Geometric integration applied to moving mesh methods and degenerate Lagrangians

Moving mesh methods (also called r-adaptive methods) are space-adaptive strategies used for the numerical simulation of time-dependent partial differential equations. These methods keep the total number of mesh points fixed during the simulation, but redistribute them over time to follow the areas where a higher mesh point density is required. There are a very limited number of moving mesh methods designed for solving field-theoretic partial differential equations, and the numerical analysis of the resulting schemes is challenging. In this thesis we present two ways to construct r-adaptive variational and multisymplectic integrators for (1+1)-dimensional Lagrangian field theories. The first method uses a variational discretization of the physical equations and the mesh equations are then coupled in a way typical of the existing r-adaptive schemes. The second method treats the mesh points as pseudo-particles and incorporates their dynamics directly into the variational principle. A user-specified adaptation strategy is then enforced through Lagrange multipliers as a constraint on the dynamics of both the physical field and the mesh points. We discuss the advantages and limitations of our methods. The proposed methods are readily applicable to (weakly) non-degenerate field theories---numerical results for the Sine-Gordon equation are presented.

In an attempt to extend our approach to degenerate field theories, in the last part of this thesis we construct higher-order variational integrators for a class of degenerate systems described by Lagrangians that are linear in velocities. We analyze the geometry underlying such systems and develop the appropriate theory for variational integration. Our main observation is that the evolution takes place on the primary constraint and the 'Hamiltonian' equations of motion can be formulated as an index 1 differential-algebraic system. We then proceed to construct variational Runge-Kutta methods and analyze their properties. The general properties of Runge-Kutta methods depend on the 'velocity' part of the Lagrangian. If the 'velocity' part is also linear in the position coordinate, then we show that non-partitioned variational Runge-Kutta methods are equivalent to integration of the corresponding first-order Euler-Lagrange equations, which have the form of a Poisson system with a constant structure matrix, and the classical properties of the Runge-Kutta method are retained. If the 'velocity' part is nonlinear in the position coordinate, we observe a reduction of the order of convergence, which is typical of numerical integration of DAEs. We also apply our methods to several models and present the results of our numerical experiments.

Structure-Guided Design and Biophysical Characterization of Novel Anti-HIV Reagents

Despite over 30 years of effort, an HIV-1 vaccine that elicits protective antibodies still does not exist. Recent clinical studies have identified that during natural infection about 20% of the population is capable of mounting a potent and protective antibody response. Closer inspection of these individuals reveal that a subset of these antibodies, recently termed potent VRC01-like (PVL), derive exclusively from a single human germline heavy chain gene. Induced clonal expansion of the B cell encoding this gene is the first step through which PVL antibodies may be elicited. Unfortunately, naturally occurring HIV gp120s fail to bind to this germline, and as a result cannot be used as the initial prime for a vaccine regimen. We have determined the crystal structure of an important germline antibody that is a promising target for vaccine design efforts, and have set out to engineer a more likely candidate using computationally-guided rational design.

In addition to prevention efforts on the side of vaccine design, recently characterized broadly neutralizing anti-HIV antibodies have excellent potential for use in gene therapy and passive immunotherapy. The separation distance between functional Fabs on an antibody is important due to the sparse distribution of envelop spikes on HIV compared to other viruses. We set out to build and characterize novel antibody architectures by incorporating structured linkers into the hinge region of an anti-HIV antibody b12. The goal was to observe whether these linkers increased the arm-span of the IgG dimer. When incorporated, flexible Gly4Ser repeats did not result in detectable extensions of the IgG antigen binding domains, by contrast to linkers including more rigid domains such as β2-microglobulin, Zn-α2-glycoprotein, and tetratricopeptide repeats (TPRs). This study adds an additional set of linkers with varying lengths and rigidities to the available linker repertoire, which may be useful for the modification and construction of antibodies and other fusion proteins.

Design, synthesis and characterization of sequence-specific DNA-cleaving metalloproteins

This thesis describes research pursued in two areas, both involving the design and synthesis of sequence specific DNA-cleaving proteins. The first involves the use of sequence-specific DNA-cleaving metalloproteins to probe the structure of a protein-DNA complex, and the second seeks to develop cleaving moieties capable of DNA cleavage through the generation of a non-diffusible oxidant under physiological conditions.

