Understanding conceptual schemas: exploring the role of application and IS domain knowledge

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.

Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB

A 16S rRNA gene database (http://greengenes.bl.gov) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria.

Application and evaluation of classification trees for screening unwanted plants

Risk assessment systems for introduced species are being developed and applied globally, but methods for rigorously evaluating them are still in their infancy. We explore classification and regression tree models as an alternative to the current Australian Weed Risk Assessment system, and demonstrate how the performance of screening tests for unwanted alien species may be quantitatively compared using receiver operating characteristic (ROC) curve analysis. The optimal classification tree model for predicting weediness included just four out of a possible 44 attributes of introduced plants examined, namely: (i) intentional human dispersal of propagules; (ii) evidence of naturalization beyond native range; (iii) evidence of being a weed elsewhere; and (iv) a high level of domestication. Intentional human dispersal of propagules in combination with evidence of naturalization beyond a plants native range led to the strongest prediction of weediness. A high level of domestication in combination with no evidence of naturalization mitigated the likelihood of an introduced plant becoming a weed resulting from intentional human dispersal of propagules. Unlikely intentional human dispersal of propagules combined with no evidence of being a weed elsewhere led to the lowest predicted probability of weediness. The failure to include intrinsic plant attributes in the model suggests that either these attributes are not useful general predictors of weediness, or data and analysis were inadequate to elucidate the underlying relationship(s). This concurs with the historical pessimism that we will ever be able to accurately predict invasive plants. Given the apparent importance of propagule pressure (the number of individuals of an species released), future attempts at evaluating screening model performance for identifying unwanted plants need to account for propagule pressure when collating and/or analysing datasets. The classification tree had a cross-validated sensitivity of 93.6% and specificity of 36.7%. Based on the area under the ROC curve, the performance of the classification tree in correctly classifying plants as weeds or non-weeds was slightly inferior (Area under ROC curve = 0.83 +/- 0.021 (+/- SE)) to that of the current risk assessment system in use (Area under ROC curve = 0.89 +/- 0.018 (+/- SE)), although requires many fewer questions to be answered.

Blind detection of PAM and QAM in fading channels

This correspondence considers block detection for blind wireless digital transmission. At high signal-to-noise ratio (SNR), block detection errors are primarily due to the received sequence having multiple possible decoded sequences with the same likelihood. We derive analytic expressions for the probability of detection ambiguity written in terms of a Dedekind zeta function, in the zero noise case with large constellations. Expressions are also provided for finite constellations, which can be evaluated efficiently, independent of the block length. Simulations demonstrate that the analytically derived error floors exist at high SNR.

Competition between polyphosphate and glycogen accumulating organisms in enhanced biological phosphorus removal systems with acetate and propionate as carbon sources

Enhanced biological phosphorus removal (EBPR) is a widely used process for achieving phosphorus removal from wastewater. A potential reason for EBPR failure is the undesirable growth of glycogen accumulating organisms (GAOs), which can compete for carbon sources with the bacterial group responsible for phosphorus removal from wastewater: the polyphosphate accumulating organisms (PAOs). This study investigates the impact of carbon source on EBPR performance and the competition between PAOs and GAOs. Two sequencing batch reactors (SBRs) were operated during a 4-6 month period and fed with a media containing acetate or propionate, respectively, as the sole carbon source. It was found that the acetate fed SBR rarely achieved a high level of phosphorus removal, and that a large portion of the microbial community was comprised of Candidatus Competibacter phosphatis, a known GAO. The propionate fed SBR, however, achieved stable phosphorus removal throughout the study, apart from one brief disturbance. The bacterial community of the propionate fed SBR was dominated by Candidatus Accumulibacter phosphatis, a known PAO, and did not contain Competibacter In a separate experiment, another SBR was seeded with a mixture of PAOs and a group of alphaproteobacterial GAOs, both enriched with propionate as the sole carbon source. Stable EBPR was achieved and the PAO population increased while the GAOs appeared to be out-competed. The results of this paper suggest that propionate may provide PAOs with a selective advantage over GAOs in the PAO-GAO competition, particularly through the minimisation of Competibacter Propionate may be a more suitable substrate than acetate for enhancing phosphorus removal in EBPR systems. (c) 2005 Elsevier B.V. All rights reserved.

