Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.

Prediction of carbon monoxide in fires by conditional moment closure

Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.

Model-based procedure for scale-up of wet, overflow ball mills - Part II: Worked example

A new ball mill scale-up procedure is developed which uses laboratory data to predict the performance of MI-scale ball mill circuits. This procedure contains two laboratory tests. These laboratory tests give the data for the determination of the parameters of a ball mill model. A set of scale-up criteria then scales-up these parameters. The procedure uses the scaled-up parameters to simulate the steady state performance of the full-scale mill circuit. At the end of the simulation, the scale-up procedure gives the size distribution, the volumetric flowrate and the mass flowrate of all the streams in the circuit, and the mill power draw. A worked example shows how the new ball mill scale-up procedure is executed. This worked example uses laboratory data to predict the performance of a full-scale re-grind mill circuit. This circuit consists of a ball mill in closed circuit with hydrocyclones. The MI-scale ball mill has a diameter (inside liners) of 1.85m. The scale-up procedure shows that the full-scale circuit produces a product (hydrocyclone overflow) that has an 80% passing size of 80 mum. The circuit has a recirculating load of 173%. The calculated power draw of the full-scale mill is 92kW (C) 2001 Elsevier Science Ltd. All rights reserved.

Settling velocity of sediments at high concentrations

New data on the settling velocity of artificial sediments and natural sands at high concentrations are presented. The data are compared with a widely used semiempirical Richardson and Zaki equation (Trans. Inst. Chem. Eng. 32 (1954) 35), which gives an accurate measure of the reduction in velocity as a function of concentration and an experimentally determined empirical power n. Here, a simple method of determining n is presented using standard equations for the clear water settling velocity and the seepage flow within fixed sediment beds. The resulting values for n are compared against values derived from new and existing laboratory data for beach and filter sands. For sands, the appropriate values of n are found to differ significantly from those suggested by Richardson and Zaki for spheres, and are typically larger, corresponding to a greater reduction in settling velocity at high concentrations. For fine and medium sands at concentrations of order 0.4, the hindered settling velocity reduces to about 70% of that expected using values of n derived for spheres. At concentrations of order 0.15, the hindered settling velocity reduces to less than half of the settling velocity in clear water. These reduced settling velocities have important implications for sediment transport modelling close to, and within, sheet flow layers and in the swash zone.

Swash overtopping and sediment overwash on a truncated beach

New experimental laboratory data are presented on swash overtopping and sediment overwash on a truncated beach, approximating the conditions at the crest of a beach berm or inter-tidal ridge-runnel. The experiments provide a measure of the uprush sediment transport rate in the swash zone that is unaffected by the difficulties inherent in deploying instrumentation or sediment trapping techniques at laboratory scale. Overtopping flow volumes are compared with an analytical solution for swash flows as well as a simple numerical model, both of which are restricted to individual swash events. The analytical solution underestimates the overtopping volume by an order of magnitude while the model provides good overall agreement with the data and the reason for this difference is discussed. Modelled flow velocities are input to simple sediment transport formulae appropriate to the swash zone in order to predict the overwash sediment transport rates. Calculations performed with traditional expressions for the wave friction factor tend to underestimate the measured transport. Additional sediment transport calculations using standard total load equations are used to derive an optimum constant wave friction factor of f(w)=0.024. This is in good agreement with a broad range of published field and laboratory data. However, the influence of long waves and irregular wave run-up on the overtopping and overwash remains to be assessed. The good agreement between modelled and measured sediment transport rates suggests that the model provides accurate predictions of the uprush sediment transport rates in the swash zone, which has application in predicting the growth and height of beach berms. (c) 2005 Elsevier B.V. All rights reserved.

Application of a coupled ground-surface water flow model to simulate periodic groundwater flow influenced by a sloping boundary, capillarity and vertical flows

Theoretical developments as well as field and laboratory data have shown the influence of the capillary fringe on water table fluctuations to increase with the fluctuation frequency. The numerical solution of a full, partially saturated flow equation can be computationally expensive. In this paper, the influence of the capillary fringe on water table fluctuations is simplified through its parameterisation into the storage coefficient of a fully-saturated groundwater flow model using the complex effective porosity concept [Nielsen, P., Perrochet, P., 2000. Water table dynamics under capillary fringes: experiments and modelling. Advances in Water Resources 23 (1), 503-515; Nielsen, P., Perrochet, P., 2000. ERRATA: water table dynamics under capillary fringes: experiments and modelling (Advances in Water Resources 23 (2000) 503-515). Advances in Water Resources 23, 907-908]. The model is applied to sand flume observations of periodic water table fluctuations induced by simple harmonic forcing across a sloping boundary, analogous to many beach groundwater systems. While not providing information on the moisture distribution within the aquifer, this approach can reasonably predict the water table fluctuations in response to periodic forcing across a sloping boundary. Furthermore, he coupled ground-surface water model accurately predicts the extent of the seepage face formed at the sloping boundary. (C) 2005 Elsevier Ltd. All rights reserved.