Chapter One provides a brief review of the literature concerning sequence-specific DNA-binding proteins. Chapter Two summarizes the results of affinity cleaving experiments using leucine zipper-basic region (bZip) DNA-binding proteins. Specifically, the NH_2-terminal locations of a dimer containing the DNA binding domain of the yeast transcriptional activator GCN4 were mapped on the binding sites 5'-CTGACTAAT-3' and 5'ATGACTCTT- 3' using affinity cleaving. Analysis of the DNA cleavage patterns from Fe•EDTA-GCN4(222-281) and (226-281) dimers reveals that the NH_2-termini are in the major groove nine to ten base pairs apart and symmetrically displaced four to five base pairs from the central C of the recognition site. These data are consistent with structural models put forward for this class of DNA binding proteins. The results of these experiments are evaluated in light of the recently published crystal structure for the GCN4-DNA complex. Preliminary investigations of affinity cleaving proteins based on the DNA-binding domains of the bZip proteins Jun and Fos are also described.

Chapter Three describes experiments demonstrating the simultaneous binding of GCN4(226-281) and 1-Methylimidazole-2-carboxamide-netropsin (2-ImN), a designed synthetic peptide which binds in the minor groove of DNA at 5'-TGACT-3' sites as an antiparallel, side-by-side dimer. Through the use of Fe•EDTA-GCN4(226-281) as a sequence-specific footprinting agent, it is shown that the dimeric protein GCN4(226-281) and the dimeric peptide 2- ImN can simultaneously occupy their common binding site in the major and minor grooves of DNA, respectively. The association constants for 2-ImN in the presence and in the absence of Fe•EDTA-GCN4(226-281) are found to be similar, suggesting that the binding of the two dimers is not cooperative.

Chapter Four describes the synthesis and characterization of PBA-β-OH-His- Hin(139-190), a hybrid protein containing the DNA-binding domain of Hin recombinase and the putative iron-binding and oxygen-activating domain of the antitumor antibiotic bleomycin. This 54-residue protein, comprising residues 139-190 of Hin recombinase with the dipeptide pyrimidoblamic acid-β-hydroxy-L-histidine (PBA-β-OH-His) at the NH2 terminus, was synthesized by solid phase methods. PBA-β-OH-His-Hin(139- 190) binds specifically to DNA at four distinct Hin binding sites with affinities comparable to those of the unmodified Hin(139-190). In the presence of dithiothreitol (DTT), Fe•PB-β-OH-His-Hin(139-190) cleaves DNA with specificity remarkably similar to that of Fe•EDTA-Hin(139-190), although with lower efficiency. Analysis of the cleavage pattern suggests that DNA cleavage is mediated through a diffusible species, in contrast with cleavage by bleomycin, which occurs through a non-diffusible oxidant.

Transceiver designs and analysis for LTI, LTV and broadcast channels - new matrix decompositions and majorization theory

Signal processing techniques play important roles in the design of digital communication systems. These include information manipulation, transmitter signal processing, channel estimation, channel equalization and receiver signal processing. By interacting with communication theory and system implementing technologies, signal processing specialists develop efficient schemes for various communication problems by wisely exploiting various mathematical tools such as analysis, probability theory, matrix theory, optimization theory, and many others. In recent years, researchers realized that multiple-input multiple-output (MIMO) channel models are applicable to a wide range of different physical communications channels. Using the elegant matrix-vector notations, many MIMO transceiver (including the precoder and equalizer) design problems can be solved by matrix and optimization theory. Furthermore, the researchers showed that the majorization theory and matrix decompositions, such as singular value decomposition (SVD), geometric mean decomposition (GMD) and generalized triangular decomposition (GTD), provide unified frameworks for solving many of the point-to-point MIMO transceiver design problems.

In this thesis, we consider the transceiver design problems for linear time invariant (LTI) flat MIMO channels, linear time-varying narrowband MIMO channels, flat MIMO broadcast channels, and doubly selective scalar channels. Additionally, the channel estimation problem is also considered. The main contributions of this dissertation are the development of new matrix decompositions, and the uses of the matrix decompositions and majorization theory toward the practical transmit-receive scheme designs for transceiver optimization problems. Elegant solutions are obtained, novel transceiver structures are developed, ingenious algorithms are proposed, and performance analyses are derived.

