Nuclear incompressibility in the quasilocal density functional theory

We explore the ability of the recently established quasilocal density functional theory for describing the isoscalar giant monopole resonance. Within this theory we use the scaling approach and perform constrained calculations for obtaining the cubic and inverse energy weighted moments (sum rules) of the RPA strength. The meaning of the sum rule approach in this case is discussed. Numerical calculations are carried out using Gogny forces and an excellent agreement is found with HF+RPA results previously reported in literature. The nuclear matter compression modulus predicted in our model lies in the range 210230 MeV which agrees with earlier findings. The information provided by the sum rule approach in the case of nuclei near the neutron drip line is also discussed.

Density matrix functional theory that includes pairing correlations

The extension of density functional theory (DFT) to include pairing correlations without formal violation of the particle-number conservation condition is described. This version of the theory can be considered as a foundation of the application of existing DFT plus pairing approaches to atoms, molecules, ultracooled and magnetically trapped atomic Fermi gases, and atomic nuclei where the number of particles is conserved exactly. The connection with Hartree-Fock-Bogoliubov (HFB) theory is discussed, and the method of quasilocal reduction of the nonlocal theory is also described. This quasilocal reduction allows equations of motion to be obtained which are much simpler for numerical solution than the equations corresponding to the nonlocal case. Our theory is applied to the study of some even Sn isotopes, and the results are compared with those obtained in the standard HFB theory and with the experimental ones.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Effect of Amylase Producing Vibrios From the Benthic Environment on the Biodegradation of Low Density Polyethylene-Dextrin Blends

Low-density polyethylene was mixed with dextrin having different particle sizes (100, 200 and 300 mesh). Various compositions were prepared and their mechanical properties were evaluated and thermal studies have been carried out. Biodegradability of these samples has been checked using liquid culture medium containing Vibrios (an amylase producing bacteria), which were isolated from marine benthic environment. Soil burial test was done and reprocessability of these samples was evaluated. The results indicate that the newly prepared blends are reprocessable without sacrificing much of their mechanical properties. The biodegradability tests on these blends indicate that these are partially biodegradable

A New Gridding Technique for High Density Microarray Images Using Intensity Projection Profile of Best Sub Image

As the technologies for the fabrication of high quality microarray advances rapidly, quantification of microarray data becomes a major task. Gridding is the first step in the analysis of microarray images for locating the subarrays and individual spots within each subarray. For accurate gridding of high-density microarray images, in the presence of contamination and background noise, precise calculation of parameters is essential. This paper presents an accurate fully automatic gridding method for locating suarrays and individual spots using the intensity projection profile of the most suitable subimage. The method is capable of processing the image without any user intervention and does not demand any input parameters as many other commercial and academic packages. According to results obtained, the accuracy of our algorithm is between 95-100% for microarray images with coefficient of variation less than two. Experimental results show that the method is capable of gridding microarray images with irregular spots, varying surface intensity distribution and with more than 50% contamination

Rice husk ash – A valuable reinforcement for high density polyethylene

This paper presents the results of a study on the use of rice husk ash (RHA) for property modification of high density polyethylene (HDPE). Rice husk is a waste product of the rice processing industry. It is used widely as a fuel which results in large quantities of RHA. Here, the characterization of RHA has been done with the help of X-ray diffraction (XRD), Inductively Coupled Plasma Atomic Emission Spectroscopy (ICPAES), light scattering based particle size analysis, Fourier transform infrared spectroscopy (FTIR) and Scanning Electron Microscope (SEM). Most reports suggest that RHA when blended directly with polymers without polar groups does not improve the properties of the polymer substantially. In this study RHA is blended with HDPE in the presence of a compatibilizer. The compatibilized HDPE-RHA blend has a tensile strength about 18% higher than that of virgin HDPE. The elongation-at-break is also higher for the compatibilized blend. TGA studies reveal that uncompatibilized as well as compatibilized HDPERHA composites have excellent thermal stability. The results prove that RHA is a valuable reinforcing material for HDPE and the environmental pollution arising from RHA can be eliminated in a profitable way by this technique.