Construction and analysis of a metagenomic library from an enhanced biological phosphorus removal biomass

The enhanced biological phosphorus removal (EBPR) process is regularly used for the treatment of wastewater, but suffers from erratic performance. Successful EBPR relies on the growth of bacteria called polyphosphate-accumulating organisms (PAOs), which store phosphorus intracellularly as polyphosphate, thus removing it from wastewater. Metabolic models have been proposed which describe the measured chemical transformations, however genetic evidence is lacking to confirm these hypotheses. The aim of this research was to generate a metagenomic library from biomass enriched in PAOs as determined by phenotypic data and fluorescence in situ hybridisation (FISH) using probes specific for the only described PAO to date, Candidatus Accumulibacter phosphatis. DNA extraction methods were optimised and two fosmid libraries were constructed which contained 93 million base pairs of metagenomic data. Initial screening of the library for 16S rRNA genes revealed fosmids originating from a range of non-pure-cultured wastewater bacteria. The metagenomic libraries constructed will provide the ability to link phylogenetic and metabolic data for bacteria involved in nutrient removal from wastewater. Keywords DNA extraction; EBPR; metagenomic library; 16S rRNA gene.

Effect of free ammonia and free nitrous acid concentration on the anabolic and catabolic processes of an enriched Nitrosomonas culture

The effects of free ammonia (FA; NH3) and free nitrous acid (FNA; HNO2) concentrations on the metabolisms of an enriched ammonia oxidizing bacteria (AOB) culture were investigated using a method allowing the decoupling of growth and energy generation processes. A lab-scale sequencing batch reactor (SBR) was operated for the enrichment of an AOB culture. Fluorescent in-situ hybridization (FISH) analysis showed that 82% of the bacterial population in the SBR bound to the NEU probe specifically designed for Nitrosomonas europaea. Batch tests were carried out to measure the oxygen and ammonium consumption rates by the culture at various FA and FNA levels, in the presence or absence of inorganic carbon (CO2, HCO3, and CO32-). It was revealed that FA of up to 16.0 mgNH(3)-N (.) L-1, which was the highest concentration used in this study, did not have any inhibitory effect on either the catabolic or anabolic processes of the Nitrosomonas culture. In contrast, FNA inhibited both the growth and energy production capabilities of the Nitrosomonas culture. The inhibition on growth initiated at approximately 0.10 mgHNO(2)-(NL-1)-L-., and the data suggested that the biosynthesis was completely stopped at an FNA concentration of 0.40 mgHNO(2)-N (.) L-1. The inhibition on energy generation initiated at a slightly lower level but the Nitrosomonas culture was still oxidizing ammonia at half of the maximum rate at an FNA concentration of 0.50-0.63 mgHNO(2)-N (.) L-1. The affinity constant of the Nitrosomonas culture with respect to ammonia was determined to be 0.36 mgNH3-N (.) L-1, independent of the presence or absence of inorganic carbon. (c) 2006 Wiley Periodicals, Inc.

Effect of temperature and free ammonia on nitrification and nitrite accumulation in landfill leachate and analysis of its nitrifying bacterial community by FISH

The cause of seasonal failure of a nitrifying municipal landfill leachate treatment plant utilizing a fixed biofilm was investigated by wastewater analyses and batch respirometric tests at every treatment stage. Nitrification of the leachate treatment plant was severely affected by the seasonal temperature variation. High free ammonia (NH3-N) inhibited not only nitrite oxidizing bacteria (NOB) but also ammonia oxidizing bacteria (AOB). In addition, high pH also increased free ammonia concentration to inhibit nitrifying activity especially when the NH4-N level was high. The effects of temperature and free ammonia of landfill leachate on nitrification and nitrite accumulation were investigated with a semi-pilot scale biofilm airlift reactor. Nitrification rate of landfill leachate increased with temperature when free ammonia in the reactor was below the inhibition level for nitrifiers. Leachate was completely nitrified up to a load of 1.5 kg NH4-N m(-3) d(-1) at 28 degrees C. The activity of NOB was inhibited by NH3-N resulting in accumulation of nitrite. NOB activity decreased more than 50% at 0.7 mg NH3-N L-1. Fluorescence in situ hybridization (FISH) was carried out to analyze the population of AOB and NOB in the nitrite accumulating nitrifying biofilm. NOB were located close to AOB by forming small clusters. A significant fraction of AOB identified by probe Nso1225 specifically also hybridized with the Nitrosonlonas specific probe Nsm156. The main NOB were Nitrobacter and Nitrospira which were present in almost equal amounts in the biofilm as identified by simultaneous hybridization with Nitrobacter specific probe Nit3 and Nitrospira specific probe Ntspa662. (c) 2005 Elsevier Ltd. All rights reserved.