The first part of the thesis focuses on transceiver design with LTI flat MIMO channels. We propose a novel matrix decomposition which decomposes a complex matrix as a product of several sets of semi-unitary matrices and upper triangular matrices in an iterative manner. The complexity of the new decomposition, generalized geometric mean decomposition (GGMD), is always less than or equal to that of geometric mean decomposition (GMD). The optimal GGMD parameters which yield the minimal complexity are derived. Based on the channel state information (CSI) at both the transmitter (CSIT) and receiver (CSIR), GGMD is used to design a butterfly structured decision feedback equalizer (DFE) MIMO transceiver which achieves the minimum average mean square error (MSE) under the total transmit power constraint. A novel iterative receiving detection algorithm for the specific receiver is also proposed. For the application to cyclic prefix (CP) systems in which the SVD of the equivalent channel matrix can be easily computed, the proposed GGMD transceiver has K/log_2(K) times complexity advantage over the GMD transceiver, where K is the number of data symbols per data block and is a power of 2. The performance analysis shows that the GGMD DFE transceiver can convert a MIMO channel into a set of parallel subchannels with the same bias and signal to interference plus noise ratios (SINRs). Hence, the average bit rate error (BER) is automatically minimized without the need for bit allocation. Moreover, the proposed transceiver can achieve the channel capacity simply by applying independent scalar Gaussian codes of the same rate at subchannels.

In the second part of the thesis, we focus on MIMO transceiver design for slowly time-varying MIMO channels with zero-forcing or MMSE criterion. Even though the GGMD/GMD DFE transceivers work for slowly time-varying MIMO channels by exploiting the instantaneous CSI at both ends, their performance is by no means optimal since the temporal diversity of the time-varying channels is not exploited. Based on the GTD, we develop space-time GTD (ST-GTD) for the decomposition of linear time-varying flat MIMO channels. Under the assumption that CSIT, CSIR and channel prediction are available, by using the proposed ST-GTD, we develop space-time geometric mean decomposition (ST-GMD) DFE transceivers under the zero-forcing or MMSE criterion. Under perfect channel prediction, the new system minimizes both the average MSE at the detector in each space-time (ST) block (which consists of several coherence blocks), and the average per ST-block BER in the moderate high SNR region. Moreover, the ST-GMD DFE transceiver designed under an MMSE criterion maximizes Gaussian mutual information over the equivalent channel seen by each ST-block. In general, the newly proposed transceivers perform better than the GGMD-based systems since the super-imposed temporal precoder is able to exploit the temporal diversity of time-varying channels. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD DFE transceiver is also proposed.

The third part of the thesis considers two quality of service (QoS) transceiver design problems for flat MIMO broadcast channels. The first one is the power minimization problem (min-power) with a total bitrate constraint and per-stream BER constraints. The second problem is the rate maximization problem (max-rate) with a total transmit power constraint and per-stream BER constraints. Exploiting a particular class of joint triangularization (JT), we are able to jointly optimize the bit allocation and the broadcast DFE transceiver for the min-power and max-rate problems. The resulting optimal designs are called the minimum power JT broadcast DFE transceiver (MPJT) and maximum rate JT broadcast DFE transceiver (MRJT), respectively. In addition to the optimal designs, two suboptimal designs based on QR decomposition are proposed. They are realizable for arbitrary number of users.

Finally, we investigate the design of a discrete Fourier transform (DFT) modulated filterbank transceiver (DFT-FBT) with LTV scalar channels. For both cases with known LTV channels and unknown wide sense stationary uncorrelated scattering (WSSUS) statistical channels, we show how to optimize the transmitting and receiving prototypes of a DFT-FBT such that the SINR at the receiver is maximized. Also, a novel pilot-aided subspace channel estimation algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) systems with quasi-stationary multi-path Rayleigh fading channels. Using the concept of a difference co-array, the new technique can construct M^2 co-pilots from M physical pilot tones with alternating pilot placement. Subspace methods, such as MUSIC and ESPRIT, can be used to estimate the multipath delays and the number of identifiable paths is up to O(M^2), theoretically. With the delay information, a MMSE estimator for frequency response is derived. It is shown through simulations that the proposed method outperforms the conventional subspace channel estimator when the number of multipaths is greater than or equal to the number of physical pilots minus one.

New directions in sparse sampling and estimation for underdetermined systems

A central objective in signal processing is to infer meaningful information from a set of measurements or data. While most signal models have an overdetermined structure (the number of unknowns less than the number of equations), traditionally very few statistical estimation problems have considered a data model which is underdetermined (number of unknowns more than the number of equations). However, in recent times, an explosion of theoretical and computational methods have been developed primarily to study underdetermined systems by imposing sparsity on the unknown variables. This is motivated by the observation that inspite of the huge volume of data that arises in sensor networks, genomics, imaging, particle physics, web search etc., their information content is often much smaller compared to the number of raw measurements. This has given rise to the possibility of reducing the number of measurements by down sampling the data, which automatically gives rise to underdetermined systems.

