Hierarchical control and optimisation of the Tennessee Eastman process

Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

A comparison of two identification and tracking methods for polar lows

In this study, we compare two different cyclone-tracking algorithms to detect North Atlantic polar lows, which are very intense mesoscale cyclones. Both approaches include spatial filtering, detection, tracking and constraints specific to polar lows. The first method uses digital bandpass-filtered mean sea level pressure (MSLP) fieldsin the spatial range of 200�600 km and is especially designed for polar lows. The second method also uses a bandpass filter but is based on the discrete cosine transforms (DCT) and can be applied to MSLP and vorticity fields. The latter was originally designed for cyclones in general and has been adapted to polar lows for this study. Both algorithms are applied to the same regional climate model output fields from October 1993 to September 1995 produced from dynamical downscaling of the NCEP/NCAR reanalysis data. Comparisons between these two methods show that different filters lead to different numbers and locations of tracks. The DCT is more precise in scale separation than the digital filter and the results of this study suggest that it is more suited for the bandpass filtering of MSLP fields. The detection and tracking parts also influence the numbers of tracks although less critically. After a selection process that applies criteria to identify tracks of potential polar lows, differences between both methods are still visible though the major systems are identified in both.

Real-time identification and modelling in pervasive mining

This paper introduces an architecture for identifying and modelling in real-time at a copper mine using new technologies as M2M and cloud computing with a server in the cloud and an Android client inside the mine. The proposed design brings up pervasive mining, a system with wider coverage, higher communication efficiency, better fault-tolerance, and anytime anywhere availability. This solution was designed for a plant inside the mine which cannot tolerate interruption and for which their identification in situ, in real time, is an essential part of the system to control aspects such as instability by adjusting their corresponding parameters without stopping the process.

Genes driving potato tuber initiation and growth: identification based on transcriptional changes using the POCI array

The increasing amount of available expressed gene sequence data makes whole-transcriptome analysis of certain crop species possible. Potato currently has the second largest number of publicly available expressed sequence tag (EST) sequences among the Solanaceae. Most of these ESTs, plus other proprietary sequences, were combined and used to generate a unigene assembly. The set of 246,182 sequences produced 46,345 unigenes, which were used to design a 44K 60-mer oligo array (Potato Oligo Chip Initiative: POCI). In this study, we attempt to identify genes controlling and driving the process of tuber initiation and growth by implementing large-scale transcriptional changes using the newly developed POCI array. Major gene expression profiles could be identified exhibiting differential expression at key developmental stages. These profiles were associated with functional roles in cell division and growth. A subset of genes involved in the regulation of the cell cycle, based on their Gene Ontology classification, exhibit a clear transient upregulation at tuber onset indicating increased cell division during these stages. The POCI array allows the study of potato gene expression on a much broader level than previously possible and will greatly enhance analysis of transcriptional control mechanisms in a wide range of potato research areas. POCI sequence and annotation data are publicly available through the POCI database (http://pgrc.ipk-gatersleben.de/poci).

Estimation of Gaussian process regression model using probability distance measures

A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Body-centric modelling, identification, and acceleration tracking control of a quadrotor UAV

This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

The identification of genes important in pseudomonas syringae pv. phaseolicola plant colonisation using in vitro screening of transposon libraries

The bacterial plant pathogen Pseudomonas syringae pv. phaseolicola (Pph) colonises the surface of common bean plants before moving into the interior of plant tissue, via wounds and stomata. In the intercellular spaces the pathogen proliferates in the apoplastic fluid and forms microcolonies (biofilms) around plant cells. If the pathogen can suppress the plant’s natural resistance response, it will cause halo blight disease. The process of resistance suppression is fairly well understood, but the mechanisms used by the pathogen in colonisation are less clear. We hypothesised that we could apply in vitro genetic screens to look for changes in motility, colony formation, and adhesion, which are proxies for infection, microcolony formation and cell adhesion. We made transposon (Tn) mutant libraries of Pph strains 1448A and 1302A and found 106/1920 mutants exhibited alterations in colony morphology, motility and biofilm formation. Identification of the insertion point of the Tn identified within the genome highlighted, as expected, a number of altered motility mutants bearing mutations in genes encoding various parts of the flagellum. Genes involved in nutrient biosynthesis, membrane associated proteins, and a number of conserved hypothetical protein (CHP) genes were also identified. A mutation of one CHP gene caused a positive increase in in planta bacterial growth. This rapid and inexpensive screening method allows the discovery of genes important for in vitro traits that can be correlated to roles in the plant interaction

AMP hydrolysis in soluble and microsomal rat cardiac cell fractions: kinetic characterization and molecular identification of 5 `-nucleotidase

The present study describes the enzymatic properties and molecular identification of 5`-nucleotidase in soluble and microsomal fractions from rat cardiac ventricles. Using AMP as a substrate, the results showed that the cation and the concentration required for maximal activity in the two fractions was magnesium at a final concentration of 1 mM. The pH optimum for both fractions was 9.5. The apparent K-m (Michaelis constant) values calculated from the Eadie-Hofstee plot were 59.7 +/- 10.4 mu M and 134.8 +/- 32.1 mu M, with V-max values of 6.7 +/- 0.4 and 143.8 +/- 23.8 nmol P-i/min/mg of protein (means +/- S.D., n = 4) from soluble and microsomal fractions respectively. Western blotting analysis of ecto-5`-nucleotidase revealed a 70 kDa protein in both fractions, with the major proportion present in the microsomal fraction. The presence of these enzymes in the heart probably has a physiological function in adenosine signalling. Furthermore, the presence of ecto-5`-nucleotidase in the microsomal fraction could have a role in the modulation of the excitation-contraction-coupling process through involvement of the Ca2+ influx into the sarcoplasmic reticulum. The measurement of maximal enzyme activities in the two fractions highlights the potential capacity of the different pathways of purine metabolism in the heart.