Characterization of Linear Low-Density Polyethylene/ Poly(vinyl alcohol) Blends and Their Biodegradability by Vibrio sp. Isolated from Marine Benthic Environment

Increasing amounts of plastic waste in the environment have become a problem of gigantic proportions. The case of linear low-density polyethylene (LLDPE) is especially significant as it is widely used for packaging and other applications. This synthetic polymer is normally not biodegradable until it is degraded into low molecular mass fragments that can be assimilated by microorganisms. Blends of nonbiodegradable polymers and biodegradable commercial polymers such as poly (vinyl alcohol) (PVA) can facilitate a reduction in the volume of plastic waste when they undergo partial degradation. Further, the remaining fragments stand a greater chance of undergoing biodegradation in a much shorter span of time. In this investigation, LLDPE was blended with different proportions of PVA (5–30%) in a torque rheometer. Mechanical, thermal, and biodegradation studies were carried out on the blends. The biodegradability of LLDPE/PVA blends has been studied in two environments: (1) in a culture medium containing Vibrio sp. and (2) soil environment, both over a period of 15 weeks. Blends exposed to culture medium degraded more than that exposed to soil environment. Changes in various properties of LLDPE/PVA blends before and after degradation were monitored using Fourier transform infrared spectroscopy, a differential scanning calorimeter (DSC) for crystallinity, and scanning electron microscope (SEM) for surface morphology among other things. Percentage crystallinity decreased as the PVA content increased and biodegradation resulted in an increase of crystallinity in LLDPE/PVA blends. The results prove that partial biodegradation of the blends has occurred holding promise for an eventual biodegradable product

Adrenergic and muscarinic receptor subtypes functional regulation during diabetogenesis: Effect of curcumin and vitamin D3 pre-treatment

In the present study, the initial phase was directed to confirm the effects of curcumin and vitamin D3 in preventing or delaying diabetes onset by studying the blood glucose and insulin levels in the pre-treated and diabetic groups. Behavioural studies were conducted to evaluate the cognitive and motor function in experimental rats. The major focus of the study was to understand the cellular and neuronal mechanisms that ensure the prophylactic capability of curcumin and vitamin D3. To elucidate the mechanisms involved in conferring the antidiabetogenesis effect, we examined the DNA and protein profiles using radioactive incorporation studies for DNA synthesis, DNA methylation and protein synthesis. Furthermore the gene expression studies of Akt-1, Pax, Pdx-1, Neuro D1, insulin like growth factor-1 and NF-κB were done to monitor pancreatic beta cell proliferation and differentiation. The antioxidant and antiapoptotic actions of curcumin and vitamin D3 were examined by studying the expression of antioxidant enzymes - SOD and GPx, and apoptotic mediators like Bax, caspase 3, caspase 8 and TNF-α. In order to understand the signalling pathways involved in curcumin and vitamin D3 action, the second messengers, cAMP, cGMP and IP3 were studied along with the expression of vitamin D receptor in the pancreas. The neuronal regulation of pancreatic beta cell maintenance, proliferation and insulin release was studied by assessing the adrenergic and muscarinic receptor functional regulation in the pancreas, brain stem, hippocampus and hypothalamus. The receptor number and binding affinity of total muscarinic, muscarinic M1, muscarinic M3, total adrenergic, α adrenergic and β adrenergic receptor subtypes were studied in pancreas, brain stem and hippocampus of experimental rats. The mRNA expression of muscarinic and adrenergic receptor subtypes were determined using Real Time PCR. Immunohistochemistry studies using confocal microscope were carried out to confirm receptor density and gene expression results. Cell signalling alterations in the pancreas and brain regions associated with diabetogenesis and antidiabetogenesis were assessed by examining the gene expression profiles of vitamin D receptor, CREB, phospholipase C, insulin receptor and GLUT. This study will establish the anti-diabetogenesis activity of curcumin and vitamin D3 pre-treatment and will attempt to understand the cellular, molecular and neuronal control mechanism in the onset of diabetes.Administration of MLD-STZ to curcumin and vitamin D3 pre-treated rats induced only an incidental prediabetic condition. Curcumin and vitamin D3 pretreated groups injected with MLD-STZ exhibited improved circulating insulin levels and behavioural responses when compared to MLD-STZ induced diabetic group. Activation of beta cell compensatory response induces an increase in pancreatic insulin output and beta cell mass expansion in the pre-treated group. Cell signalling proteins that regulate pancreatic beta cell survival, insulin release, proliferation and differentiation showed a significant increase in curcumin and vitamin D3 pre-treated rats. Marked decline in α2 adrenergic receptor function in pancreas helps to relent sympathetic inhibition of insulin release. Neuronal stimulation of hyperglycemia induced beta cell compensatory response is mediated by escalated signalling through β adrenergic, muscarinic M1 and M3 receptors. Pre-treatment mediated functional regulation of adrenergic and cholinergic receptors, key cell signalling proteins and second messengers improves pancreatic glucose sensing, insulin gene expression, insulin secretion, cell survival and beta cell mass expansion in pancreas. Curcumin and vitamin D3 pre-treatment induced modulation of adrenergic and cholinergic signalling in brain stem, hippocampus and hypothalamus promotes insulin secretion, beta cell compensatory response, insulin sensitivity and energy balance to resist diabetogenesis. Pre-treatment improved second messenger levels and the gene expression of intracellular signalling molecules in brain stem, hippocampus and hypothalamus, to retain a functional neuronal response to hyperglycemia. Curcumin and vitamin D3 protect pancreas and brain regions from oxidative stress by their indigenous antioxidant properties and by their ability to stimulate cellular free radical defence system. The present study demonstrates the role of adrenergic and muscarinic receptor subtypes functional regulation in curcumin and vitamin D3 mediated anti-diabetogenesis. This will have immense clinical significance in developing effective strategies to delay or prevent the onset of diabetes.

