Investigating brain tumor differentiation with diffusion and perfusion metrics at 3T MRI using pattern recognition techniques

The aim of this study was to evaluate the contribution of diffusion and perfusion MR metrics in the discrimination of intracranial brain lesions at 3T MRI, and to investigate the potential diagnostic and predictive value that pattern recognition techniques may provide in tumor characterization using these metrics as classification features. Conventional MRI, diffusion weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic-susceptibility contrast imaging (DSCI) were performed on 115 patients with newly diagnosed intracranial tumors (low-and- high grade gliomas, meningiomas, solitary metastases). The Mann–Whitney U test was employed in order to identify statistical differences of the diffusion and perfusion parameters for different tumor comparisons in the intra-and peritumoral region. To assess the diagnostic contribution of these parameters, two different methods were used; the commonly used receiver operating characteristic (ROC) analysis and the more sophisticated SVM classification, and accuracy, sensitivity and specificity levels were obtained for both cases. The combination of all metrics provided the optimum diagnostic outcome. The highest predictive outcome was obtained using the SVM classification, although ROC analysis yielded high accuracies as well. It is evident that DWI/DTI and DSCI are useful techniques for tumor grading. Nevertheless, cellularity and vascularity are factors closely correlated in a non-linear way and thus difficult to evaluate and interpret through conventional methods of analysis. Hence, the combination of diffusion and perfusion metrics into a sophisticated classification scheme may provide the optimum diagnostic outcome. In conclusion, machine learning techniques may be used as an adjunctive diagnostic tool, which can be implemented into the clinical routine to optimize decision making.     

Use of holography in particle image velocimetry measurements of a swirling flow

 Particle Image Velocimetry (PIV) is now a well established experimental technique to measure two components of the velocity in a planar region of a flow field. This paper shows how its proven capabilities can be further extended by using holographic recording to register the particle displacements. Among other unique characteristics, holography enables the acquisition of multiple images on a single plate, and the recording of three dimensional images. These features are used to circumvent some of the limitations of conventional PIV. Some of these possibilities are demonstrated in this study by applying the technique to a high Reynolds number swirling flow using a lens-less off-axis orthogonal recording geometry. Received: 25 February 1998/ Accepted: 2 September 1998     

Depolarized light scattering from critical polymer blends

Depolarized light scattering of binary polymer blends in disordered state near the demixing critical point is considered both theoretically and experimentally. It is shown that the depolarized scattering in such systems is predominantly due to double scattering processes induced by composition fluctuations. For long enough polymer chains, this scattering is stronger than the contribution from intrinsic anisotropy fluctuations. The general equation for the static and dynamic double scattering function is obtained in terms of the system structure factor. The scattering functions are calculated both analytically and numerically (dynamic part) for polymer blends. We found that the depolarized intensity depends on the polymerization degree N and the relative distance from the critical point τ = 1 – χ*/χ (where χ is the Flory‐Huggins interaction parameter and χ* its critical value) as I_vh ∼︁ N²/τ², which is in good agreement with the experimental data. It is also shown that the dynamic scattering function is decaying non‐exponentially. We calculate the relaxation rate and the non‐exponentiality parameter as functions of the scattering angle and τ. These theoretical predictions are compared with experimental data for three chemically different blends.     

Broadband Dielectric Relaxation Spectroscopy in Polymer Nanocomposites

Summary: Dielectric spectroscopy in the frequency domain and thermally stimulated depolarization currents techniques, covering together a broad frequency range (10⁻⁴–10⁹ Hz), were employed to investigate molecular dynamics in relation to structure and morphology in polymeric nanocomposites. Several systems were investigated, three of them with the same epoxy resin matrix and different inclusions (modified smectite clay, conducting carbon nanoparticles and diamond nanoparticles) and two with silica nanofiller (styrene-butadiene rubber/silica and polyimide/silica nanocomposites). Special attention was paid to the investigation of segmental dynamics associated with the glass transition of the polymer matrix, in combination also with differential scanning calorimetry measurements. Effects of nanoparticles on local (secondary) relaxations and on the overall dielectric behavior were, however, also investigated. Several interesting results were obtained and discussed for each of the particular systems. Two opposite effects seem to be common to the nanocomposites studied and dominate their behavior: (1) immobilization/reduction of mobility of a fraction of the chains at the interface to the inorganic nanoparticles, due to chemical or physical bonds with the particles, and (2) loosened molecular packing of the chains, due to tethering and geometrical confinement, resulting in an increase of free volume and of molecular mobility.     

