Coherent potential approximation, averaged T-matrix approximation and Lloyd's model

It is shown how the single-site coherent potential approximation and the averaged T-matrix approximation become exact in the calculation of the averaged single-particle Green function of the electron in the Anderson model when the site energy is distributed randomly with lorentzian distribution. Using these approximations, Lloyd's exact result is reproduced.

Study of linear and nonlinear optical properties of dendrimers using density matrix renormalization group method

We have used the density matrix renormalization group (DMRG) method to study the linear and nonlinear optical responses of first generation nitrogen based dendrimers with donor acceptor groups. We have employed Pariser–Parr–Pople Hamiltonian to model the interacting pi electrons in these systems. Within the DMRG method we have used an innovative scheme to target excited states with large transition dipole to the ground state. This method reproduces exact optical gaps and polarization in systems where exact diagonalization of the Hamiltonian is possible. We have used a correction vector method which tacitly takes into account the contribution of all excited states, to obtain the ground state polarizibility, first hyperpolarizibility, and two photon absorption cross sections. We find that the lowest optical excitations as well as the lowest excited triplet states are localized. It is interesting to note that the first hyperpolarizibility saturates more rapidly with system size compared to linear polarizibility unlike that of linear polyenes.

Matrix Decomposition Methods for Data Mining : Computational Complexity and Algorithms

Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

Role of Capping Ligands on the Nanoparticles in the Modulation of Properties of a Hybrid Matrix of Nanoparticles in a 2D Film and in a Supramolecular Organogel

We incorporate various gold nanoparticles (AuNPs) capped with different ligands in two-dimensional films and three-dimensional aggregates derived from N-stearoyl-L-alanine and N-lauroyl-L-alanine, respectively. The assemblies of N-stearoyl-L-alanine afforded stable films at the air-water interface. More compact assemblies were formed upon incorporation of AuNPs in the air-water interface of N-stearoyl-L-alanine. We then examined the effects of incorporation of various AuNPs functionalized with different capping ligands in three-dimensional assemblies of N-lauroyl-L-alanine, a compound that formed a gel in hydrocarbons. The profound influence of nanoparticle incorporation into physical gels was evident from evaluation of various microscopic and bulk properties. The interaction of AuNPs with the gelator assembly was found to depend critically on the capping ligands protecting the Au surface of the gold nanoparticles. Transmission electron microscopy (TEM) showed a long-range directional assembly of certain AuNPs along the gel fibers. Scanning electron microscopy (SEM) images of the freeze-dried gels and nanocomposites indicate that the morphological transformation in the composite microstructures depends significantly on the capping agent of the nanoparticles. Differential scanning calorimetry (DSC) showed that gel formation from sol occurred at a lower temperature upon incorporation of AuNPs having capping ligands that were able to align and noncovalently interact with the gel fibers. Rheological studies indicate that the gel-nanoparticle composites exhibit significantly greater viscoelasticity compared to the native gel alone when the capping ligands are able to interact through interdigitation into the gelator assembly. Thus, it was possible to define a clear relationship between the materials and the molecular-level properties by means of manipulation of the information inscribed on the NP surface.

Applicability of pebble matrix filtration for the pre-treatment of surface waters containing high turbidity and NOM

Purification of drinking water is routinely achieved by use of conventional coagulants and disinfection procedures. However, there are instances such as flood events when the level of turbidity reaches extreme levels while NOM may be an issue throughout the year. Consequently, there is a need to develop technologies which can effectively treat water of high turbidity during flood events and natural organic matter (NOM) content year round. It was our hypothesis that pebble matrix filtration potentially offered a relatively cheap, simple and reliable means to clarify such challenging water samples. Therefore, a laboratory scale pebble matrix filter (PMF) column was used to evaluate the turbidity and natural organic matter (NOM) pre-treatment performance in relation to 2013 Brisbane River flood water. Since the high turbidity was only a seasonal and short term problem, the general applicability of pebble matrix filters for NOM removal was also investigated. A 1.0 m deep bed of pebbles (the matrix) partly in-filled with either sand or crushed glass was tested, upon which was situated a layer of granular activated carbon (GAC). Turbidity was measured as a surrogate for suspended solids (SS), whereas, total organic carbon (TOC) and UV Absorbance at 254 nm were measured as surrogate parameters for NOM. Experiments using natural flood water showed that without the addition of any chemical coagulants, PMF columns achieved at least 50% turbidity reduction when the source water contained moderate hardness levels. For harder water samples, above 85% turbidity reduction was obtained. The ability to remove 50% turbidity without chemical coagulants may represent significant cost savings to water treatment plants and added environmental benefits accrue due to less sludge formation. A TOC reduction of 35-47% and UV-254 nm reduction of 24-38% was also observed. In addition to turbidity removal during flood periods, the ability to remove NOM using the pebble matrix filter throughout the year may have the benefit of reducing disinfection by-products (DBP) formation potential and coagulant demand at water treatment plants. Final head losses were remarkably low, reaching only 11 cm at a filtration velocity of 0.70 m/h.