In this thesis, we provide new directions for estimation in an underdetermined system, both for a class of parameter estimation problems and also for the problem of sparse recovery in compressive sensing. There are two main contributions of the thesis: design of new sampling and statistical estimation algorithms for array processing, and development of improved guarantees for sparse reconstruction by introducing a statistical framework to the recovery problem.

We consider underdetermined observation models in array processing where the number of unknown sources simultaneously received by the array can be considerably larger than the number of physical sensors. We study new sparse spatial sampling schemes (array geometries) as well as propose new recovery algorithms that can exploit priors on the unknown signals and unambiguously identify all the sources. The proposed sampling structure is generic enough to be extended to multiple dimensions as well as to exploit different kinds of priors in the model such as correlation, higher order moments, etc.

Recognizing the role of correlation priors and suitable sampling schemes for underdetermined estimation in array processing, we introduce a correlation aware framework for recovering sparse support in compressive sensing. We show that it is possible to strictly increase the size of the recoverable sparse support using this framework provided the measurement matrix is suitably designed. The proposed nested and coprime arrays are shown to be appropriate candidates in this regard. We also provide new guarantees for convex and greedy formulations of the support recovery problem and demonstrate that it is possible to strictly improve upon existing guarantees.

This new paradigm of underdetermined estimation that explicitly establishes the fundamental interplay between sampling, statistical priors and the underlying sparsity, leads to exciting future research directions in a variety of application areas, and also gives rise to new questions that can lead to stand-alone theoretical results in their own right.

Analysis-aware design of embedded systems software

In the past many different methodologies have been devised to support software development and different sets of methodologies have been developed to support the analysis of software artefacts. We have identified this mismatch as one of the causes of the poor reliability of embedded systems software. The issue with software development styles is that they are ``analysis-agnostic.'' They do not try to structure the code in a way that lends itself to analysis. The analysis is usually applied post-mortem after the software was developed and it requires a large amount of effort. The issue with software analysis methodologies is that they do not exploit available information about the system being analyzed.

In this thesis we address the above issues by developing a new methodology, called "analysis-aware" design, that links software development styles with the capabilities of analysis tools. This methodology forms the basis of a framework for interactive software development. The framework consists of an executable specification language and a set of analysis tools based on static analysis, testing, and model checking. The language enforces an analysis-friendly code structure and offers primitives that allow users to implement their own testers and model checkers directly in the language. We introduce a new approach to static analysis that takes advantage of the capabilities of a rule-based engine. We have applied the analysis-aware methodology to the development of a smart home application.

Bright-field and fluorescence chip-scale microscopy for biological imaging

Optical microscopy is an essential tool in biological science and one of the gold standards for medical examinations. Miniaturization of microscopes can be a crucial stepping stone towards realizing compact, cost-effective and portable platforms for biomedical research and healthcare. This thesis reports on implementations of bright-field and fluorescence chip-scale microscopes for a variety of biological imaging applications. The term “chip-scale microscopy” refers to lensless imaging techniques realized in the form of mass-producible semiconductor devices, which transforms the fundamental design of optical microscopes.

Our strategy for chip-scale microscopy involves utilization of low-cost Complementary metal Oxide Semiconductor (CMOS) image sensors, computational image processing and micro-fabricated structural components. First, the sub-pixel resolving optofluidic microscope (SROFM), will be presented, which combines microfluidics and pixel super-resolution image reconstruction to perform high-throughput imaging of fluidic samples, such as blood cells. We discuss design parameters and construction of the device, as well as the resulting images and the resolution of the device, which was 0.66 µm at the highest acuity. The potential applications of SROFM for clinical diagnosis of malaria in the resource-limited settings is discussed.

