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.

A systematic approach for externalities in occupational safety through the use of the delphi methodology

Ramos, D., Arezes, P. M., & Afonso, P. (2015). A systematic approach for externalities in occupational safety through the use of the delphi methodology. Paper presented at the Occupational Safety and Hygiene III - Selected Extended and Revised Contributions from the International Symposium on Safety and Hygiene.

Chest pain in the emergency room. Importance of a systematic approach

OBJECTIVE: To evaluate the efficiency of a systematic diagnostic approach in patients with chest pain in the emergency room in relation to the diagnosis of acute coronary syndrome (ACS) and the rate of hospitalization in high-cost units. METHODS: One thousand and three consecutive patients with chest pain were screened according to a pre-established process of diagnostic investigation based on the pre-test probability of ACS determinate by chest pain type and ECG changes. RESULTS: Of the 1003 patients, 224 were immediately discharged home because of no suspicion of ACS (route 5) and 119 were immediately transferred to the coronary care united because of ST elevation or left bundle-branch block (LBBB) (route 1) (74% of these had a final diagnosis of acute myocardial infarction [AMI]). Of the 660 patients that remained in the emergency room under observation, 77 (12%) had AMI without ST segment elevation and 202 (31%) had unstable angina (UA). In route 2 (high probability of ACS) 17% of patients had AMI and 43% had UA, whereas in route 3 (low probability) 2% had AMI and 7 % had UA. The admission ECG has been confirmed as a poor sensitivity test for the diagnosis of AMI ( 49%), with a positive predictive value considered only satisfactory (79%). CONCLUSION: A systematic diagnostic strategy, as used in this study, is essential in managing patients with chest pain in the emergency room in order to obtain high diagnostic accuracy, lower cost, and optimization of the use of coronary care unit beds.

Fatigue: revue et approche diagnostique [Fatigue: review and systematic approach to potential causes]

Fatigue is defined as a sensation of exhaustion during or after usual activities. As much as one third of patients consulting a primary care physician report this complaint. After investigation, two-thirds of the patients have a somatic or psychiatric diagnosis. This review presents a seven-step approach to the patient who complains of fatigue.

Of flies, mice and men: a systematic approach to understanding the early life origins of chronic lung disease.

Despite intensive research efforts, the aetiology of the majority of chronic lung diseases (CLD) in both, children and adults, remains elusive. Current therapeutic options are limited, providing only symptomatic relief, rather than treating the underlying condition, or preventing its development in the first place. Thus, there is a strong and unmet clinical need for the development of both, novel effective therapies and preventative strategies for CLD. Many studies suggest that modifications of prenatal and/or early postnatal lung development will have important implications for future lung function and risk of CLD throughout life. This view represents a fundamental change of current pathophysiological concepts and treatment paradigms, and holds the potential to develop novel preventative and/or therapeutic strategies. However, for the successful development of such approaches, key questions, such as a clear understanding of underlying mechanisms of impaired lung development, the identification and validation of relevant preclinical models to facilitate translational research, and the development of concepts for correction of aberrant development, all need to be solved. Accordingly, a European Science Foundation Exploratory Workshop was held where clinical, translational and basic research scientists from different disciplines met to discuss potential mechanisms of developmental origins of CLD, and to identify major knowledge gaps in order to delineate a roadmap for future integrative research.

Practical applications of a systematic approach to the chemical abatement of pollutants in water and air

The present dissertation is devoted to the systematic approach to the development of organic toxic and refractory pollutants abatement by chemical decomposition methods in aqueous and gaseous phases. The systematic approach outlines the basic scenario of chemical decomposition process applications with a step-by-step approximation to the most effective result with a predictable outcome for the full-scale application, confirmed by successful experience. The strategy includes the following steps: chemistry studies, reaction kinetic studies in interaction with the mass transfer processes under conditions of different control parameters, contact equipment design and studies, mathematical description of the process for its modelling and simulation, processes integration into treatment technology and its optimisation, and the treatment plant design. The main idea of the systematic approach for oxidation process introduction consists of a search for the most effective combination between the chemical reaction and the treatment device, in which the reaction is supposed to take place. Under this strategy,a knowledge of the reaction pathways, its products, stoichiometry and kinetics is fundamental and, unfortunately, often unavailable from the preliminary knowledge. Therefore, research made in chemistry on novel treatment methods, comprisesnowadays a substantial part of the efforts. Chemical decomposition methods in the aqueous phase include oxidation by ozonation, ozone-associated methods (O3/H2O2, O3/UV, O3/TiO2), Fenton reagent (H2O2/Fe2+/3+) and photocatalytic oxidation (PCO). In the gaseous phase, PCO and catalytic hydrolysis over zero valent ironsare developed. The experimental studies within the described methodology involve aqueous phase oxidation of natural organic matter (NOM) of potable water, phenolic and aromatic amino compounds, ethylene glycol and its derivatives as de-icing agents, and oxygenated motor fuel additives ¿ methyl tert-butyl ether (MTBE) ¿ in leachates and polluted groundwater. Gas-phase chemical decomposition includes PCO of volatile organic compounds and dechlorination of chlorinated methane derivatives. The results of the research summarised here are presented in fifteenattachments (publications and papers submitted for publication and under preparation).

