Ground and Electronic Excited States from Pairing Matrix Fluctuation and Particle-Particle Random Phase Approximation

The accurate description of ground and electronic excited states is an important and challenging topic in quantum chemistry. The pairing matrix fluctuation, as a counterpart of the density fluctuation, is applied to this topic. From the pairing matrix fluctuation, the exact electron correlation energy as well as two electron addition/removal energies can be extracted. Therefore, both ground state and excited states energies can be obtained and they are in principle exact with a complete knowledge of the pairing matrix fluctuation. In practice, considering the exact pairing matrix fluctuation is unknown, we adopt its simple approximation --- the particle-particle random phase approximation (pp-RPA) --- for ground and excited states calculations. The algorithms for accelerating the pp-RPA calculation, including spin separation, spin adaptation, as well as an iterative Davidson method, are developed. For ground states correlation descriptions, the results obtained from pp-RPA are usually comparable to and can be more accurate than those from traditional particle-hole random phase approximation (ph-RPA). For excited states, the pp-RPA is able to describe double, Rydberg, and charge transfer excitations, which are challenging for conventional time-dependent density functional theory (TDDFT). Although the pp-RPA intrinsically cannot describe those excitations excited from the orbitals below the highest occupied molecular orbital (HOMO), its performances on those single excitations that can be captured are comparable to TDDFT. The pp-RPA for excitation calculation is further applied to challenging diradical problems and is used to unveil the nature of the ground and electronic excited states of higher acenes. The pp-RPA and the corresponding Tamm-Dancoff approximation (pp-TDA) are also applied to conical intersections, an important concept in nonadiabatic dynamics. Their good description of the double-cone feature of conical intersections is in sharp contrast to the failure of TDDFT. All in all, the pairing matrix fluctuation opens up new channel of thinking for quantum chemistry, and the pp-RPA is a promising method in describing ground and electronic excited states.

Linear Hyperspectral Unmixing Using L0-norm Approximations and Nonnegative Matrix Factorization

Spectral unmixing (SU) is a technique to characterize mixed pixels of the hyperspectral images measured by remote sensors. Most of the existing spectral unmixing algorithms are developed using the linear mixing models. Since the number of endmembers/materials present at each mixed pixel is normally scanty compared with the number of total endmembers (the dimension of spectral library), the problem becomes sparse. This thesis introduces sparse hyperspectral unmixing methods for the linear mixing model through two different scenarios. In the first scenario, the library of spectral signatures is assumed to be known and the main problem is to find the minimum number of endmembers under a reasonable small approximation error. Mathematically, the corresponding problem is called the $\ell_0$-norm problem which is NP-hard problem. Our main study for the first part of thesis is to find more accurate and reliable approximations of $\ell_0$-norm term and propose sparse unmixing methods via such approximations. The resulting methods are shown considerable improvements to reconstruct the fractional abundances of endmembers in comparison with state-of-the-art methods such as having lower reconstruction errors. In the second part of the thesis, the first scenario (i.e., dictionary-aided semiblind unmixing scheme) will be generalized as the blind unmixing scenario that the library of spectral signatures is also estimated. We apply the nonnegative matrix factorization (NMF) method for proposing new unmixing methods due to its noticeable supports such as considering the nonnegativity constraints of two decomposed matrices. Furthermore, we introduce new cost functions through some statistical and physical features of spectral signatures of materials (SSoM) and hyperspectral pixels such as the collaborative property of hyperspectral pixels and the mathematical representation of the concentrated energy of SSoM for the first few subbands. Finally, we introduce sparse unmixing methods for the blind scenario and evaluate the efficiency of the proposed methods via simulations over synthetic and real hyperspectral data sets. The results illustrate considerable enhancements to estimate the spectral library of materials and their fractional abundances such as smaller values of spectral angle distance (SAD) and abundance angle distance (AAD) as well.

Endonuclease Controlled Aggregation of Gold Nanoparticles for the Ultrasensitive Detection of Pathogenic Bacterial DNA

The development of an ultrasensitive biosensor for the low-cost and on-site detection of pathogenic DNA could transform detection capabilities within food safety, environmental monitoring and clinical diagnosis. Herein, we present an innovative approach exploiting endonuclease-controlled aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. The method utilizes RNA-functionalized AuNPs which form DNA-RNA heteroduplex structures through specific hybridization with target DNA. Once formed, the DNA-RNA heteroduplex is susceptible to RNAse H enzymatic cleavage of the RNA probe, allowing the target DNA to liberate and hybridize with another RNA probe. This continuously happens until all of the RNA probes are cleaved, leaving the nanoparticles unprotected and thus aggregated upon exposure to a high electrolytic medium. The assay is ultrasensitive, allowing the detection of target DNA at femtomolar level by simple spectroscopic analysis (40.7 fM and 2.45 fM as measured by UV-vis and dynamic light scattering (DLS), respectively). The target DNA spiked food matrix (chicken meat) is also successfully detected at a concentration of 1.2 pM (by UV-vis) or 18.0 fM (by DLS). In addition to the ultra-high sensitivity, the total analysis time of the assay is less than 3 hours, thus demonstrating its practicality for food analysis.

