Low cost,microprocessor-based system for flow evaluation in a hydraulic model using the dilution method

An Automatic Dye Dilution Processor (ADP) based on a microprocessor is applied to a hydraulic model to process on-line dilution curves, using saline or thermodilution methods. A low cost, F8 microcomputer with minimum parts configuration was used in an Automatic Dilution Processor (ADP) system. Software allows an operator to select methods, amount of indicator to be injected, cell calibration constant, and temperature step. Care has been taken in the curve data processing, to avoid errors when recirculation occurs. The system is used, together with an open hydraulic model, for flow measurement demonstration, and the estimation of cell calibration constant.     

Fermentation fault management and on-line state estimation using methods of cluster analysis

The results of the cluster analysis of fermentation data are used for the supervision and on-line state estimation. The results of the classification are presented as the average over all fermentation runs belonging to the class as well as the standard deviation. With the help of the class information the on-line fermentation is associated with the best suiting class. Faults in the data such as spikes or total failure of the sensors are detected as the class information automatically supplies tolerance regions for the measurements. In case of a fault a reliable extrapolation for the time of the fault can be calculated. The approach is implemented in the real-time expert system tool G2 and is applied to data of the carbon dioxide evolution rate (CER) of an industrial antibiotic fermentation process.     

On-line estimation of mycelial cell mass concentrations with a computer-interfaced filtration probe

This article deals with the design and operation of a filtration probe for estimating cell concentrations in fermentations involving mycelial organisms such as Penicillium chrysogenum. This device, a much improved version of one developed previously, is placed directly into the fermentor and measures the filtration properties of the fermentation broth, which are correlated to the cell concentration. The probe is connected to a computer system which enables on-line estimation of the cell concentration. Fiber-optic light guides are used in combination with a pair of light sources and receivers to detect the relative position of the filter-cake-fermentation-broth interface. The lower sensor in the filtration tube enables reliable estimation of cell mass upto about 20 g/L (dry wt), while the upper sensor yields useful measurement of the filtration properties upto a concentration of about 40 g/L (dry wt) and appears to have the potential to go even higher. Major advantages of this probe system are the ease of measurement and the on-line ability to measure very frequently, due to its nondestructive mode of operation. Thus, the probe obviates the need for manual sampling and reduces the risk of contaminating the culture. But, more significantly, it enables one to implement on-line schemes including feedback control.     

刺五加经济产量估测的数学模型

一、前言生物生产量的研究是60年代以来,生态学中一个崭新的领域,随着生产的发展和对自然资源开发利用的需要,愈来愈引起人们的注意,并成为当代生物学研究的中心问题之一。这类研究是以有机物的重量或能量(即生物量和生产力)为指标,研究各生态系统中物质与能量的数量及其固定、消耗、分配、积累与转化的特点,并探讨其与生态因素     

On-line monitoring of hybridoma cell growth using a laser turbidity sensor

A high-sensitivity turbidity probe was used for on-line monitoring of the cell concentration in batch hybridoma cultivation. Good correlation between off-line cell counts and the linearized sensor signal was found. The quality of the signal was sufficiently high to provide for on-line estimation of the specific growth rate using an efficient filtering procedure. These positive results suggest that such laser turbidity sensors will facilitate development of systems for on-line monitoring and control of animal cell cultivations. (c) 1992 John Wiley & Sons, Inc.     

On-line biomass estimation in biosurfactant production process by <Emphasis Type="Italic">Candida lipolytica</Emphasis> UCP 988

Biomass is an important variable in biosurfactant production process. However, such bioprocess variable, usually, is collected by sampling and determined by off-line analysis, with significant time delay. Therefore, simple and reliable on-line biomass estimation procedures are highly desirable. An artificial neural network model (ANN) is presented for the on-line estimation of biomass concentration, in biosurfactant production by Candida lipolytica UCP 988, as a nonlinear function of pH and dissolved oxygen. Several configurations were evaluated while developing the optimal ANN model. The optimal ANN model consists of one hidden layer with four neurons. The performance of the ANN was checked using experimental data. The results obtained indicate a very good predictive capacity for the ANN-based software sensor with values of R2 of 0.969 and RMSE of 0.021 for biomass concentration. Estimated biomass using the ANN was proved to be a simple, robust and accurate method.     