Long wave generation by the shoaling and breaking of transient wave groups on a beach

This paper presents new laboratory data on the generation of long waves by the shoaling and breaking of transient-focused short-wave groups. Direct offshore radiation of long waves from the breakpoint is shown experimentally for the first time. High spatial resolution enables identification of the relationship between the spatial gradients of the short-wave envelope and the long-wave surface. This relationship is consistent with radiation stress theory even well inside the surf zone and appears as a result of the strong nonlinear forcing associated with the transient group. In shallow water, the change in depth across the group leads to asymmetry in the forcing which generates significant dynamic setup in front of the group during shoaling. Strong amplification of the incident dynamic setup occurs after short-wave breaking. The data show the radiation of a transient long wave dominated by a pulse of positive elevation, preceded and followed by weaker trailing waves with negative elevation. The instantaneous cross-shore structure of the long wave shows the mechanics of the reflection process and the formation of a transient node in the inner surf zone. The wave run-up and relative amplitude of the radiated and incident long waves suggests significant modification of the incident bound wave in the inner surf zone and, the dominance of long waves generated by the breaking process. It is proposed that these conditions occur when the primary short waves and bound wave are not shallow water waves at the breakpoint. A simple criterion is given to determine these conditions, which generally occur for the important case of storm waves.

Baseline laboratory bioassay data for spinosad against populations of Australian sheep blowfly, Lucilia cuprina (Wiedemann) (Diptera : Calliphoridae)

Spinosad was an effective larvicide against the Australian sheep blowfly, Lucilia cuprina. A survey of 41 field populations indicated no cross-resistance to spinosad from existing organophosphate resistance. The data presented serve as baseline data for future resistance surveys.

Knowledge discovery and data mining in biological databases

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Cytokine-related genes identified from the RIKEN full-length mouse cDNA data set

To identify novel cytokine-related genes, we searched the set of 60,770 annotated RIKEN mouse cDNA clones (FANTOM2 clones), using keywords such as cytokine itself or cytokine names (such as interferon, interleukin, epidermal growth factor, fibroblast growth factor, and transforming growth factor). This search produced 108 known cytokines and cytokine-related products such as cytokine receptors, cytokine-associated genes, or their products (enhancers, accessory proteins, cytokine-induced genes). We found 15 clusters of FANTOM2 clones that are candidates for novel cytokine-related genes. These encoded products with strong sequence similarity to guanylate-binding protein (GBP-5), interleukin-1 receptor-associated kinase 2 (IRAK-2), interleukin 20 receptor alpha isoform 3, a member of the interferon-inducible proteins of the Ifi 200 cluster, four members of the membrane-associated family 1-8 of interferon-inducible proteins, one p27-like protein, and a hypothetical protein containing a Toll/Interleukin receptor domain. All four clones representing novel candidates of gene products from the family contain a novel highly conserved cross-species domain. Clones similar to growth factor-related products included transforming growth factor beta-inducible early growth response protein 2 (TIEG-2), TGFbeta-induced factor 2, integrin beta-like 1, latent TGF-binding protein 4S, and FGF receptor 4B. We performed a detailed sequence analysis of the candidate novel genes to elucidate their likely functional properties.

Identification of novel "pathologs" (human disease-related gene candidates) from the RIKEN full-length mouse cDNA data set

The majority of common diseases such as cancer, allergy, diabetes, or heart disease are characterized by complex genetic traits, in which genetic and environmental components contribute to disease susceptibility. Our knowledge of the genetic factors underlying most of such diseases is limited. A major goal in the post-genomic era is to identify and characterize disease susceptibility genes and to use this knowledge for disease treatment and prevention. More than 500 genes are conserved across the invertebrate and vertebrate genomes. Because of gene conservation, various organisms including yeast, fruitfly, zebrafish, rat, and mouse have been used as genetic models.

Population pharmacokinetics of perhexiline from very sparse, routine monitoring data

Using NONMEM, the population pharmacokinetics of perhexiline were studied in 88 patients (34 F, 54 M) who were being treated for refractory angina. Their mean +/- SD (range) age was 75 +/- 9.9 years (46-92), and the length of perhexiline treatment was 56 +/- 77 weeks (0.3-416). The sampling time after a dose was 14.1 +/- 21.4 hours (0.5-200), and the perhexiline plasma concentrations were 0.39 +/- 0.32 mg/L (0.03-1.56). A one-compartment model with first-order absorption was fitted to the data using the first-order (FO) approximation. The best model contained 2 subpopulations (obtained via the $MIXTURE subroutine) of 77 subjects (subgroup A) and 11 subjects (subgroup B) that had typical values for clearance (CL/F) of 21.8 L/h and 2.06 L/h, respectively. The volumes of distribution (V/F) were 1470 L and 260 L, respectively, which suggested a reduction in presystemic metabolism in subgroup B. The interindividual variability (CV%) was modeled logarithmically and for CL/F ranged from 69.1% (subgroup A) to 86.3% (subgroup B). The interindividual variability in V/F was 111%. The residual variability unexplained by the population model was 28.2%. These results confirm and extend the existing pharmacokinetic data on perhexiline, especially the bimodal distribution of CL/F manifested via an inherited deficiency in hepatic and extrahepatic CYP2D6 activity.