Evaluating New Matrix Pooled Testing Methods for Detecting HIV Treatment Failure with and without Covariate Information

Thesis (Master's)--University of Washington, 2016-08

Hierarchical Reconstruction Method for Solving Ill-posed Linear Inverse Problems

We present a detailed analysis of the application of a multi-scale Hierarchical Reconstruction method for solving a family of ill-posed linear inverse problems. When the observations on the unknown quantity of interest and the observation operators are known, these inverse problems are concerned with the recovery of the unknown from its observations. Although the observation operators we consider are linear, they are inevitably ill-posed in various ways. We recall in this context the classical Tikhonov regularization method with a stabilizing function which targets the specific ill-posedness from the observation operators and preserves desired features of the unknown. Having studied the mechanism of the Tikhonov regularization, we propose a multi-scale generalization to the Tikhonov regularization method, so-called the Hierarchical Reconstruction (HR) method. First introduction of the HR method can be traced back to the Hierarchical Decomposition method in Image Processing. The HR method successively extracts information from the previous hierarchical residual to the current hierarchical term at a finer hierarchical scale. As the sum of all the hierarchical terms, the hierarchical sum from the HR method provides an reasonable approximate solution to the unknown, when the observation matrix satisfies certain conditions with specific stabilizing functions. When compared to the Tikhonov regularization method on solving the same inverse problems, the HR method is shown to be able to decrease the total number of iterations, reduce the approximation error, and offer self control of the approximation distance between the hierarchical sum and the unknown, thanks to using a ladder of finitely many hierarchical scales. We report numerical experiments supporting our claims on these advantages the HR method has over the Tikhonov regularization method.

APP RERMS enriched matrix as an adhesion substrate for neuritic outgrowth

Specific domains can determine protein structural functional relationships. For the Alzheimer’s Amyloid Precursor Protein (APP) several domains have been described, both in its intracellular and extracellular fragments. Many functions have been attributed to APP including an important role in cell adhesion and cell to cell recognition. This places APP at key biological responses, including synaptic transmission. To fulfil these functions, extracellular domains take on added significance. The APP extracellular domain RERMS is in fact a likely candidate to be involved in the aforementioned physiological processes. A multidisciplinary approach was employed to address the role of RERMS. The peptide RERMS was crosslinked to PEG (Polyethylene glycol) and the reaction validated by FTIR (Fourier transform infrared spectrometry). FTIR proved to be the most efficient at validating this reaction because it requires only a drop of sample, and it gives information about the reactions occurred in a mixture. The data obtained consist in an infrared spectra of the sample, where peaks positions give information about the structure of the molecules, and the intensity of peaks is related to the concentration of the molecules. Subsequently substrates of PEG impregnated with RERMS were prepared and SH-SY5Y (human neuroblastoma cell line) cells were plated and differentiated on the latter. Several morphological alterations were clearly evident. The RERMS peptide provoked cells to take on a flatter appearance and the cytoskeletal architecture changed, with the appearance of stress fibres, a clear indicator of actin reorganization. Given that focal adhesions play a key role in determining cellular structure the latter were directly investigated. Focal adhesion kinase (FAK) is one of the most highly expressed proteins in the CNS (central nervous system) during development. It has been described to be crucial for radial migration of neurons. FAK can be localized in growth cones and mediated the response to attractive and repulsive cues during migration. One of the mechanisms by which FAK becomes active is by auto phosphorylation at tyrosine 397. It became clearly evident that in the presence of the RERMS peptide pFAK staining at focal adhesions intensified and more focal adhesions became apparent. Furthermore speckled structures in the nucleus, putatively corresponding to increased expression activity, also increased with RERMS. Taken together these results indicate that the RERMS domain in APP plays a critical role in determining cellular physiological responses. Here is suggested a model by which RERMS domain is recognized by integrins and mediate intracellular responses involving FAK, talin, actin filaments and vinculin. This mechanism probably is responsible for mediating cell adhesion and neurite outgrowth on neurons.

