Direct analysis of blood serum by total reflection X-ray fluorescence spectrometry and application of an artificial neural network approach for cancer diagnosis

Iron, copper, zinc and selenium were determined directly in serum samples from healthy individuals (n=33) and cancer patients (n=27) by total reflection X-ray fluorescence spectrometry using the Compton peak as internal standard [L.M. Marcó P. et al., Spectrochim. Acta Part B 54 (1999) 1469–1480]. The standardized concentrations of these elements were used as input data for two-layer artificial neural networks trained with the generalized delta rule in order to classify such individuals according to their health status. Various artificial neural networks, comprising a linear function in the input layer, a hyperbolic tangent function in the hidden layer and a sigmoid function in the output layer, were evaluated for such a purpose. Of the networks studied, the (4:4:1) gave the highest estimation (98%) and prediction rates (94%). The latter demonstrates the potential of the total reflection X-ray fluorescence spectrometry/artificial neural network approach in clinical chemistry.     

Semicontinuous GC analysis and receptor modelling for source apportionment of ozone precursor hydrocarbons in Bresso, Milan, 2003

The European Ozone Directive 2002/3/EC specifies the analysis of 30 individual C2-C9 hydrocarbons in urban air with the attribution of emission sources to pollution concentrations as a major objective. In the present study, we investigate an approach for source apportionment of these ozone precursor hydrocarbons in urban air based on reliable semi continuous volatile organic compound (VOC) analysis in the field and in vehicle emission laboratory combined with multivariate receptor modeling. The GC system relies on an hourly analytical cycle based on a trap sample enrichment phase followed by a dual column gas chromatographic flame ionisation detector (FID) analysis and has successfully been tested during an air monitoring campaign at an urban site (Milan, Italy, September 2003) and in the vehicle laboratory performing exhaust emission measurements while running driving cycles on a chassis dynamometer (mopeds, gasoline and diesel cars). The receptor modeling relies on two complementary principles. The chemical mass balance (CMB) modeling apportions well characterized source profiles for the 30 individual C2-C9 hydrocarbons in the Ozone Directive to the concentrations in ambient air and produces source contribution estimates (SCE) as output. The positive matrix factorization (PMF) analyses variability in the ambient air concentration data and searches for latent variables consisting of co-varying hydrocarbons and produces profiles as output, which in this study could be attributed to known emission sources. Both CMB and PMF rely on an estimated uncertainty for each input data. A new approach is presented, by which the uncertainty is allowed to float as function of the photochemical reactivity of the atmosphere and the stability of each individual compound.     

Photocatalytic Degradation of Oxytetracycline in Aqueous Solutions with TiO2 in Suspension and Prediction by Artificial Neural Networks

In this study, the photocatalytic degradation of oxytetracycline (OTC) in aqueous solutions has been studied under different conditions such as initial pollutant concentrations, amount of catalyst, and pH of the solution. Experimental results showed that photocatalysis was clearly the predominant process in the pollutant degradation, since OTC adsorption on the catalyst and photolysis are negligible. The optimal TiO₂ concentration for OTC degradation was found to be 1.0 g/L. The apparent rate constant decreased, and the initial degradation rate increased with increasing initial OTC concentration with the other parameters kept unchanged. Subsequently, data obtained from photocatalytic degradation were used for training the artificial neural networks (ANN). The Levenberg–Marquardt algorithm, log sigmoid function in the hidden layer, and the linear activation function in the output layer were used. The optimized ANN structure was four neurons at the input layer, eighteen neurons at the hidden layer, and one neuron at the output layer. The application of 18 hidden neurons allowed to obtain the best values for R² and the mean squared error, 0.99751 and 7.504e–04, respectively, showing the relevance of the training, and hence the network can be used for final prediction of photocatalytic degradation of OTC with suspended TiO₂.     

Diagram,a drawing program for logarithmic concentration/pH plots

DIAGRAM provides graphic display of acid-base equilibria based on logarithmic concentrations of the species involved. Various subroutines facilitate calculation of α and concentration values of the different species in a system and successive protonations can be superimposed on the output.     

A comparative study of laser induced breakdown spectroscopy analysis for element concentrations in aluminum alloy using artificial neural networks and calibration methods

A comparative study of analysis methods (traditional calibration method and artificial neural networks (ANN) prediction method) for laser induced breakdown spectroscopy (LIBS) data of different Al alloy samples was performed. In the calibration method, the intensity of the analyte lines obtained from different samples are plotted against their concentration to form calibration curves for different elements from which the concentrations of unknown elements were deduced by comparing its LIBS signal with the calibration curves. Using ANN, an artificial neural network model is trained with a set of input data of known composition samples. The trained neural network is then used to predict the elemental concentration from the test spectra. The present results reveal that artificial neural networks are capable of predicting values better than traditional method in most cases.     