Note on the estimation of the correlation function of neural spike trains

The use of time-bins in the estimation of the correlation function of neural spike trains has a filtering effect on the estimate and results in distortion and aliasing. Prior low-pass filtering of the spike trains, on the other hand, and computation of the correlation function of the emerging waveforms in the standard way result in an estimate that is also a filtered version of the original function but distortion- and alias-free. In addition, the correlation function so computed can be normalized. An analogous definition of the correlation coefficient for the first technique enables the comparison of these various correlation estimates and clarifies their properties.     

Electronic nose for estimation of product concentration in mammalian cell cultivation

The off-gas composition from perfusion cultivation of a CHO-cell line producing recombinant human blood coagulation Factor VIII is monitored with an electronic nose. It is shown that the electronic nose in combination with an artificial neural network can be used for on-line estimation of the Factor VIII concentration in production-scale cultivations. The obtained prediction error (1†) for the Factor VIII concentration was 1.1 IU/ml. The potential of the electronic nose for estimation of viable cell count is outlined in laboratory-scale Factor VIII cultivations. The obtained prediction error (1†) for the viable cell count was 0.4᎒⁶ cells/ml. The results show that this non-invasive method is potentially useful for on-line bioprocess monitoring.     

On-line measurements of culture fluorescence: Method and application

Summary In this paper a new probe allowing the measurement of NAD(P)H-dependent culture fluorescence in a bioreactor is presented. This sterilizable probe can be inserted in every bioreactor using a standard fitting of 25 mm. Under well defined conditions high specificity and sensitivity as well as high stability are further advantages of this probe. Application examples are given to demonstrate the operation possibilities of this fluorescence probe. In batch growth the culture fluorescence can be used for on-line estimation of biomass concentration. Metabolic alterations due to substrate of oxygen deficiency can easily be detected by fluorometric measurements. In kinetic studies the fluorescence probe is of great use because of a very small time delay.     

On-line monitoring of yeast cell growth by impedance spectroscopy

The application of impedance spectroscopy to estimate on-line cell concentration was studied. The estimation was based on the relative variation between electrical impedance measured at low (10 kHz) and high frequencies (10 MHz). Studies were carried out to characterise the influence of changes in physical and chemical parameters on the impedance measurement. Two different possibilities to perform on-line measurements were tested: a simple set-up, based on an in situ probe, gave good results but was not suitable for high agitation and aeration rates. An ex situ flow-through on-line measuring cell was used to overcome these problems, showing a better performance. The use of this set-up for the growth monitorisation of a Saccharomyces cerevisiae culture showed an efficient performance, having the correlation between estimated and measured S. cerevisiae a Pearson coefficient of 0.999.     

State and parameter estimation of microalgal photobioreactor cultures based on local irradiance measurement

Local photosynthetic photon flux fluence rate (PPFFR) determined by a submersible 4pi quantum micro-sensor was used in developing a versatile on-line state estimator for stirred-tank microalgal photobioreactor cultures. A marine micro-alga Dunaliella salina was used as a model organism in this study. On-line state estimation was realized using the extended Kalman filter (EKF), based on a state model of the photobioreactor and on-line local PPFFR measurement. The dynamic state model for the photobioreactor was derived based on mass-balance equations of the relevant states. The measurement equation was established based on an empirical correlation between the microalgal biomass concentration and the local PPFFR measured at a fixed point inside the photobioreactor. An internal model approach was used to estimate the specific growth rate without the need of state-based kinetic expression. The estimator was proven to be capable of estimating biomass concentration and specific growth rate, as well as phosphate and dissolved oxygen concentrations in a photobioreactor illuminated with either fixed or time-varying incident radiation. The quantum sensor was shown to be robust and able to quickly respond to dynamic changes in local PPFFR. In addition, the quantum sensor outputs were not affected by bubble aeration or agitation within the typical operating range. The strong filtering capacity of EKF gives the state estimator superior performance compared to direct calculation from the empirical biomass/local PPFFR correlation. This state estimation system makes use of inexpensive and reliable sensor hardware to report key process dynamics of microalgal photobioreactor cultures on-line, enabling improved operation of such a process.     

