Use of Zebrafish Embryo Assay to Evaluate Toxicity and Safety of Bioreactor-Grown Exopolysaccharides and Endopolysaccharides from European Ganoderma applanatum Mycelium for Future Aquaculture Applications

Natural mycelial exopolysaccharide (EPS) and endopolysaccharide (ENS) extracted from bioreactor-cultivated European Ganoderma applanatum mushrooms are of potential high commercial value for both food and adjacent biopharmaceutical industries. In order to evaluate their potential toxicity for aquaculture application, both EPS (0.01–10 mg/mL) and ENS (0.01–10 mg/mL) extracts were tested for Zebrafish Embryo Toxicity (ZFET); early development effects on Zebrafish Embryos (ZE) were also analyzed between 24 and 120 h post-fertilization (HPF). Both EPS and ENS are considered non-toxic with LC₅₀ of 1.41 mg/mL and 0.87 mg/mL respectively. Both EPS and ENS did not delay hatching and teratogenic defect towards ZE with <1.0 mg/mL, respectively. No significant changes in the ZE heart rate were detected following treatment with the two compounds tested (EPS: 0.01–10 mg/mL: 176.44 ± 0.77 beats/min and ENS: 0.01–10 mg/mL: 148.44 ± 17.75 beats/min) compared to normal ZE (120–180 beats/min). These initial findings support future pre-clinical trials in adult fish models with view to safely using EPS and ENS as potential feed supplements for supplements for development of the aquaculture industry.     

Preparation and characterization of polyethylene/cellulose composite with diatomite and bentonite as fillers

ABSTRACT

This research work was carried out to examine the performance of different polyethylene/cellulose composites. The effect of three different factors was examined. First factor was the effect of clay type as filler, in which diatomite and bentonite were used. Second factor was the effect of cellulose grafting with cyclic oxymethylene. Third factor was the presence of polyethylene grafted with maleic anhydride (PE-g-MA) in the polymer matrix of polyethylene/cellulose as a compatibilizer. The polymer matrix was characterized by scanning electron microscope (SEM), differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA). Tensile test and permeability were also examined.     

A fictitious domain decomposition method for the solution of partially axisymmetric acoustic scattering problems. Part I: Dirichlet boundary conditions

We present a fictitious domain decomposition method for the fast solution of high‐frequency acoustic scattering problems characterized by a partially axisymmetric sound‐soft scatterer. We apply this method to the solution of various mockup submarine problems, and highlight its computational advantages and intrinsic parallelism. Copyright © 2002 John Wiley & Sons, Ltd.     

A fictitious domain decomposition method for the solution of partially axisymmetric acoustic scattering problems. Part 2: Neumann boundary conditions

We present a fictitious domain decomposition method for the fast solution of acoustic scattering problems characterized by a partially axisymmetric sound‐hard scatterer. We apply this method to the solution of a mock‐up submarine problem, and highlight its computational advantages and intrinsic parallelism. A key component of our method is an original idea for addressing a Neumann boundary condition in the general framework of a fictitious domain method. This idea is applicable to many other linear partial differential equations besides the Helmholtz equation. Copyright © 2003 John Wiley & Sons, Ltd.     

Reliability‐based estimation of the survival of Listeria monocytogenes in chorizos

Reliability analysis is especially important when critical decisions are to be made involving potentially severe adverse consequences such as foodborne illness. Owing to uncertainty associated with the parameters controlling survival of Listeria monocytogenes in chorizo (a Mexican‐style sausage), the time needed to reduce the count by a certain number (n) of logs (t_nD) is probabilistic. In this paper the first‐order second‐moment (FOSM) method based on Taylor series expansion is used to derive the expected value and standard deviation of t_nD as function of the operating conditions (random variables) affecting survival, namely initial water activity (a_w0) of the sausage batter, storage temperature (T) and airflow velocity (F), along with their uncertainties characterised by their means and coefficients of variation. For any given n the derived t_nD probability distribution enables one to determine an estimate of t_nD for any desired level of reliability or confidence level, such as 50% (median value), 95%, 99%, etc. Among the conclusions drawn were: (i) the variability associated with T and F has a minor effect on estimating uncertainty in t_nD, whereas the reliability of t_nD estimation is greatly influenced by the uncertainty in a_w0; and (ii) the uncertainty in a_w0 has the greatest impact when a_w0 of the sausage formulation exceeds 0.90. The approach used and discussed in this paper can be applied to any survival/inactivation study to incorporate the effect of uncertainty in the various extrinsic and intrinsic parameters on the survival kinetics of the pathogen in a food system under evaluation. Copyright © 2006 Society of Chemical Industry     