Estimation of uncertainty in electrochemical amperometric measurement of dissolved oxygen concentration

A procedure for the estimation of measurement uncertainty of dissolved oxygen (DO) concentration measurement based on the ISO approach is presented. It is based on a mathematical model that involves 14 input parameters. The uncertainty of DO concentration strongly depends on changes in experimental details (temperature difference between calibration and measurement, the time interval between calibration and measurement, etc.). The relative measurement uncertainty is, however, practically independent of the DO concentration itself. The uncertainty is the lowest if the calibration and the measurement are done at the same temperature and on the same day. A calculation tool is provided (in the form of a GUM Workbench file) for practitioners that can be used for uncertainty calculation of DO concentrations at very different experimental conditions.Electronic Supplementary Material The uncertainty calculation example is available as a GUM Workbench calculation file C_O2_meas.smu (GUM Workbench ver. 1.3.3, Metrodata GmbH) together with its data file Input_values.xls (MS Excel 97). For those users who do not have GUM Workbench, the full report of the GUM Workbench calculation is available as a PDF file C_O2_meas.pdf. This material is available via the Internet at .     

Calculation of equilibrium constants from multiwavelength spectroscopic data-IV Model-free least-squares refinement by use of evolving factor analysis

The newly developed algorithm of evolving factor analysis has been supplemented by iterative refinement. It allows the completely model-free calculation of concentration profiles and spectra from spectrophotometric and other spectroscopic data. Not even implicit use is made of the law of mass action. The results are practically identical with those based on a specific chemical model and classical least-squares refinement. Iterative evolving factor analysis is based on applying factor analysis successively to the set of the first 1,2 M spectra of a spectrometric titration. The analysis is repeated from the opposite end and the eigenvalues thus calculated are combined into “concentration profiles” of completely abstract “species”. These “concentration profiles” are iteratively refined by normalization, calculation of the absorption spectra from the normalized concentrations and recalculation of the concentration profiles from the absorption spectra. Evolving factor analysis is not restricted to spectrometric titrations, and can also be applied to peak resolution in chromatography using a multiwavelength (diode array) photometric or mass-spectrometric detection system, or to any other ordered set of multichannel data.     

MoCalc: a new graphical user interface for molecular calculations

A new computer program called MoCalc (Molecular Calculations) has been designed to help the computational chemistry practitioner in the task of performing and analyzing molecular calculations. MoCalc is a graphical user interface for the MO calculation programs Gamess and Mopac, and uses Rasmol and Babel for molecule display and file conversion, respectively. In its initial version, MoCalc can execute the following operations: (a) create and handle Gamess and Mopac input files; (b) import any kind of molecular geometry supported by Babel and paste it as Cartesian, internal, or Gaussian-type coordinates on the input file; (c) convert Gamess and Mopac output files to inputs of both programs; (d) edit and validate the keywords that control the Gamess and Mopac calculation procedure; (e) display the input (Mopac) and output (Gamess and Mopac) molecular geometries; (f) run single or multiple (batch) calculations, either interactively or in background; (g) automatically open the output files as soon as the calculation finishes; (h) extract results from the output files, such as energy, charges, dipole, population analysis, wave function, bond orders, and valence analysis, and display them in spreadsheets; (i) calculate reactivity indices derived from the frontier orbital theory and the root-mean-square (rms) deviation of input and output geometries. All the results generated by MoCalc can be promptly transferred to text editors and electronic spreadsheets, which facilitate a detailed subsequent analysis and the publication of the results. MoCalc can also perform graphical and numerical comparative analysis of the some results when more than one output file is loaded. The program was coded in Visual Basic and runs in Windows 95/98/NT4/ME/2000/XP environments.     

Monitoring the melt-extrusion transesterification of ethylene-vinylacetate copolymer by self-modeling curve resolution analysis of on-line near-infrared spectra

The transesterification of molten ethylene-vinylacetate (EVA) copolymers by octanol with sodium methoxide as catalyst in an extruder has been monitored by on-line near infrared (NIR) spectroscopy. A total of 60 NIR spectra were acquired for 37 min with the last spectrum recorded 31 min after the addition of octanol and catalyst was stopped. The experimental spectra show strong baseline fluctuations which are corrected for by multiplicative scatter correction (MSC). The chemometric methods of the orthogonal projection approach (OPA) and multivariate curve resolution (MCR) were used to resolve the spectra and to derive concentration profiles of the species. The detailed analysis reveals the absence of completely pure variables which leads to small errors in the calculation of pure spectra. The initial estimation of a concentration that is necessary as an input parameter for MCR also presents a non-trivial task. We obtained results that were not ideal but applicable for practical concentration control. They enable a fast monitoring of the process in real-time and resolve the spectra of the EVA copolymer and the ethylene-vinyl alcohol (EVAL) copolymer to be very close to the reference spectra. The chemometric methods used and the decomposed spectra are discussed in detail.     