Modification of Polypropylene/High Density Polyethylene Blend Using Nanokaolinite Clay and E-Glass Fibre: Preparation, Characterization and Micromechanical Modelling

Upgrading two widely used standard plastics, polypropylene (PP) and high density polyethylene (HDPE), and generating a variety of useful engineering materials based on these blends have been the main objective of this study. Upgradation was effected by using nanomodifiers and/or fibrous modifiers. PP and HDPE were selected for modification due to their attractive inherent properties and wide spectrum of use. Blending is the engineered method of producing new materials with tailor made properties. It has the advantages of both the materials. PP has high tensile and flexural strength and the HDPE acts as an impact modifier in the resultant blend. Hence an optimized blend of PP and HDPE was selected as the matrix material for upgradation. Nanokaolinite clay and E-glass fibre were chosen for modifying PP/HDPE blend. As the first stage of the work, the mechanical, thermal, morphological, rheological, dynamic mechanical and crystallization characteristics of the polymer nanocomposites prepared with PP/HDPE blend and different surface modified nanokaolinite clay were analyzed. As the second stage of the work, the effect of simultaneous inclusion of nanokaolinite clay (both N100A and N100) and short glass fibres are investigated. The presence of nanofiller has increased the properties of hybrid composites to a greater extent than micro composites. As the last stage, micromechanical modeling of both nano and hybrid A composite is carried out to analyze the behavior of the composite under load bearing conditions. These theoretical analyses indicate that the polymer-nanoclay interfacial characteristics partially converge to a state of perfect interfacial bonding (Takayanagi model) with an iso-stress (Reuss IROM) response. In the case of hybrid composites the experimental data follows the trend of Halpin-Tsai model. This implies that matrix and filler experience varying amount of strain and interfacial adhesion between filler and matrix and also between the two fillers which play a vital role in determining the modulus of the hybrid composites.A significant observation from this study is that the requirement of higher fibre loading for efficient reinforcement of polymers can be substantially reduced by the presence of nanofiller together with much lower fibre content in the composite. Hybrid composites with both nanokaolinite clay and micron sized E-glass fibre as reinforcements in PP/HDPE matrix will generate a novel class of high performance, cost effective engineering material.

Development and applications of density matrix functional theory of generalized Hubbard Models

