the most frequent behavioral responses. There was a strong relationship between struggling and concentrations of glucose and lactate. Glucose and lactate concentrations increased rapidly and significantly in all cats in response to bathing, with peak concentrations occurring at the end of the bath (glucose baseline 83 mg/dL, mean peak 162 mg/dL; lactate baseline 6.3 mg/dL, mean peak 64.0 mg/dL). Glucose response resolved within 90 minutes in 12 of the 20 cats. Changes in mean glucose concentrations were strongly correlated with changes in mean lactate (r =.84; P

An assessment of maturity from anthropometric measurements

Purpose: The range of variability between individuals of the same chronological age (CA) in somatic and biological maturity is large and especially accentuated around the adolescent growth spurt. Maturity assessment is an important consideration when dealing with adolescents, from both a research perspective and youth sports stratification. A noninvasive, practical method predicting years from peak height velocity (a maturity offset value) by using anthropometric variables is developed in one sample and cross-validated in two different samples. Methods: Gender specific multiple regression equations were calculated on a sample of 152 Canadian children aged 8-16 yr (79 boys; 73 girls) who were followed through adolescence from 1991 to 1997, The equations included three somatic dimensions (height, sitting height, and leg length), CA, and their interactions. The equations were cross-validated on a Combined sample of Canadian (71 boys, 40 girls measured from 1964 through 1973) and Flemish children (50 boys, 48 girls measured from 1985 through 1999). Results: The coefficient of determination (R2) for the boys' model was 0.92 and for the girls' model 0.91 the SEEs were 0.49 and 0.50, respectively, Mean difference between actual and predicted maturity offset for the verification samples was 0.24 (SD 0.65) yr in boys and 0,001 (SD 0.68) yr in girls. Conclusion: Although the cross-validation meets statistical standards or acceptance, caution 1, warranted with regard to implementation. It is recommended that maturity offset be considered as a categorical rather than a continuous assessment. Nevertheless, the equations presented are a reliable, noninvasive and a practical solution for the measure of biological maturity for matching adolescent athletes.

Toward a better understanding of the influences on physical activity: The role of determinants, correlates, causal variables, mediators, moderators, and confounders

Background: For research on physical activity interventions to progress systematically, the mechanisms of action must be studied. In doing so, the research methods and their associated concepts and terminology become more complex. It is particularly important to clearly distinguish among determinants, correlates, mediators, moderators, and confounder variables used in physical activity research. This article examines the factors that are correlated with and that may have a causal relationship to physical activity. Methods and Results: We propose that the term correlate be used, instead of determinant, to describe statistical associations or correlations between measured variables and physical activity. Studies of the correlates of physical activity are reviewed. The findings of these studies can help to critique existing theories of health behavior change and can provide hypotheses to be tested in intervention studies from which it is possible to draw causal inferences. Mediator, moderator, and confounder variables can act to influence measured changes in physical activity. Intervening causal variables that are necessary to complete a cause-effect pathway between an intervention and physical activity are termed mediators. The relationship between an intervention and physical activity behaviors may vary for different groups; the strata by which they vary are levels of moderators of the relationship. Other factors may distort or affect the observed relationships between program exposure and physical activity, and are known as confounders. Conclusions: Consistent use of terms and additional research on mediators and moderators of intervention effects will improve our ability to understand and influence physical activity.

A new level of conotoxin diversity, a non-native disulfide bond connectivity in alpha-conotoxin AuIB reduces structural definition but increases biological activity

alpha-Conotoxin AuIB and a disulfide bond variant of AuIB have been synthesized to determine the role of disulfide bond connectivity on structure and activity. Both of these peptides contain the 15 amino acid sequence GCCSYPPCFATNPDC, with the globular (native) isomer having the disulfide connectivity Cys(2-8 and 3-15) and the ribbon isomer having the disulfide connectivity Cys(2-15 and 3-8). The solution structures of the peptides were determined by NAIR spectroscopy, and their ability to block the nicotinic acetylcholine receptors on dissociated neurons of the rat parasympathetic ganglia was examined. The ribbon disulfide isomer, although having a less well defined structure, is surprisingly found to have approximately 10 times greater potency than the native peptide. To our knowledge this is the first demonstration of a non-native disulfide bond isomer of a conotoxin exhibiting greater biological activity than the native isomer.

Biological determinants of extinction risk: why are smaller species less vulnerable?

It is becoming increasingly clear that species of smaller body size tend to be less vulnerable to contemporary extinction threats than larger species, but few studies have examined the mechanisms underlying this pattern. In this paper, data for the Australian terrestrial mammal fauna are used to ask whether higher reproductive output or smaller home ranges can explain the reduced extinction risk of smaller species. Extinct and endangered species do indeed have smaller litters and larger home ranges for their body size than expected under a null model. In multiple regressions, however, only litter size is a significant predictor of extinction risk once body size and phylogeny are controlled for. Larger litters contribute to fast population growth, and are probably part of the reason that smaller species are less extinction-prone. The effect of litter size varies between the mesic coastal regions and the and interior of Australia, indicating that the environment a species inhabits mediates the effect of biology on extinction risk. These results suggest that predicting extinction risk from biological traits is likely to be a complex task which must consider explicitly interactions between biology and environment.

Species richness in agamid lizards: chance, body size, sexual selection or ecology?

Why does species richness vary so greatly across lineages? Traditionally, variation in species richness has been attributed to deterministic processes, although it is equally plausible that it may result from purely stochastic processes. We show that, based on the best available phylogenetic hypothesis, the pattern of cladogenesis among agamid lizards is not consistent with a random model, with some lineages having more species, and others fewer species, than expected by chance. We then use phylogenetic comparative methods to test six types of deterministic explanation for variation in species richness: body size, life history, sexual selection, ecological generalism, range size and latitude. Of eight variables we tested, only sexual size dimorphism and sexual dichromatism predicted species richness. Increases in species richness are associated with increases in sexual dichromatism but reductions in sexual size dimorphism. Consistent with recent comparative studies, we find no evidence that species richness is associated with small body size or high fecundity. Equally, we find no evidence that species richness covaries with ecological generalism, latitude or range size.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.