Spectrophotometric study of competitive complexation equilibria involving overlapped spectral responding species: Determination of the stability constant of bismuth-pyrophosphate complex

Spectrophotometric study of competitive complex formation equilibria involving overlapped spectral responding species applying a simple and versatile algorithm was carried out. The algorithm involves multivariable regression for calculation of equilibrium concentrations from multiwavelength data and mass action law for the stability constant calculation. The used regression functions are part of common statistical software. Stability constants and complex stoichiometry of competing equilibria were simultaneously determined. The species concentration profiles at several spectral overlapping and ??-coefficient of competing reaction were obtained. Non-absorbing bismuth ?? pyrophosphate (PPh) system was studied as a competitive reaction of bismuth ?? 4-(2-Pyridylazo) resorcinol (PAR) complex. The formation of Bi-PPh complex with 1:1 stoichiometry was proved in the studied concentration region (C_Bi = 1×10^?5 mol L^?1; C_PPh = 5×10^?6 ? 1×10^?4 mol L^?1). The stability constant of the complex at pH 1 and ?? = 1.0 have been determined: log?? = 4.2±0.2.      

Adsorption Profiles of Long‐Chain Polymer in Semidilute Solutions Physisorbed to a Wall

Equilibrium concentration profiles for long macromolecules in solution strongly adsorbed to a flat wall were estimated by a combination of persistent reptation and partial chain regrowth using a configurational bias lattice Monte Carlo method. The profiles were obtained for various concentrations in the semidilute regime and different chain lengths. A master curve exists in a plot of the profile reduced by the bulk concentration as a function of the distance to the wall reduced by the correlation length estimated for the bulk concentration. Near the wall, the master curve follows a power law with an exponent predicted in the scaling theory. Compared to depletion profiles at a repulsive wall that require a small penetration length, no correction of the distance to the wall is needed for the adsorption profiles.

Reduced plot of ϕ(x)/ϕ_bulk vs. x/ξ for chain length N = 1 000 and five bulk concentrations above ϕ* indicated in legend. Slope with the exact exponent from scaling theory is shown for comparison.     

Calculation of chemical equilibrium concentrations of complexing ligands and metals A flexible computer programme taking account of uncertainty in formation constant values

Metal complexes often act as substrates in enzymic reactions. Because their concentrations cannot be measured directly, they must be calculated from the formation constants and the total concentrations of the different metal and ligand species. An iteration algorithm devised by Sayce has been used to formulate a FORTRAN (ICT 1900) programme, which meets the following requirements. (1) The programme may be made to calculate the total concentrations for the parent species if the free concentration of any metal or ligand species is known, or to calculate the free concentrations of all species for which the total concentrations are known. This feature of the programme is useful for calculation of the total amounts which must be put into a solution in order to achieve prescribed free concentrations. (2) To allow for the uncertainty in the formation constants of the complex species the programme permits the input values of the formation constants to be varied automatically and the resulting variation of the calculated concentrations to be evaluated.     

Sedimentation of concentrated monodisperse colloidal suspensions: role of collective particle interaction forces

The sedimentation velocities and concentration profiles of low-charge, monodisperse hydroxylate latex particle suspensions were investigated experimentally as a function of the particle concentration to study the effects of the collective particle interactions on suspension stability. We used the Kossel diffraction technique to measure the particle concentration profile and sedimentation rate. We conducted the sedimentation experiments using three different particle sizes. Collective hydrodynamic interactions dominate the particle-particle interactions at particle concentrations up to 6.5 vol%. However, at higher particle concentrations, additional collective particle-particle interactions resulting from the self-depletion attraction cause particle aggregation inside the suspension. The collective particle-particle interaction forces play a much more important role when relatively small particles (500 nm in diameter or less) are used. We developed a theoretical model based on the statistical particle dynamics simulation method to examine the role of the collective particle interactions in concentrated suspensions in the colloidal microstructure formation and sedimentation rates. The theoretical results agree with the experimentally-measured values of the settling velocities and concentration profiles.     

Elektronentheorie auf dem Smartphone

We introduce a new tool for the performance of Hueckel molecular orbital calculations on a smartphone using a simple graphical input. It produces all routine output expected from a Hueckel calculation. Advanced users may also study things like Moebius rings, hetero systems, or Pauli‐antisymmetry constraints in monocycles. In short, in addition to its main use in teaching, the app can also be employed for fast estimate in research, be it only to assess whether the application of state‐of‐the‐art quantum chemical calculations may be warranted.     