Use of PCR for detecting Aspergillus flavus in maize treated by gamma radiation process

The aim of this study was to verify the effects of gamma radiation process on the fungal DNA and the application of PCR in the detection of Aspergillus flavus in irradiated maize grains. The samples were inoculated with a toxigenic strain and incubated under controlled conditions of relative humidity, water activity, and temperature for 15 days. After incubation, the samples were treated with gamma radiation with doses of 5 and 10 kGy and individually analyzed. The use of PCR technique showed the presence of DNA bands of Aspergillus flavus in all irradiated samples that showed no fungal growth in agar medium.

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants. (C) 2008 Elsevier Inc. All rights reserved.

Identification of lift-off mechanism failure for salt drill-in drilling fluid containing polymer filter cake through adsorption/desorption studies

Drilling fluid`s contact with the productive zone of horizontal or complex wells can reduce well productivity by fluid invasion in the borehole wall. Salted drilling drill-in fluid containing polymers has often been applied in horizontal or complex petroleum wells in the poorly consolidated sandstone reservoirs of the Campos basin, Rio de Janeiro, Brazil. This fluid usually consists of natural polymers such as starch and xanthan gum, which are deposited as a filter cake on the wellbore wall during the drilling. Therefore, the identification of a lift-off mechanism failure, which can be detachment or blistering and pinholing, will enable formulation improvements. increasing the chances of success during filter cake removal in open hole operations. Likewise, knowledge of drill-in drilling fluid adsorption/desorption onto sand can help understand the filter cake-rock adhesion mechanism and consequently filter cake lift-off mechanism failures. The present study aimed to identify the lift-off failure mechanism for this type of fluid filter cake studying adsorption/desorption onto SiO(2) using solutions of natural polymers, lubricants, besides the fluid itself. Ellipsometry was employed to measure this process. The adsorption/desorption studies showed that the adsorbed layer of drilling fluid onto the walls of the rock pores is made up of clusters of polymers, linked by hydrogen bonds, which results in a force of lower cohesion compared to the electrostatic interaction between silica and polymers. Consequently, it was found that the most probable filter cake failure mechanism is rupture (blistering and pinholing), which results in the formation of ducts within the filter cake. (C) 2009 Elsevier B.V. All rights reserved.

Microwave-assisted digestion procedures for biological samples with diluted nitric acid: Identification of reaction products

Microwave-assisted sample preparation using diluted nitric acid solutions is an alternative procedure for digesting organic samples. The efficiency of this procedure depends on the chemical properties of the samples and in this work it was evaluated by the determination of crude protein amount. fat and original carbon. Soybeans grains, bovine blood. bovine muscle and bovine viscera were digested in a cavity-microwave oven using oxidant mixtures in different acid concentrations. The digestion efficiency was evaluated based on the determination of residual carbon content and element recoveries using inductively coupled plasma optical emission spectrometry (ICP OES). In order to determine the main residual organic compounds, the digests were characterized by nuclear magnetic resonance (1 H NMR). Subsequently, studies concerning separation of nitrobenzoic acid isomers were performed by ion pair reversed phase liquid chromatography using a C18 stationary phase, water:acetonitrile:methanol (75:20:5, v/v/v) +0.05% (v/v) TFA as mobile phase and ultraviolet detection at 254 nm. Sample preparation based on diluted acids proved to be feasible and a recommendable alternative for organic sample digestion, reducing both the reagent volumes and the variability of the residues as a result of the process of decomposition. It was shown that biological matt-ices containing amino acids, proteins and lipids in their composition produced nitrobenzoic acid isomers and other organic compounds after cleavage of chemical bonds. (C) 2009 Elsevier B.V. All rights reserved.

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

The role of venture capitalists in the identification and measurement of intangible assets

The increase in the importance of intangibles in business competitiveness has made investment selection more challenging to investors that, under high information asymmetry, tend to charge higher premiums to provide capital or simply deny it. Private Equity and Venture Capital (PE/VC) organizations developed contemporarily with the increase in the relevance of intangible assets in the economy. They form a specialized breed of financial intermediaries that are better prepared to deal with information asymmetry. This paper is the result of ten interviews with PE/VC organizations in Brazil. Its objective is to describe the selection process, criteria and indicators used by these organizations to identify and measure intangible assets, as well as the methods used to valuate prospective investments. Results show that PE/VC organizations rely on sophisticated methods to assess investment proposals, with specific criteria and indicators to assess the main classes of intangible assets. However, no value is given to these assets individually. The information gathered is used to understand the sources of cash flows and risks, which are then combined by discounted cash flow methods to estimate firm's value. Due to PE/VC organizations extensive experience with innovative Small and Medium-sized Enterprises (SMEs), we believe that shedding light on how PE/VC organizations deal with intangible assets brings important insights to the intangible assets debate.