Next, the implementations of ePetri, a self-imaging Petri dish platform with microscopy resolution, are presented. Here, we simply place the sample of interest on the surface of the image sensor and capture the direct shadow images under the illumination. By taking advantage of the inherent motion of the microorganisms, we achieve high resolution (~1 µm) imaging and long term culture of motile microorganisms over ultra large field-of-view (5.7 mm × 4.4 mm) in a specialized ePetri platform. We apply the pixel super-resolution reconstruction to a set of low-resolution shadow images of the microorganisms as they move across the sensing area of an image sensor chip and render an improved resolution image. We perform longitudinal study of Euglena gracilis cultured in an ePetri platform and image based analysis on the motion and morphology of the cells. The ePetri device for imaging non-motile cells are also demonstrated, by using the sweeping illumination of a light emitting diode (LED) matrix for pixel super-resolution reconstruction of sub-pixel shifted shadow images. Using this prototype device, we demonstrate the detection of waterborne parasites for the effective diagnosis of enteric parasite infection in resource-limited settings.

Then, we demonstrate the adaptation of a smartphone’s camera to function as a compact lensless microscope, which uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is also based on the image reconstruction with sweeping illumination technique, where the sequence of images are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. Image acquisition and reconstruction is performed on the device using a custom-built android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system.

Finally, we report on the implementation of fluorescence chip-scale microscope, based on a silo-filter structure fabricated on the pixel array of a CMOS image sensor. The extruded pixel design with metal walls between neighboring pixels successfully guides fluorescence emission through the thick absorptive filter to the photodiode layer of a pixel. Our silo-filter CMOS image sensor prototype achieves 13-µm resolution for fluorescence imaging over a wide field-of-view (4.8 mm × 4.4 mm). Here, we demonstrate bright-field and fluorescence longitudinal imaging of living cells in a compact, low-cost configuration.

Computational design of self-assembling proteins and protein-DNA nanowires

Computational protein design (CPD) is a burgeoning field that uses a physical-chemical or knowledge-based scoring function to create protein variants with new or improved properties. This exciting approach has recently been used to generate proteins with entirely new functions, ones that are not observed in naturally occurring proteins. For example, several enzymes were designed to catalyze reactions that are not in the repertoire of any known natural enzyme. In these designs, novel catalytic activity was built de novo (from scratch) into a previously inert protein scaffold. In addition to de novo enzyme design, the computational design of protein-protein interactions can also be used to create novel functionality, such as neutralization of influenza. Our goal here was to design a protein that can self-assemble with DNA into nanowires. We used computational tools to homodimerize a transcription factor that binds a specific sequence of double-stranded DNA. We arranged the protein-protein and protein-DNA binding sites so that the self-assembly could occur in a linear fashion to generate nanowires. Upon mixing our designed protein homodimer with the double-stranded DNA, the molecules immediately self-assembled into nanowires. This nanowire topology was confirmed using atomic force microscopy. Co-crystal structure showed that the nanowire is assembled via the desired interactions. To the best of our knowledge, this is the first example of a protein-DNA self-assembly that does not rely on covalent interactions. We anticipate that this new material will stimulate further interest in the development of advanced biomaterials.

High-strain composites and dual-matrix composite structures

Most space applications require deployable structures due to the limiting size of current launch vehicles. Specifically, payloads in nanosatellites such as CubeSats require very high compaction ratios due to the very limited space available in this typo of platform. Strain-energy-storing deployable structures can be suitable for these applications, but the curvature to which these structures can be folded is limited to the elastic range. Thanks to fiber microbuckling, high-strain composite materials can be folded into much higher curvatures without showing significant damage, which makes them suitable for very high compaction deployable structure applications. However, in applications that require carrying loads in compression, fiber microbuckling also dominates the strength of the material. A good understanding of the strength in compression of high-strain composites is then needed to determine how suitable they are for this type of application.

The goal of this thesis is to investigate, experimentally and numerically, the microbuckling in compression of high-strain composites. Particularly, the behavior in compression of unidirectional carbon fiber reinforced silicone rods (CFRS) is studied. Experimental testing of the compression failure of CFRS rods showed a higher strength in compression than the strength estimated by analytical models, which is unusual in standard polymer composites. This effect, first discovered in the present research, was attributed to the variation in random carbon fiber angles respect to the nominal direction. This is an important effect, as it implies that microbuckling strength might be increased by controlling the fiber angles. With a higher microbuckling strength, high-strain materials could carry loads in compression without reaching microbuckling and therefore be suitable for several space applications.