TissueDistributionDBs: a repository of organism-specific tissue-distribution profiles

Tissue-distribution profiles are crucial for understanding the characteristics of cells and tissues in terms of their differential expression of genes. Most of the currently available resources for tissue-distribution profiles are either specialized for a few particular organisms, tissue types and disease stages or do not consider the “tissue ontology” levels for the calculation of the tissue-distribution profiles. Therefore, we have developed “TissueDistributionDBs”, a repository of tissue-distribution profiles based on the expressed sequence tags (ESTs) data extracted from the UniGene database by employing “Tissue Ontology” available at BRENDA. To overcome the occurrence of the natural language variations in the EST’s source tissue-type terms, we have generated a “tissue synonym library” and standardized these tissue-type terms by cross-referencing to the controlled vocabulary for tissue-type terms available at BRENDA “Tissue Ontology”. Furthermore, we have provided a quantitative expression for genes among the tissue types at various anatomical levels by constructing “tissue slims”. Concurrently, the expression among tissue types is used for tissue-distribution calculations. The resulting output profiles can be queried by the Sequence Retrieval System (SRS) and are currently available for 20 different model organisms. We benchmarked our database system against the Swissprot database using a set of 40 different tissue types. This database system is useful for the understanding of the tissue-specific expression patterns of genes, which have implications for the identification of possible new therapeutic drug targets, in gene discovery, and in the design and analysis of micro-arrays. TissueDistributionDBs can be accessed via the World Wide Web (www) at http://genius.embnet.dkfz-heidelberg.de/menu/tissue_db/.     

A NEURAL NETWORK STUDY ON GLASS TRANSITION TEMPERATURE OF POLYMERS

In this paper, an atificial neural network model is adopted to study the glass transition temperature of polymers. Inour artificial neural networks, the input nodes are the characteristic ratio C_∞, the average molecular weigh M_e betweenentanglement points and the molecular weigh M_(mon) of repeating unit. The output node is the glass transition temperature T_g,and the number of the hidden layer is 6. We found that the artificial neural network simulations are accurate in predicting theoutcome for polymers for which it is not trained. The maximum relative error for predicting of the glass transitiontemperature is 3.47%, and the overall average error is only 2.27%. Artificial neural networks may provide some new ideas toinvestigate other properties of the polymers.     

On the use of catalysis to bias reaction pathways in out-of-equilibrium systems

Catalysis is an essential function in living systems and provides a way to control complex reaction networks. In natural out-of-equilibrium chemical reaction networks (CRNs) driven by the consumption of chemical fuels, enzymes provide catalytic control over pathway kinetics, giving rise to complex functions. Catalytic regulation of man-made fuel-driven systems is far less common and mostly deals with enzyme catalysis instead of synthetic catalysts. Here, we show via simulations, illustrated by literature examples, how any catalyst can be incorporated in a non-equilibrium CRN and what their effect is on the behavior of the system. Alteration of the catalysts'' concentrations in batch and flow gives rise to responses in maximum conversion, lifetime (i.e. product half-lives and t90 – time to recover 90% of the reactant) and steady states. In situ up or downregulation of catalysts'' levels temporarily changes the product steady state, whereas feedback elements can give unusual concentration profiles as a function of time and self-regulation in a CRN. We show that simulations can be highly effective in predicting CRN behavior. In the future, shifting the focus from enzyme catalysis towards small molecule and metal catalysis in out-of-equilibrium systems can provide us with new reaction networks and enhance their application potential in synthetic materials, overall advancing the design of man-made responsive and interactive systems.

We show, via simulations, how catalytic control over individual paths in a fuel-driven non-equilibrium chemical reaction network in batch or flow gives rise to responses in maximum conversion, lifetime and steady states.     

Dynamics and Control Strategies for a Butanol Fermentation Process

In this work, mathematical modeling was employed to assess the dynamic behavior of the flash fermentation process for the production of butanol. This process consists of three interconnected units as follows: fermentor, cell retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). Based on the study of the dynamics of the process, suitable feedback control strategies [single input/single output (SISO) and multiple input/multiple output (MIMO)] were elaborated to deal with disturbances related to the process. The regulatory control consisted of keeping sugar and/or butanol concentrations in the fermentor constant in the face of disturbances in the feed substrate concentration. Another objective was the maintenance of the proper operation of the flash tank (maintenance of the thermodynamic equilibrium of the liquid and vapor phases) considering that oscillations in the temperature in the tank are expected. The servo control consisted of changes in concentration set points. The performance of an advanced controller, the dynamic matrix control, and the classical proportional-integral controller was evaluated. Both controllers were able to regulate the operating conditions in order to accommodate the perturbations with the lowest possible alterations in the process outputs. However, the performance of the PI controller was superior because it showed quicker responses without oscillations.