Genetic and process engineering approaches for improving lipid productivity in the non-conventional oleaginous yeast Cutaneotrichosporon oleaginosus

Gli oli microbici stanno ricevendo sempre più attenzioni come possibile alternativa agli oli vegetali, nel processo di sostituzione dei combustibili fossili. Tuttavia, diversi aspetti necessitano di essere ottimizzati al fine di ottenere oli economicamente competitivi e con caratteristiche chimico-fisiche desiderate. In questa ricerca, sono stati utilizzati due differenti approcci per poter realizzare l’obiettivo preposto. Il primo, si è basato sull’ingegnerizzazione genetica del lievito C. oleaginous, al fine di incrementare la produttività di lipidi e modificare la composizione dei trigliceridi (TAG) sintetizzati. Un protocollo basato su una trasformazione genetica mediata da Agrobacterium è stato utilizzato per sovraesprimere la diacilglicerol trasnferasi (DGA1), l’enzima responsabile dell’ultimo step della sintesi dei TAG, e la Δ9-desaturasi, l’enzima che catalizza la conversione dell’acido stearico (C18:0) in acido oleico (C18:1). La selezione di colonie positive e l’analisi dei mutanti ottenuti ha confermato la buona riuscita della trasformazione. Il secondo approccio ha mirato a studiare l’influenza sulla crescita e sul profilo di lipidi accumulati da C. oleaginous da parte di diversi acidi grassi volatili (VFAs), una materia prima ottenibile da trattamenti di scarti industriali. A questo proposito, sono state utilizzate fermentazioni fed-batch su scala da 1-L basate su glucosio e miscele sintetiche di acido acetico e di VFAs come fonte di carbonio. L’utilizzo simultaneo di acido acetico e acidi secondari ha mostrato come sia possibile stimolare il metabolismo microbico al fine di incrementare l'accumulo di oli e ottenere una composizione chimica lipidica desiderata.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Modeling of columnar-to-equiaxed transition in solidified Al-Si alloys

A Cellular-Automaton Finite-Volume-Method (CAFVM) algorithm has been developed, coupling with macroscopic model for heat transfer calculation and microscopic models for nucleation and growth. The solution equations have been solved to determine the time-dependent constitutional undercooling and interface retardation during solidification. The constitutional undercooling is then coupled into the CAFVM algorithm to investigate both the effects of thermal and constitutional undercooling on columnar growth and crystal selection in the columnar zone, and formation of equiaxed crystals in the bulk liquid. The model cannot only simulate microstructures of alloys but also investigates nucleation mechanisms and growth kinetics of alloys solidified with various solute concentrations and solidification morphologies.

Signature of mott-insulator transition with ultracold fermions in a one-dimensional optical lattice

Using the exact Bethe ansatz solution of the Hubbard model and Luttinger liquid theory, we investigate the density profiles and collective modes of one-dimensional ultracold fermions confined in an optical lattice with a harmonic trapping potential. We determine a generic phase diagram in terms of a characteristic filling factor and a dimensionless coupling constant. The collective oscillations of the atomic mass density, a technique that is commonly used in experiments, provide a signature of the quantum phase transition from the metallic phase to the Mott-insulator phase. A detailed experimental implementation is proposed.

SAR imaging of buried objects from MoM modelled scattered field

Synthetic aperture radar (SAR) images of resonant buried objects are modelled in the presence of ground surface clutter. The method of moments (MoM) is used to model scattered fields from a resonant buried conductor and clutter is modelled as a bivariant Gaussian distribution. A diffraction stack SAR imaging technique is applied to the ultra-wideband waveforms to give a bipolar signal image. A number of examples have been computed to illustrate the combined effects of SAR processing with resonant targets and clutter. SAR images of different targets show differences which may facilitate target identification. To maximise the peak signal-to-clutter ratio, an image correlation technique is applied and the results are shown.

Complex natural resonances of conducting planar objects buried in a dielectric half-space

A scheme is presented to incorporate a mixed potential integral equation (MPIE) using Michalski's formulation C with the method of moments (MoM) for analyzing the scattering of a plane wave from conducting planar objects buried in a dielectric half-space. The robust complex image method with a two-level approximation is used for the calculation of the Green's functions for the half-space. To further speed up the computation, an interpolation technique for filling the matrix is employed. While the induced current distributions on the object's surface are obtained in the frequency domain, the corresponding time domain responses are calculated via the inverse fast Fourier transform (FFT), The complex natural resonances of targets are then extracted from the late time response using the generalized pencil-of-function (GPOF) method. We investigate the pole trajectories as we vary the distance between strips and the depth and orientation of single, buried strips, The variation from the pole position of a single strip in a homogeneous dielectric medium was only a few percent for most of these parameter variations.

Transmit array of transistor amplifiers illuminated by a patch array in the reactive near-field region

In this paper, a small transmit array of transistor amplifiers illuminated by a passive array of microstrip patches in the reactive near-field region is investigated as a power-combining structure. The two cases considered are when the transmit array radiates in a free space and when a passive array similar to the one used for illumination collects the radiated power. A comparison of the performance of the proposed structure against the alternative one, which uses a conventional horn antenna as a power-launching/receiving device, is also presented.

Simulation of interface states effect on the scanning capacitance microscopy measurement of p-n junctions

A two-dimensional numerical simulation model of interface states in scanning capacitance microscopy (SCM) measurements of p-n junctions is presented-In the model, amphoteric interface states with two transition energies in the Si band gap are represented as fixed charges to account for their behavior in SCM measurements. The interface states are shown to cause a stretch-out-and a parallel shift of the capacitance-voltage characteristics in the depletion. and neutral regions of p-n junctions, respectively. This explains the discrepancy between - the SCM measurement and simulation near p-n junctions, and thus modeling interface states is crucial for SCM dopant profiling of p-n junctions. (C) 2002 American Institute of Physics.

High resolution 3-D imaging via multi-pass SAR

Spaceborne/airborne synthetic aperture radar (SAR) systems provide high resolution two-dimensional terrain imagery. The paper proposes a technique for combining multiple SAR images, acquired on flight paths slightly separated in the elevation direction, to generate high resolution three-dimensional imagery. The technique could be viewed as an extension to interferometric SAR (InSAR) in that it generates topographic imagery with an additional dimension of resolution. The 3-D multi-pass SAR imaging system is typically characterised by a relatively short ambiguity length in the elevation direction. To minimise the associated ambiguities we exploit the relative phase information within the set of images to track the terrain landscape. The SAR images are then coherently combined, via a nonuniform DFT, over a narrow (in elevation) volume centred on the 'dominant' terrain ground plane. The paper includes a detailed description of the technique, background theory, including achievable resolution, and the results of an experimental study.