An algorithmic approach to constructing the on-line estimation system for the specific growth rate

The objective of this article is to propose an algorithm for the on-line estimation of the specific growth rate in a batch or a fed-batch fermentation process. The algorithm shows the practical procedure for the estimation method utilizing the macroscopic balance and the extended Kalman filter. A number of studies of the on line estimation have been presented. However, there are few studies discussing about the selection of the observed variables and for the tuning of some parameters of the extended Kalman filter, such as covariance matrix and initial values of the state.The beginning of this article is devoted to explain the selection of the observed variable. This information is very important in terms of the practical know-how for using technique. It is discovered that the condition number is a practically useful and valid criterion for number is a practically useful and valid criterion for choosing the variable to be observed.Next, when the extended Kalman filter in applied to the online estimation of the specific growth rate, which is directly unmeasurable, criteria for judging the validity of the estimated value from the observed data are proposed. Based on the proposed criterial, the system equation of the specific growth rate is selected and initial value of the state variable and covariance matrix of the system noises are adjusted. From many experiments, it is certified that the specific growth rate in the batch or fed -batch fermentation can be estimated accurately by means of the algorithm proposed here. In these experiments, that is, when the cell concentration is measured directly, the extended Kalman filter using the convariance matrix with a constant element can estimate more accurately values of the specific growth rate than the adaptive extended Kalman filter does.     

Regression analyses and motile sperm subpopulation structure study as improving tools in boar semen quality analysis

A precise estimation of the fertilizing ability of a boar ejaculate would be very useful to improve pig assisted reproduction results. For this purpose, we tested the mathematical combination of several parameters of the boar semen quality analysis, including the computer-assisted semen motility analysis (CASA), as a predictive fertility tool. The utilized mathematical relations among parameters were logistic and linear regressions. Two mathematical models obtained by logistic regression involving Osmotic Resistance Test (ORT Test), Hyperosmotic Resistance Test (HRT Test) and viability of fresh samples, showed a significant (P<0.05) correlation between semen characteristics and conception rate. However, none of the obtained models produced a significant correlation model between semen characteristics and prolificacy. The CASA analyses show that three separate subpopulations of spermatozoa with different motility characteristics coexist in boar ejaculates. There were significant (P<0.001) differences in the distribution of these subpopulations among boars, but no clear relationship between motile subpopulation structure and fertility was obtained. Our results support the belief that the predictive use of the results obtained in a standard boar semen quality analysis can reasonably be achieved by applying logistic correlation analyses among several function parameters of boar semen quality analysis and in vivo conception rates obtained after artificial insemination (AI).     

Numerical methods for estimating iron requirements from population data

The estimation of iron requirements is crucial for nutrition and food policy. The traditional methods for estimating iron requirements are balance methods based on iron intakes and excretions and factorial methods based on estimated iron absorption rates and estimated iron losses from body compartments. As an alternative, numerical methods for estimating iron requirements from population data of iron status were developed. The iron status data reported by Satoh (1991) were used in the sixth edition of Recommended Dietary Allowances for Japanese. The menstrual iron losses in Japanese premenopausal women were estimated from the literature to calculate total iron losses as the sum of basal iron losses and menstrual iron losses. The use of this alternative method is illustrated by analyzing the same population data comprising the prevalence of iron deficiency and the distribution of iron intake. The estimated average requirements were affected by the form of distribution function, the relative standard deviation of requirements, and the correlation coefficient between iron intakes and requirements. We conclude that numerical methods can be very useful for estimating iron requirements and to elucidate dietary recommendations of iron. These methods may contribute to determining requirements of other nutrients as well as iron.     