In dieser Doktorarbeit wird eine akkurate Methode zur Bestimmung von Grundzustandseigenschaften stark korrelierter Elektronen im Rahmen von Gittermodellen entwickelt und angewandt. In der Dichtematrix-Funktional-Theorie (LDFT, vom englischen lattice density functional theory) ist die Ein-Teilchen-Dichtematrix γ die fundamentale Variable. Auf der Basis eines verallgemeinerten Hohenberg-Kohn-Theorems ergibt sich die Grundzustandsenergie Egs[γgs] = min° E[γ] durch die Minimierung des Energiefunktionals E[γ] bezüglich aller physikalischer bzw. repräsentativer γ. Das Energiefunktional kann in zwei Beiträge aufgeteilt werden: Das Funktional der kinetischen Energie T[γ], dessen lineare Abhängigkeit von γ genau bekannt ist, und das Funktional der Korrelationsenergie W[γ], dessen Abhängigkeit von γ nicht explizit bekannt ist. Das Auffinden präziser Näherungen für W[γ] stellt die tatsächliche Herausforderung dieser These dar. Einem Teil dieser Arbeit liegen vorausgegangene Studien zu Grunde, in denen eine Näherung des Funktionals W[γ] für das Hubbardmodell, basierend auf Skalierungshypothesen und exakten analytischen Ergebnissen für das Dimer, hergeleitet wird. Jedoch ist dieser Ansatz begrenzt auf spin-unabhängige und homogene Systeme. Um den Anwendungsbereich von LDFT zu erweitern, entwickeln wir drei verschiedene Ansätze zur Herleitung von W[γ], die das Studium von Systemen mit gebrochener Symmetrie ermöglichen. Zuerst wird das bisherige Skalierungsfunktional erweitert auf Systeme mit Ladungstransfer. Eine systematische Untersuchung der Abhängigkeit des Funktionals W[γ] von der Ladungsverteilung ergibt ähnliche Skalierungseigenschaften wie für den homogenen Fall. Daraufhin wird eine Erweiterung auf das Hubbardmodell auf bipartiten Gittern hergeleitet und an sowohl endlichen als auch unendlichen Systemen mit repulsiver und attraktiver Wechselwirkung angewandt. Die hohe Genauigkeit dieses Funktionals wird aufgezeigt. Es erweist sich jedoch als schwierig, diesen Ansatz auf komplexere Systeme zu übertragen, da bei der Berechnung von W[γ] das System als ganzes betrachtet wird. Um dieses Problem zu bewältigen, leiten wir eine weitere Näherung basierend auf lokalen Skalierungseigenschaften her. Dieses Funktional ist lokal bezüglich der Gitterplätze formuliert und ist daher anwendbar auf jede Art von geordneten oder ungeordneten Hamiltonoperatoren mit lokalen Wechselwirkungen. Als Anwendungen untersuchen wir den Metall-Isolator-Übergang sowohl im ionischen Hubbardmodell in einer und zwei Dimensionen als auch in eindimensionalen Hubbardketten mit nächsten und übernächsten Nachbarn. Schließlich entwickeln wir ein numerisches Verfahren zur Berechnung von W[γ], basierend auf exakten Diagonalisierungen eines effektiven Vielteilchen-Hamilton-Operators, welcher einen von einem effektiven Medium umgebenen Cluster beschreibt. Dieser effektive Hamiltonoperator hängt von der Dichtematrix γ ab und erlaubt die Herleitung von Näherungen an W[γ], dessen Qualität sich systematisch mit steigender Clustergröße verbessert. Die Formulierung ist spinabhängig und ermöglicht eine direkte Verallgemeinerung auf korrelierte Systeme mit mehreren Orbitalen, wie zum Beispiel auf den spd-Hamilton-Operator. Darüber hinaus berücksichtigt sie die Effekte kurzreichweitiger Ladungs- und Spinfluktuationen in dem Funktional. Für das Hubbardmodell wird die Genauigkeit der Methode durch Vergleich mit Bethe-Ansatz-Resultaten (1D) und Quanten-Monte-Carlo-Simulationen (2D) veranschaulicht. Zum Abschluss wird ein Ausblick auf relevante zukünftige Entwicklungen dieser Theorie gegeben.

Multivariate Density Estimation: An SVM Approach

We formulate density estimation as an inverse operator problem. We then use convergence results of empirical distribution functions to true distribution functions to develop an algorithm for multivariate density estimation. The algorithm is based upon a Support Vector Machine (SVM) approach to solving inverse operator problems. The algorithm is implemented and tested on simulated data from different distributions and different dimensionalities, gaussians and laplacians in $R^2$ and $R^{12}$. A comparison in performance is made with Gaussian Mixture Models (GMMs). Our algorithm does as well or better than the GMMs for the simulations tested and has the added advantage of being automated with respect to parameters.

Risk Bounds for Mixture Density Estimation

In this paper we focus on the problem of estimating a bounded density using a finite combination of densities from a given class. We consider the Maximum Likelihood Procedure (MLE) and the greedy procedure described by Li and Barron. Approximation and estimation bounds are given for the above methods. We extend and improve upon the estimation results of Li and Barron, and in particular prove an $O(\\frac{1}{\\sqrt{n}})$ bound on the estimation error which does not depend on the number of densities in the estimated combination.

High Density Single Crystalline GaN Nanodot Arrays Fabricated Using Template-Assisted Selective Growth

High density, uniform GaN nanodot arrays with controllable size have been synthesized by using template-assisted selective growth. The GaN nanodots with average diameter 40nm, 80nm and 120nm were selectively grown by metalorganic chemical vapor deposition (MOCVD) on a nano-patterned SiO2/GaN template. The nanoporous SiO2 on GaN surface was created by inductively coupled plasma etching (ICP) using anodic aluminum oxide (AAO) template as a mask. This selective regrowth results in highly crystalline GaN nanodots confirmed by high resolution transmission electron microscopy. The narrow size distribution and uniform spatial position of the nanoscale dots offer potential advantages over self-assembled dots grown by the Stranski–Krastanow mode.

Hilbert space on probability density functions with Aitchison geometry

Compositional data analysis motivated the introduction of a complete Euclidean structure in the simplex of D parts. This was based on the early work of J. Aitchison (1986) and completed recently when Aitchinson distance in the simplex was associated with an inner product and orthonormal bases were identified (Aitchison and others, 2002; Egozcue and others, 2003). A partition of the support of a random variable generates a composition by assigning the probability of each interval to a part of the composition. One can imagine that the partition can be refined and the probability density would represent a kind of continuous composition of probabilities in a simplex of infinitely many parts. This intuitive idea would lead to a Hilbert-space of probability densities by generalizing the Aitchison geometry for compositions in the simplex into the set probability densities