Zygosity Diagnosis in the Absence of Genotypic Data: An Approach Using Latent Class Analysis

For zygosity diagnosis in the absence of genotypic data, or in the recruitment phase of a twin study where only single twins from same-sex pairs are being screened, or to provide a test for sample duplication leading to the false identification of a dizygotic pair as monozygotic, the appropriate analysis of respondents' answers to questions about zygosity is critical. Using data from a young adult Australian twin cohort (N = 2094 complete pairs and 519 singleton twins from same-sex pairs with complete responses to all zygosity items), we show that application of latent class analysis (LCA), fitting a 2-class model, yields results that show good concordance with traditional methods of zygosity diagnosis, but with certain important advantages. These include the ability, in many cases, to assign zygosity with specified probability on the basis of responses of a single informant (advantageous when one zygosity type is being oversampled); and the ability to quantify the probability of misassignment of zygosity, allowing prioritization of cases for genotyping as well as identification of cases of probable laboratory error. Out of 242 twins (from 121 like-sex pairs) where genotypic data were available for zygosity confirmation, only a single case was identified of incorrect zygosity assignment by the latent class algorithm. Zygosity assignment for that single case was identified by the LCA as uncertain (probability of being a monozygotic twin only 76%), and the co-twin's responses clearly identified the pair as dizygotic (probability of being dizygotic 100%). In the absence of genotypic data, or as a safeguard against sample duplication, application of LCA for zygosity assignment or confirmation is strongly recommended.

Reproducibility of a laboratory-based 40-km cycle time-trial on a stationary wind-trainer in highly trained cyclists

The purpose of the present study was to examine the reproducibility of laboratory-based 40-km cycle time-trial performance on a stationary wind-trainer. Each week, for three consecutive weeks, and on different days, forty-three highly trained male cyclists ((x) over bar +/- SD; age = 25 +/- 6 y; mass = 75 +/- 7 kg; peak oxygen uptake [(V) over dot O-2 peak] = 64.8 +/- 5.2 ml x kg(-1) x min(-1)) performed: 1) a (V) over dot O-2 peak test, and 2) a 40-km time-trial on their own racing bicycle mounted to a stationary wind-trainer (Cateye - Cyclosimulator). Data from all tests were compared using a one-way analysis of variance. Performance on the second and third 40-km time-trials were highly related (r = 0.96; p < 0.001), not significantly different (57:21 +/- 2:57 vs. 57:12 +/- 3:14 min:s), and displayed a low coefficient of variation (CV) = 0.9 +/- 0.7%. Although the first 40-km time-trial (58:43 +/- 3:17min:s) was not significantly different from the second and third tests (p = 0.06), inclusion of the first test in the assessment of reliability increased within-subject CV to 3.0 +/- 2.9%. 40-km time-trial speed (km x h(-1)) was significantly (p < 0.001) related to peak power output (W; r = 0.75), (V) over dot O-2 peak (1 x min(-1); r = 0.53), and the second ventilatory turnpoint (1 x min(-1); r = 0.68) measured during the progressive exercise tests. These data demonstrate that the assessment of 40-km cycle time-trial performance in well-trained endurance cyclists on a stationary wind-trainer is reproducible, provided the athletes perform a familiarization trial.

Exploration of the cell-cycle genes found within the RIKEN FANTOM2 data set

The cell cycle is one of the most fundamental processes within a cell. Phase-dependent expression and cell-cycle checkpoints require a high level of control. A large number of genes with varying functions and modes of action are responsible for this biology. In a targeted exploration of the FANTOM2-Variable Protein Set, a number of mouse homologs to known cell-cycle regulators as well as novel members of cell-cycle families were identified. Focusing on two prototype cell-cycle families, the cyclins and the NIMA-related kinases (NEKs), we believe we have identified all of the mouse members of these families, 24 cyclins and 10 NEKs, and mapped them to ENSEMBL transcripts. To attempt to globally identify all potential cell cycle-related genes within mouse, the MGI (Mouse Genome Database) assignments for the RIKEN Representative Set (RPS) and the results from two homology-based queries were merged. We identified 1415 genes with possible cell-cycle roles, and 1758 potential paralogs. We comment on the genes identified in this screen and evaluate the merits of each approach.