Experiments and modelling of phenanthrene biodegradation in the aqueous phase by a mixed culture

Pollution by polycyclic aromatic hydrocarbons(PAHs) is widespread due to unsuitable disposal of industrial waste. They are mostly defined as priority pollutants by environmental protection authorities worldwide. Phenanthrene, a typical PAH, was selected as the target in this paper. The PAH-degrading mixed culture, named ZM, was collected from a petroleum contaminated river bed. This culture was injected into phenanthrene solutions at different concentrations to quantify the biodegradation process. Results show near-complete removal of phenanthrene in three days of biodegradation if the initial phenanthrene concentration is low. When the initial concentration is high, the removal rate is increased but 20%-40% of the phenanthrene remains at the end of the experiment. The biomass shows a peak on the third day due to the combined effects of microbial growth and decay. Another peak is evident for cases with a high initial concentration, possibly due to production of an intermediate metabolite. The pH generally decreased during biodegradation because of the production of organic acid. Two phenomenological models were designed to simulate the phenanthrene biodegradation and biomass growth. A relatively simple model that does not consider the intermediate metabolite and its inhibition of phenanthrene biodegradation cannot fit the observed data. A modified Monod model that considered an intermediate metabolite (organic acid) and its inhibiting reversal effect reasonably depicts the experimental results.

Three-dimensional electrical impedance, tomography: A topology optimization approach

Electrical impedance tomography is a technique to estimate the impedance distribution within a domain, based on measurements on its boundary. In other words, given the mathematical model of the domain, its geometry and boundary conditions, a nonlinear inverse problem of estimating the electric impedance distribution can be solved. Several impedance estimation algorithms have been proposed to solve this problem. In this paper, we present a three-dimensional algorithm, based on the topology optimization method, as an alternative. A sequence of linear programming problems, allowing for constraints, is solved utilizing this method. In each iteration, the finite element method provides the electric potential field within the model of the domain. An electrode model is also proposed (thus, increasing the accuracy of the finite element results). The algorithm is tested using numerically simulated data and also experimental data, and absolute resistivity values are obtained. These results, corresponding to phantoms with two different conductive materials, exhibit relatively well-defined boundaries between them, and show that this is a practical and potentially useful technique to be applied to monitor lung aeration, including the possibility of imaging a pneumothorax.

Dynamic strain measurement using piezoelectric polymer film

Piezoelectric polymers have been used to form the basis of dynamic strain gauges for the detection of stress waves. The linearity of response was tested using a split Hopkinson pressure bar arrangement. The results obtained illustrate the effectiveness of piezoelectric film strain gauges in the measurement of axial stress waves.

Severe and refractory myositis in mixed connective tissue disease: a description of a rare case

Mixed connective tissue disease (MCTD) is a rare disease that includes clinical and laboratorial manifestations of systemic lupus erythematosus, scleroderma and polymyositis that is associated with high titers of anti-U1RNP antibodies. In general, muscle involvement is subclinical, usually appearing as an increase in muscle enzyme levels that tends to be a characteristic of the initial phases of the disease. Severe clinical muscle weakness is not observed in this disease. The objective of this study is to report a rare case of a patient who presented a severe onset of myositis characterized by dysphagia, an increase in myopathy and a weakening of the cervical musculature. While there was no response to the administration of an initial dose of corticosteroids, improvement was observed after increasing the dose of corticosteroids, in addition to the initiation of pulse therapy with methylprednisolone accompanied by methotrexate treatment. The authors emphasize that there is only one previously reported case regarding a child with MCTD and severe clinical myopathy on electromyography and muscle biopsy, and they report in this article one adult female patient who presented severe myositis and was refractive to corticotherapy. Lupus (2010) 19, 1659-1661.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Analysis of dynamic models for structural insight and model reduction .2. A multi-stage compressor shutdown case-study

In this second paper, the three structural measures which have been developed are used in the modelling of a three stage centrifugal synthesis gas compressor. The goal of this case study is to determine the essential mathematical structure which must be incorporated into the compressor model to accurately model the shutdown of this system. A simple, accurate and functional model of the system is created via three structural measures. It was found that the model can be correctly reduced into its basic modes and that the order of the differential system can be reduced from 51(st) to 20(th). Of the 31 differential equational 21 reduce to algebraic relations, 8 become constants and 2 can be deleted thereby increasing the algebraic set from 70 to 91 equations. An interpretation is also obtained as to which physical phenomena are dominating the dynamics of the compressor add whether the compressor will enter surge during the shutdown. Comparisons of the reduced model performance against the full model are given, showing the accuracy and applicability of the approach. Copyright (C) 1996 Elsevier Science Ltd

A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Integer matrix diagonalization

We consider algorithms for computing the Smith normal form of integer matrices. A variety of different strategies have been proposed, primarily aimed at avoiding the major obstacle that occurs in such computations-explosive growth in size of intermediate entries. We present a new algorithm with excellent performance. We investigate the complexity of such computations, indicating relationships with NP-complete problems. We also describe new heuristics which perform well in practice. Wie present experimental evidence which shows our algorithm outperforming previous methods. (C) 1997 Academic Press Limited.

Genetic algorithms for continuous optimization problems - a concept of parameter-space size adjustment

The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.

An optimization model for antibiotic use

There is a positive correlation between the intensity of use of a given antibiotic and the prevalence of resistant strains. The more you treat, more patients infected with resistant strains appears and, as a consequence, the higher the mortality due to the infection and the longer the hospitalization time. In contrast, the less you treat, the higher the mortality rates and the longer the hospitalization time of patients infected with sensitive strains that could be successfully treated. The hypothesis proposed in this paper is an attempt to solve such a conflict: there must be an optimum treatment intensity that minimizes both the additional mortality and hospitalization time due to the infection by both sensitive and resistant bacteria strains. In order to test this hypothesis we applied a simple mathematical model that allowed us to estimate the optimum proportion of patients to be treated in order to minimize the total number of deaths and hospitalization time due to the infection in a hospital setting. (C) 2007 Elsevier Inc. All rights reserved.