Discrete Delta Estimation of the Variance of the Logistic Scores Estimator of ED50

A discrete delta method is applied to estimation of the standard error of the logistic scores estimator of ED50 in quantal bioassay. Results of a simulation study suggest that the standard error estimator is useful for assessing the precision of the ED50 estimate and for interval estimation of ED50.     

On the use of the variogram in checking for independence in spatial data

The variogram is a standard tool in the analysis of spatial data, and its shape provides useful information on the form of spatial correlation that may be present. However, it is also useful to be able to assess the evidence for the presence of any spatial correlation. A method of doing this, based on an assessment of whether the true function underlying the variogram is constant, is proposed. Nonparametric smoothing of the squared differences of the observed variables, on a suitably transformed scale, is used to estimate variogram shape. A statistic based on a ratio of quadratic forms is proposed and the test is constructed by investigating the distributional properties of this statistic under the assumption of an independent Gaussian process. The power of the test is investigated. Reference bands are proposed as a graphical follow-up. An example is discussed.     

An in situ probe for on-line monitoring of cell density and viability on the basis of dark field microscopy in conjunction with image processing and supervised machine learning

Fermentation industries would benefit from on-line monitoring of important parameters describing cell growth such as cell density and viability during fermentation processes. For this purpose, an in situ probe has been developed, which utilizes a dark field illumination unit to obtain high contrast images with an integrated CCD camera. To test the probe, brewer's yeast Saccharomyces cerevisiae is chosen as the target microorganism. Images of the yeast cells in the bioreactors are captured, processed, and analyzed automatically by means of mechatronics, image processing, and machine learning. Two support vector machine based classifiers are used for separating cells from background, and for distinguishing live from dead cells afterwards. The evaluation of the in situ experiments showed strong correlation between results obtained by the probe and those by widely accepted standard methods. Thus, the in situ probe has been proved to be a feasible device for on-line monitoring of both cell density and viability with high accuracy and stability.     

Estimators of repeatability

Summary Analysis of variance and principal components methods have been suggested for estimating repeatability. In this study, six estimation procedures are compared: ANOVA, principal components based on the sample covariance matrix and also on the sample correlation matrix, a related multivariate method (structural analysis) based on the sample covariance matrix and also on the sample correlation matrix, and maximum likelihood estimation. A simulation study indicates that when the standard linear model assumptions are met, the estimators are quite similar except when the repeatability is small. Overall, maximum likelihood appears the preferred method. If the assumption of equal variance is relaxed, the methods based on the sample correlation matrix perform better although others are surprisingly robust. The structural analysis method (with sample correlation matrix) appears to be best.Paper number 776 from the Department of Meat and Animal Science, University of Wisconsin-Madison.     

On-line estimation of the biomass activity during animal-cell cultivations

A software sensor was developed to determine the volumetric biomass activity of animal cell cultivations on-line. It was based on the on-line estimation of the ATP-production rate from the oxygen uptake and the lactic-acid production rate. The sensor was verified for a batch culture of Vero cells, and a batch and a continuous culture of hybridoma cells. For the hybridoma cells, the sensor showed a good correlation with the biomass concentration. However, this was not the case for the Vero cells. As soon as glutamine was exhausted, the biomass activity stabilized, whereas the amount of biomass almost doubled. Because the sensor developed responds to nutrient limitations much faster than becomes visible through cell density measurements, and because the volumetric biomass activity can be related to the volumetric consumption rates and production rates of important metabolites, it shows excellent possibilities for control purposes. (c) 1996 John Wiley & Sons, Inc.     

Monitoring a complex medium fermentation with sample-sample two-dimensional FT-NIR correlation spectroscopy

The possibility of monitoring state transitions during the time course of a fermentation through the analysis of the on-line collected near-infrared (NIR) spectra with sample-sample two-dimensional correlation spectroscopy (SS-2DCoS) was investigated. SS-2DCoS has proved to be useful for extracting process information directly from the spectra collected on-line. The complexity of the system studied prevented the extraction of concentration profiles, but nevertheless, the application of SS-2DCoS enables the identification of fermentation state transitions due to metabolic and morphological changes of the microorganism.