Alteration of the bone tissue material properties in type 1 diabetes mellitus: A Fourier transform infrared microspectroscopy study

International audience

Aluminum and iron can be deposited in the calcified matrix of bone exostoses.

International audience

Designing Hydrogels that Transform their Shape in Response to Molecular Cues

There has been considerable interest in developing shape-changing soft materials for potential applications in drug delivery, microfluidics and biosensing. These shape- changing materials are inspired by the morphological changes exhibited by plants in nature, such as the Venus flytrap. One specific class of shape-change is that from a flat sheet to a folded structure (e.g., a tube). Such “self-folding” materials are usually composed of polymer hydrogels, and these typically fold in response to external stimuli such as pH and temperature. In order to develop these hydrogels for the previously described applications, it is necessary to expand the range of triggers. The focus of this dissertation is the advancement of shape-changing polymer hydrogels that are sensitive to uncommon cues such as specific biomolecules (enzymes), the substrates for such enzymes, or specific multivalent cations. First, we describe a hybrid gel that responds to the presence of low concentrations of a class of enzymes known as matrix metalloproteinases (MMPs). The hybrid gel was created by utilizing photolithographic techniques to combine two or more gels with distinct chemical composition into the same material. Certain portions of the hybrid gel are composed of a biopolymer derivative with crosslinkable groups. The hybrid gel is flat in water; however, in the presence of MMPs, the regions containing the biopolymer are degraded and the flat sheet folds to form a 3D structure. We demonstrate that hydrogels with different patterns can transform into different 3D structures such as tubes, helices and pancakes. Furthermore, this shape change can be made to occur at physiological concentrations of enzymes. Next, we report a gel with two layers that undergoes a shape change in the presence of glucose. The enzyme glucose oxidase (GOx) is immobilized in one of the layers. GOx catalyzes the conversion of glucose to gluconic acid. The production of gluconic acid decreases the local pH. The decrease in local pH causes one of the layers to swell. As a result, the flat sheet folds to form a tube. The tube unfolds to form a flat sheet when it is transferred to a solution with no glucose present. Therefore, this biomolecule- triggered shape transformation is reversible, meaning the glucose sensing gel is reusable. Furthermore, this shape change only occurs in the presence of glucose and it does not occur in the presence of other small sugars such as fructose. In our final study, we report the shape change of a gel with two layers in the presence of multivalent ions such as Ca2+ and Sr2+. The gel consists of a passive layer and an active layer. The passive layer is composed of dimethylyacrylamide (DMAA), which does not interact with multivalent ions. The active layer consists of DMAA and the biopolymer alginate. In the presence of Ca2+ ions, the alginate chains crosslink and the active layer shrinks. As a result, the gel converts from a flat sheet to a folded tube. What is particularly unusual is the direction of folding. In most cases, when flat rectangular gels fold, they do so about their short-side. However, our gels typically fold about their long-side. We hypothesize that non-homogeneous swelling determines the folding axis.

A new method for conditioning stochastic groundwater flow models in fractured media

Many geological formations consist of crystalline rocks that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. This is the process where the values of fracture transmissivities in a model are adjusted to obtain a good fit of the calculated pressures to measured pressure values. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium there is little literature on conditioning fracture networks. Conditioning fracture transmissivities on pressure or flow values is a complex problem because the measurements are not linearly related to the fracture transmissivities and they are also dependent on all the fracture transmissivities in the network. We present a new method for conditioning fracture transmissivities on measured pressure values based on the calculation of certain basis vectors; each basis vector represents the change to the log transmissivity of the fractures in the network that results in a unit increase in the pressure at one measurement point whilst keeping the pressure at the remaining measurement points constant. The fracture transmissivities are updated by adding a linear combination of basis vectors and coefficients, where the coefficients are obtained by minimizing an error function. A mathematical summary of the method is given. This algorithm is implemented in the existing finite element code ConnectFlow developed and marketed by Serco Technical Services, which models groundwater flow in a fracture network. Results of the conditioning are shown for a number of simple test problems as well as for a realistic large scale test case.