Mechanical properties of nanodiamond-reinforced polymer-matrix composites

Poly(vinyl alcohol)-matrix reinforced with nanodiamond (ND) particles, with ND content up to 0.6 wt%, were synthesized. Characterization of the composites by transmission electron microscopy (TEM) and small angle X-ray scattering (SAXS) reveal uniform distribution of the ND particles with no agglomeration in the matrix. Differential scanning calorimetry reveals that the crystallinity of the polymer increases with increasing ND content, indicating a strong interaction between ND and PVA. Nano-indentation technique was employed to assess the mechanical properties of composites. Results show that even small additions of ND lead to significant enhancement in the hardness and elastic modulus of PVA. Possible micromechanisms responsible for the enhancement of the mechanical properties are discussed.

Velocity ratio-cum-transfer matrix method for the evaluation of a muffler with mean flow

The paper deals with a method for the evaluation of exhaust muffers with mean flow. A new set of variables, convective pressure and convective mass velocity, have been defined to replace the acoustic variables. An expression for attenuation (insertion loss) of a muffler has been proposed in terms of convective terminal impedances and a velocity ratio, on the lines of the one existing for acoustic filters. In order to evaluate the velocity ratio in terms of convective variables, transfer matrices for various muffler elements have been derived from the basic relations of energy, mass and momentum. Finally, the velocity ratiocum-transfer matrix method is illustrated for a typical straight-through muffler.

On the transfer matrix for a uniform tube with a moving medium

Abstract is not available.

Optimal iterative schemes for computing the Moore-Penrose matrix inverse

Among the iterative schemes for computing the Moore — Penrose inverse of a woll-conditioned matrix, only those which have an order of convergence three or two are computationally efficient. A Fortran programme for these schemes is provided.

Rank-Augmented LU-Algorithm for Computing Generalized Matrix Inverses

A rank-augmnented LU-algorithm is suggested for computing a generalized inverse of a matrix. Initially suitable diagonal corrections are introduced in (the symmetrized form of) the given matrix to facilitate decomposition; a backward-correction scheme then yields a desired generalized inverse.

Co-Signaling by Neurotrophic Factors and the Extracellular Matrix for Axonal Growth and Neuronal Survival