Efficient and cost-effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the efficiency and cost-effectiveness by reducing the necessary amount of experiments and data points measured. (C) 2003 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Efficient and accurate experimental design for enzyme kinetics: Bayesian studies reveal a systematic approach

In areas such as drug development, clinical diagnosis and biotechnology research, acquiring details about the kinetic parameters of enzymes is crucial. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. We demonstrate that a Bayesian approach (the use of prior knowledge) can produce major gains quantifiable in terms of information, productivity and accuracy of each experiment. Developing the use of Bayesian Utility functions, we have used a systematic method to identify the optimum experimental designs for a number of kinetic model data sets. This has enabled the identification of trends between kinetic model types, sets of design rules and the key conclusion that such designs should be based on some prior knowledge of K-M and/or the kinetic model. We suggest an optimal and iterative method for selecting features of the design such as the substrate range, number of measurements and choice of intermediate points. The final design collects data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. (C) 2003 Elsevier Science B.V. All rights reserved.

A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments

Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

A systematic approach to identify STRE-binding proteins of the gsn glycogen synthase gene promoter in Neurospora crassa

The gene encoding glycogen synthase in Neurospora crassa (gsn) is transcriptionally down-regulated when mycelium is exposed to a heat shock from 30 to 45 degrees C. The gsn promoter has one stress response element (STRE) motif that is specifically bound by heat shock activated nuclear proteins. In this work, we used biochemical approaches together with mass spectrometric analysis to identify the proteins that bind to the STRE motif and could participate in the gsn transcription regulation during heat shock. Crude nuclear extract of heat-shocked mycelium was prepared and fractionated by affinity chromatography. The fractions exhibiting DNA-binding activity were identified by electrophoretic mobility shift assay (EMSA) using as probe a DNA fragment containing the STRE motif DNA-protein binding activity was confirmed by Southwestern analysis. The molecular mass (MM) of proteins was estimated by fractionating the crude nuclear extract by SDS-PAGE followed by EMSA analysis of the proteins corresponding to different MM intervals. Binding activity was detected at the 30-50 MM kDa interval. Fractionation of the crude nuclear proteins by IEF followed by EMSA analysis led to the identification of two active fractions belonging to the pIs intervals 3.54-4.08 and 6.77-7.31. The proteins comprising the MM and pI intervals previously identified were excised from a 2-DE gel, and subjected to mass spectrometric analysis (MALDI-TOF/TOF) after tryptic digestion. The proteins were identified by search against the MIPS and MIT N. crassa databases and five promising candidates were identified. Their structural characteristics and putative roles in the gsn transcription regulation are discussed.

Straightforward systematic approach for fuel efficiency and emissions assessment in automotive systems

At this time, each major automotive market bares its own standards and test procedures to regulate the vehicle green house gases emissions and, thus, fuel consumption. Hence, much are the ways to evaluate the overall efficiency of motor vehicles. The majority of such standards rely on dynamometer cycle tests that appraise only the vehicle as a whole, but fail to assess emissions for each component or sub-system. Once the amount of work generated by the power source of an ICE vehicle to overcome the driving resistance forces is proportional to the energy contained in the required amount of fuel, the power path of the vehicle can be straightforwardly modeled as a set of mechanical systems, and each sub-system evaluated for its share on the total fuel consumption and green house gases emission. This procedure enables the estimation of efficiency gains on the system due to improvement of particular elements on the vehicle's driveline. In this work a simple systematic mechanical model of an arbitrary smallsized hatch back was assembled and total required energy calculated for different regulatory cycles. All the modeling details of the energy balance throughout the system are presented. Afterward, each subsystem was investigated for its role on the fuel consumption and the generated emission quantified. Furthermore, the application of the modeling technique for different sets of sub-systems was introduced. Copyright © 2011 SAE International.

Biochemical characterization of detergent-resistant membranes: a systematic approach

Lateral segregation of cholesterol- and sphingomyelin-rich rafts and glycerophospholipid-containing non-raft microdomains has been proposed to play a role in a variety of biological processes. The most compelling evidence for membrane segregation is based on the observation that extraction with non-ionic detergents leads to solubilization of a subset of membrane components only. However, one decade later, a large body of inconsistent detergent-extraction data is threatening the very concept of membrane segregation. We have assessed the validity of the existing paradigms and we show the following. (i) The localization of a membrane component within a particular fraction of a sucrose gradient cannot be taken as a yardstick for its solubility: a variable localization of the DRMs (detergent-resistant membranes) in sucrose gradients is the result of complex associations between the membrane skeleton and the lipid bilayer. (ii) DRMs of variable composition can be generated by using a single detergent, the increasing concentration of which gradually extracts one protein/lipid after another. Therefore any extraction pattern obtained by a single concentration experiment is bound to be 'investigator-specific'. It follows that comparison of DRMs obtained by different detergents in a single concentration experiment is prone to misinterpretations. (iii) Depletion of cholesterol has a graded effect on membrane solubility. (iv) Differences in detergent solubility of the members of the annexin protein family arise from their association with chemically different membrane compartments; however, these cannot be attributed to the 'brick-like' raft-building blocks of fixed size and chemical composition. Our findings demonstrate a need for critical re-evaluation of the accumulated detergent-extraction data.