Voltage and current spectra for matrix power converters

Matrix power converters are used for transforming one alternating-current power supply to another, with different peak voltage and frequency. There are three input lines, with sinusoidally varying voltages which are 120◦ out of phase one from another, and the output is to be delivered as a similar three-phase supply. The matrix converter switches rapidly, to connect each output line in sequence to each of the input lines in an attempt to synthesize the prescribed output voltages. The switching is carried out at high frequency and it is of practical importance to know the frequency spectra of the output voltages and of the input and output currents. We determine in this paper these spectra using a new method, which has significant advantages over the prior default method (a multiple Fourier series technique), leading to a considerably more direct calculation. In particular, the determination of the input current spectrum is feasible here, whereas it would be a significantly more daunting procedure using the prior method instead.

Síntese hidrotérmica assistida por micro-ondas de tiO2, e aplicação em nanocompósito

In recent decades have seen a sharp growth in the study area of nanoscience and nanotechnology and is included in this area, the study of nanocomposites with self-cleaning properties. Since titanium dioxide (TiO2) has high photocatalytic activity and also antimicrobial, self-cleaning surfaces in your application has been explored. In this study a comparison was made between two synthesis routes to obtain TiO2 nanoparticles by hydrothermal method assisted by microwave. And after analysis of XRD and SEM was considered the best material for use in nanocomposites. It was deposited nanocomposite film of poly (dimethyl siloxane) (PDMS) with 0.5, 1, 1.5 and 2% by weight of nanoparticles of titanium dioxide (TiO2) by the spraying method. The nanocomposite was diluted with hexane and the suspension was deposited onto glass substrate, followed by curing in an oven with forced air circulation. The photocatalytic activity of the nanocomposite impregnated with methylene blue was evaluated by UV- vis spectroscopy from the intensity variation of absorption main peak at 660nm with time of exposure to the UV chamber. Changes in the contact angle and microhardness were analyzed before and after UV aging test. The effect of ultraviolet radiation on the chemical structure of the PDMS matrix was evaluated by spectrophotometry Fourier transform infrared (FTIR).The results indicated that the addition of TiO2 nanoparticles in the coating PDMS gave high photocatalytic activity in the decomposition of methylene blue, an important characteristic for the development of self-cleaning coatings

The effect of sample and sample matrix on DNA processing: Mechanisms for the detection and management of inhibition in forensic samples

The presence of inhibitory substances in biological forensic samples has, and continues to affect the quality of the data generated following DNA typing processes. Although the chemistries used during the procedures have been enhanced to mitigate the effects of these deleterious compounds, some challenges remain. Inhibitors can be components of the samples, the substrate where samples were deposited or chemical(s) associated to the DNA purification step. Therefore, a thorough understanding of the extraction processes and their ability to handle the various types of inhibitory substances can help define the best analytical processing for any given sample. A series of experiments were conducted to establish the inhibition tolerance of quantification and amplification kits using common inhibitory substances in order to determine if current laboratory practices are optimal for identifying potential problems associated with inhibition. DART mass spectrometry was used to determine the amount of inhibitor carryover after sample purification, its correlation to the initial inhibitor input in the sample and the overall effect in the results. Finally, a novel alternative at gathering investigative leads from samples that would otherwise be ineffective for DNA typing due to the large amounts of inhibitory substances and/or environmental degradation was tested. This included generating data associated with microbial peak signatures to identify locations of clandestine human graves. Results demonstrate that the current methods for assessing inhibition are not necessarily accurate, as samples that appear inhibited in the quantification process can yield full DNA profiles, while those that do not indicate inhibition may suffer from lowered amplification efficiency or PCR artifacts. The extraction methods tested were able to remove >90% of the inhibitors from all samples with the exception of phenol, which was present in variable amounts whenever the organic extraction approach was utilized. Although the results attained suggested that most inhibitors produce minimal effect on downstream applications, analysts should practice caution when selecting the best extraction method for particular samples, as casework DNA samples are often present in small quantities and can contain an overwhelming amount of inhibitory substances.^

The study of thermal stresses in a single long elastic fiber embedded in an infinite matrix

This work considered the micro-mechanical behavior of a long fiber embedded in an infinite matrix. Using the theory of elasticity, the idea of boundary layer and some simplifying assumptions, an approximate analytical solution was obtained for the normal and shear stresses along the fiber. The analytical solution to the problem was found for the case when the length of the embedded fiber is much greater than its radius, and the Young's modulus of the matrix was much less than that of the fiber. The analytical solution was then compared with a numerical solution based on Finite Element Analysis (FEA) using ANSYS. The numerical results showed the same qualitative behavior of the analytical solution, serving as a validation tool against lack of experimental results. In general this work provides a simple method to determine the thermal stresses along the fiber embedded in a matrix, which is the foundation for a better understanding of the interaction between the fiber and matrix in the case of the classical problem of thermal-stresses.