Neurotrophic factors (NTFs) and the extracellular matrix (ECM) are important regulators of axonal growth and neuronal survival in mammalian nervous system. Understanding of the mechanisms of this regulation is crucial for the development of posttraumatic therapies and drug intervention in the injured nervous system. NTFs act as soluble, target-derived extracellular regulatory molecules for a wide range of physiological functions including axonal guidance and the regulation of programmed cell death in the nervous system. The ECM determines cell adhesion and regulates multiple physiological functions via short range cell-matrix interactions. The present work focuses on the mechanisms of the action of NTFs and the ECM on axonal growth and survival of cultured sensory neurons from dorsal root ganglia (DRG). We first examined signaling mechanisms of the action of the glial cell line-derived neurotrophic factor (GDNF) family ligands (GFLs) on axonal growth. GDNF, neurturin (NRTN) and artemin (ART) but not persephin (PSPN) promoted axonal initiation in cultured DRG neurons from young adult mice. This effect required Src family kinase (SFK) activity. In neurons from GFRalpha2-deficient mice, NRTN did not significantly promote axonal initiation. GDNF and NRTN induced extensive lamellipodia formation on neuronal somata and growth cones. This study suggested that GDNF, NRTN and ARTN may serve as stimulators of nerve regeneration under posttraumatic conditions. Consequently we studied the convergence of signaling pathways induced by NTFs and the ECM molecule laminin in the intracellular signaling network that regulates axonal growth. We demonstrated that co-stimulation of DRG neurons with NTFs (GDNF, NRTN or nerve growth factor (NGF)) and laminin leads to axonal growth that requires activation of SFKs. A different, SFK-independent signaling pathway evoked axonal growth on laminin in the absence of the NTFs. In contrast, axonal branching was regulated by SFKs both in the presence and in the absence of NGF. We proposed and experimentally verified a Boolean model of the signaling network triggered by NTFs and laminin. Our results put forward an approach for predictable, Boolean logics-driven pharmacological manipulation of a complex signaling network. Finally we found that N-syndecan, the receptor for the ECM component HB-GAM was required for the survival of neonatal sensory neurons in vitro. We demonstrated massive cell death of cultured DRG neurons from mice deficient in the N-syndecan gene as compared to wild type controls. Importantly, this cell death could not be prevented by NGF the neurotrophin which activates multiple anti-apoptotic cascades in DRG neurons. The survival deficit was observed during first postnatal week. By contrast, DRG neurons from young adult N-syndecan knock-out mice exhibited normal survival. This study identifies a completely new syndecan-dependent type of signaling that regulates cell death in neurons.

Regulation of extracellular matrix genes by arecoline in primary gingival fibroblasts requires epithelial factors

Background and Objective: Oral submucous fibrosis, a disease of collagen disorder, has been attributed to arecoline present in the saliva of betel quid chewers. However, the molecular basis of the action of arecoline in the pathogenesis of oral submucous fibrosis is poorly understood. The basic aim of our study was to elucidate the mechanism underlying the action of arecoline on the expression of genes in oral fibroblasts. Material and Methods: Human keratinocytes (HaCaT cells) and primary human gingival fibroblasts were treated with arecoline in combination with various pathway inhibitors, and the expression of transforming growth factor-beta isoform genes and of collagen isoforms was assessed using reverse transcription polymerase chain reaction analysis. Results: We observed the induction of transforming growth factor-beta2 by arecoline in HaCaT cells and this induction was found to be caused by activation of the M-3 muscarinic acid receptor via the induction of calcium and the protein kinase C pathway. Most importantly, we showed that transforming growth factor-beta2 was significantly overexpressed in oral submucous fibrosis tissues (p = 0.008), with a median of 2.13 (n = 21) compared with 0.75 (n = 18) in normal buccal mucosal tissues. Furthermore, arecoline down-regulated the expression of collagens 1A1 and 3A1 in human primary gingival fibroblasts; however these collagens were induced by arecoline in the presence of spent medium of cultured human keratinocytes. Treatment with a transforming growth factor-beta blocker, transforming growth factor-beta1 latency-associated peptide, reversed this up-regulation of collagen, suggesting a role for profibrotic cytokines, such as transforming growth factor-beta, in the induction of collagens. Conclusion: Taken together, our data highlight the importance of arecoline-induced epithelial changes in the pathogenesis of oral submucous fibrosis.

A new mixed-matrix membrane for DMFCs

A new mixed-matrix membrane based on stabilized phosphotungstic acid (PTA) incorporated to chitosan (CS)-hydroxy ethyl cellulose (HEC) for application in direct methanol fuel cells (DMFCs) is reported. Membranes are characterised using Fourier Transform Spectroscopy (FTIR), Thermo-Gravimetric Analysis (TGA), Scanning Electron Microscopy (SEM) and their mechanical properties are evaluated. The PTA content in the CS-HEC blend and its influence on proton conductivity, water/methanol sorption, and methanol cross-over in the DMFC is studied. The DMFC with 3 wt. % stabilized PTA-CS-HEC mixed-matrix membrane delivers peak power-density of 58 mW/cm(2) at a load current-density of 210 mA/cm(2) with a lower methanol cross-over than that observed for a DMFC operating with a Nafion membrane electrolyte.