Microbial Fuel Cells: Methodology and Technology

Microbial fuel cell (MFC) research is a rapidly evolving field that lacks established terminology and methods for the analysis of system performance. This makes it difficult for researchers to compare devices on an equivalent basis. The construction and analysis of MFCs requires knowledge of different scientific and engineering fields, ranging from microbiology and electrochemistry to materials and environmental engineering. DescribingMFCsystems therefore involves an understanding of these different scientific and engineering principles. In this paper, we provide a review of the different materials and methods used to construct MFCs, techniques used to analyze system performance, and recommendations on what information to include in MFC studies and the most useful ways to present results.

Modelling biological processes under anaerobic conditions through integrating titrimetric and off-gas measurements - applied to EBPR systems

An innovative method for modelling biological processes under anaerobic conditions is presented and discussed. The method is based on titrimetric and off-gas measurements. Titrimetric data is recorded as the addition rate of hydroxyl ions or protons that is required to maintain pH in a bioreactor at a constant level. An off-gas analysis arrangement measures, among other things, the transfer rate of carbon dioxide. The integration of these signals results in a continuous signal which is solely related to the biological reactions. When coupled with a mathematical model of the biological reactions, the signal allows a detailed characterisation of these reactions, which would otherwise be difficult to achieve. Two applications of the method to the enhanced biological phosphorus removal processes are presented and discussed to demonstrate the principle and effectiveness of the method.

Identifying causes for N2O accumulation in a lab-scale sequencing batch reactor performing simultaneous nitrification, denitrification and phosphorus removal

The recently described process of simultaneous nitrification, denitrification and phosphorus removal (SNDPR) has a great potential to save capital and operating costs for wastewater treatment plants. However, the presence of glycogen-accumulating organisms (GAOs) and the accumulation of nitrous oxide (N2O) can severely compromise the advantages of this process. In this study, these two issues were investigated using a lab-scale sequencing batch reactor performing SNDPR over a 5-month period. The reactor was highly enriched in polyphosphate-accumulating organisms (PAOs) and GAOs representing around 70% of the total microbial community. PAOs were the dominant population at all times and their abundance increased, while GAOs population decreased over the study period. Anoxic batch tests demonstrated that GAOs rather than denitrifying PAOs were responsible for denitrification. NO accumulated from denitrification and more than half of the nitrogen supplied in a reactor cycle was released into the atmosphere as NO. After mixing SNDPR sludge with other denitrifying sludge, N2O present in the bulk liquid was reduced immediately if external carbon was added. We therefore suggest that the N2O accumulation observed in the SNDPR reactor is an artefact of the low microbial diversity facilitated by the use of synthetic wastewater with only a single carbon source. (C) 2005 Elsevier B.V. All rights reserved.

Stoichiometric and kinetic characterisation of Nitrobacter in mixed culture by decoupling the growth and energy generation processes

The growth, maintenance and lysis processes of Nitrobacter were characterised. A Nitrobacter culture was enriched in a sequencing batch reactor (SBR). Fluorescent in situ hybridisation showed that Nitrobacter constituted 73% of the bacterial population. Batch tests were carried out to measure the oxygen uptake rate and/or nitrite consumption rate when both nitrite and CO2 were in excess, and in the absence of either of these two substrates. The results obtained, along with the SBR performance data, allowed the determination of the maintenance coefficient and in situ cell lysis rate of Nitrobacter. Nitrobacter spends a significant amount of energy for maintenance, which varies considerably with the specific growth rate. At maximum growth, Nitrobacter consume nitrite at a rate of 0.042 mgN/mgCOD(biomass)center dot h for maintenance purposes, which increases more than threefold to 0.143 mgN/mgCOD(biomass)center dot h in the absence of growth. In the SBR, where Nitrobacter grew at 40% of its maximum growth rate, a maintenance coefficient of 0.113 mgN/mgCOD center dot h was found, resulting in 42% of the total amount of nitrite being consumed for maintenance. The above three maintenance coefficient values obtained at different growth rates appear to support the maintenance model proposed in Pirt (1982). The in situ lysis rate of Nitrobacter was determined to be 0.07/day under aerobic conditions at 22 C and pH 7.3. Further, the maximum specific growth rate of Nitrobacter was estimated to be 0.02/h (0.48/day). The affinity constant of Nitrobacter with respect to nitrite was determined to be 1.50 mgNO(2)(-)-N/L, independent of the presence or absence of CO2. (c) 2006 Wiley Periodicals, Inc.