The engineering of doxorubicin-loaded liposome-quantum dot hybrids for cancer theranostics

In the fabrication of phase change random access memory(PRAM) devices, high temperature thermal processes are inevitable. We investigate the thermal stability of Ge2Sb2Te5(GST) which is a prototypical phase change material. After high temperature process, voids of phase change material exist at the interface between Ge2Sb2Te5 and substrate in the initial open memory cell. This lower region of Ge2Sb2Te5 is found to be a Te-rich phase change layer. Phase change memory devices are fabricated in different process conditions and examined by scanning electron microscopy and energy dispersive X-ray. It is found that hot-chuck process, nitrogen-doping process, and lower temperature inter-metal dielectric(IMD) deposition process can ease the thermal impact of line-GST PRAM cell.     

A model for the shear viscosity of non-colloidal suspensions with Newtonian matrix fluids

We present a model for the shear viscosity of non-colloidal suspensions with Newtonian matrix fluids. The model is based on the original idea first presented by Brinkman (Applied Sci Research A1:27-34. 1947) for the viscous force exerted by a flowing fluid on a dense swarm of spherical particles. In particular, we consider an inertialess suspension in which the mean flow is driven by a pressure difference, and simultaneously, the suspension is subject to simple shear. Assuming steady state, incompressibility and taking into account a resistance force which is generated due to the presence of the particles in the flow, the three-dimensional governing equations for the mean flow around a single spherical particle are solved analytically. Self-consistency of the model provides a relationship between the resistance parameter and the volume fraction of the solid phase. A volume, or an ensemble, averaging of the total stress gives the bulk properties and an expression for the relative (bulk) viscosity of the suspension. The viscosity expression reduces to the Einstein limit for dilute suspensions and agrees well with empirical formulas from the literature in the semi-dilute and concentrated regimes. Since the model is based on a single particle and its average interaction with the other particles is isotropic, no normal stress differences can be predicted. A possible method of addressing this problem is provided in the paper.     

Simulations of nematic homopolymer melts using particle-based models with interactions expressed through collective variables

We develop a hybrid Monte Carlo approach for modelling nematic liquid crystals of homopolymer melts. The polymer architecture is described with a discrete worm-like chain model. A quadratic density functional accounts for the limited compressibility of the liquid, while an additional quadratic functional of the local orientation tensor of the segments captures the nematic ordering. The approach can efficiently address large systems parametrized according to volumetric and conformational properties, representative of real polymeric materials. The results of the simulations regarding the influence of the molecular weight on the isotropic-nematic transition are compared to predictions from a Landau-de Gennes free energy expansion. The formation of the nematic phase is addressed within Rouse-like dynamics, realized using the current model.     

Buyer behavior adaptation based on a fuzzy logic controller and prediction techniques

The current form of Web provides numerous product resources available to users. Users can rely on intelligent agents for purchase actions. These actions are taken in specific environments such as Electronic Markets (EMs). In this paper, we study the interaction process between buyers and sellers and focus on the buyer side. Each buyer has the opportunity to interact with a number of sellers trying to buy the most appropriate products. This interaction can be modeled as a finite horizon Bargaining Game (BG). In this game, players have opposite goals concerning the product price. We adopt a number of techniques in the buyer side trying to give the appropriate level of efficiency in the buyer decision process. The buyer uses a prediction mechanism in combination with the use of Fuzzy Logic (FL) theory in order to be able to predict the upcoming seller proposal and, thus, understand the seller pricing policy. Based on this, he/she can adapt his/her behavior when trying to purchase products. The buyer adaptation mechanism produces the belief that the buyer has about the seller pricing policy and a parameter that indicates his/her own pricing policy which yields the buyer offers in the upcoming rounds. Moreover, the buyer is based on FL system that derives the appropriate actions at every round of the BG. Our results show that the combination of Fuzzy Logic (FL) with the above-mentioned techniques provides an efficient decision mechanism in the buyer side that in specific scenarios outperforms an optimal stopping model.