Automatic partitioning of unstructured meshes for the parallel solution of problems in computational mechanics

Most of the recently proposed computational methods for solving partial differential equations on multiprocessor architectures stem from the 'divide and conquer' paradigm and involve some form of domain decomposition. For those methods which also require grids of points or patches of elements, it is often necessary to explicitly partition the underlying mesh, especially when working with local memory parallel processors. In this paper, a family of cost-effective algorithms for the automatic partitioning of arbitrary two- and three-dimensional finite element and finite difference meshes is presented and discussed in view of a domain decomposed solution procedure and parallel processing. The influence of the algorithmic aspects of a solution method (implicit/explicit computations), and the architectural specifics of a multiprocessor (SIMD/MIMD, startup/transmission time), on the design of a mesh partitioning algorithm are discussed. The impact of the partitioning strategy on load balancing, operation count, operator conditioning, rate of convergence and processor mapping is also addressed. Finally, the proposed mesh decomposition algorithms are demonstrated with realistic examples of finite element, finite volume, and finite difference meshes associated with the parallel solution of solid and fluid mechanics problems on the iPSC/2 and iPSC/860 multiprocessors.     

Depollution of atmospheric emissions of wood pyrolysis furnaces

The wood carbonization in Tunisia consists essentially of traditional activity using charcoaling stacks and pits characterized by high atmospheric pollution and poor energy conversion. Indeed, 70% of the initial mass of anhydrous wood are found in the vapor as aerosols, polluting and toxic gases and complex condensable organic compounds that can cause a substantial pollution of air, ground and water. Several processes of treatment and energy valorization of such effluents were proposed, but the incineration remains at present the most promising technique of depollution. The results show that the incineration, at about 1000°C, of wood carbonization smokes allows the destruction of 99% of the mass of pollutants except CO₂ and the reduction of polluting gas emission. The possible valorization of the smoke’s energy in the exit of the incinerator enhances the thermal efficiency of the process.     

Microwave diversity imaging and automated target identificationbased on models of neural networks

Radar targets can be identified by either forming images with sufficient resolution to be recognized by the human observer or by forming signatures or representations of the target for automated machine recognition. Tomographic microwave diversity imaging techniques that combine angular (aspect), spectral, and polarization degrees of freedom have been shown, as summarized in the first part of this paper, to be capable of producing images of the scattering centers of a target with near optical resolution. In the second part of the paper the author shows that collective nonlinear signal processing based on models of neural networks combined with the use of suitable target signatures (here sinogram representations) offer the promise of robust super-resolved target identification from partial information. Results presented are of numerical simulations for a neuromorphic processor where the neural net performs simultaneously the functions of data storage, processing, and recognition by automatically generating an identifying object label, and fast optoelectronic architectures and hardware implementations are briefly mentioned. Practical considerations and extensions to real systems are briefly discussed     

DRYING KINETICS AND CHARACTERISTIC DRYING CURVE OF LIGHTLY SALTED SARDINE (SARDINELLA AURITA)

Drying of lightly salted sardine (Sardinella aurita) was accomplished using three air temperatures (35°C, 40°C, 50°C) and three air velocities (0.5 m/s, 1.5 m/s, 2 m/s); the effects of drying conditions on drying kinetics were studied. As for all biological products, air temperature is the main factor influencing the drying kinetics. However, over a given temperature which seems to correspond to protein modification (50°C), and at a high air flow rate (2 m/s and 2.5 m/s) a crust formation on the surface of the fish, due to the combined effect of heat and salt was observed. This phenomenon inhibited the drying rate. From the drying curves, two falling rate periods were observed. The dimensionless drying rate versus a dimensionless moisture content data were regressed by the Marquardt Levenberg non-linear optimization method to obtain an empirical equation describing the salted sardine characteristic drying curve.