A finite element model was developed to predict the homogenized stiffness of the CFRS, and the homogenization results were used in another finite element model that simulated a homogenized rod under axial compression. A statistical representation of the fiber angles was implemented in the model. The presence of fiber angles increased the longitudinal shear stiffness of the material, resulting in a higher strength in compression. The simulations showed a large increase of the strength in compression for lower values of the standard deviation of the fiber angle, and a slight decrease of strength in compression for lower values of the mean fiber angle. The strength observed in the experiments was achieved with the minimum local angle standard deviation observed in the CFRS rods, whereas the shear stiffness measured in torsion tests was achieved with the overall fiber angle distribution observed in the CFRS rods.

High strain composites exhibit good bending capabilities, but they tend to be soft out-of-plane. To achieve a higher out-of-plane stiffness, the concept of dual-matrix composites is introduced. Dual-matrix composites are foldable composites which are soft in the crease regions and stiff elsewhere. Previous attempts to fabricate continuous dual-matrix fiber composite shells had limited performance due to excessive resin flow and matrix mixing. An alternative method, presented in this thesis uses UV-cure silicone and fiberglass to avoid these problems. Preliminary experiments on the effect of folding on the out-of-plane stiffness are presented. An application to a conical log-periodic antenna for CubeSats is proposed, using origami-inspired stowing schemes, that allow a conical dual-matrix composite shell to reach very high compaction ratios.

Design strategies for ultra-high efficiency photovoltaics

While concentrator photovoltaic cells have shown significant improvements in efficiency in the past ten years, once these cells are integrated into concentrating optics, connected to a power conditioning system and deployed in the field, the overall module efficiency drops to only 34 to 36%. This efficiency is impressive compared to conventional flat plate modules, but it is far short of the theoretical limits for solar energy conversion. Designing a system capable of achieving ultra high efficiency of 50% or greater cannot be achieved by refinement and iteration of current design approaches.

This thesis takes a systems approach to designing a photovoltaic system capable of 50% efficient performance using conventional diode-based solar cells. The effort began with an exploration of the limiting efficiency of spectrum splitting ensembles with 2 to 20 sub cells in different electrical configurations. Incorporating realistic non-ideal performance with the computationally simple detailed balance approach resulted in practical limits that are useful to identify specific cell performance requirements. This effort quantified the relative benefit of additional cells and concentration for system efficiency, which will help in designing practical optical systems.

Efforts to improve the quality of the solar cells themselves focused on the development of tunable lattice constant epitaxial templates. Initially intended to enable lattice matched multijunction solar cells, these templates would enable increased flexibility in band gap selection for spectrum splitting ensembles and enhanced radiative quality relative to metamorphic growth. The III-V material family is commonly used for multijunction solar cells both for its high radiative quality and for the ease of integrating multiple band gaps into one monolithic growth. The band gap flexibility is limited by the lattice constant of available growth templates. The virtual substrate consists of a thin III-V film with the desired lattice constant. The film is grown strained on an available wafer substrate, but the thickness is below the dislocation nucleation threshold. By removing the film from the growth substrate, allowing the strain to relax elastically, and bonding it to a supportive handle, a template with the desired lattice constant is formed. Experimental efforts towards this structure and initial proof of concept are presented.

Cells with high radiative quality present the opportunity to recover a large amount of their radiative losses if they are incorporated in an ensemble that couples emission from one cell to another. This effect is well known, but has been explored previously in the context of sub cells that independently operate at their maximum power point. This analysis explicitly accounts for the system interaction and identifies ways to enhance overall performance by operating some cells in an ensemble at voltages that reduce the power converted in the individual cell. Series connected multijunctions, which by their nature facilitate strong optical coupling between sub-cells, are reoptimized with substantial performance benefit.

Photovoltaic efficiency is usually measured relative to a standard incident spectrum to allow comparison between systems. Deployed in the field systems may differ in energy production due to sensitivity to changes in the spectrum. The series connection constraint in particular causes system efficiency to decrease as the incident spectrum deviates from the standard spectral composition. This thesis performs a case study comparing performance of systems over a year at a particular location to identify the energy production penalty caused by series connection relative to independent electrical connection.

Structure-, stereochemistry-, and metal-regulated DNA binding/cleaving molecules

In the cell, the binding of proteins to specific sequences of double helical DNA is essential for controlling the processes of protein synthesis (at the level of DNA transcription) and cell proliferation (at the level of DNA replication). In the laboratory, the sequence-specific DNA binding/cleaving properties of restriction endonuclease enzymes (secreted by microorganisms to protect them from foreign DNA molecules) have helped to fuel a revolution in molecular biology. The strength and specificity of a protein:DNA interaction depend upon structural features inherent to the protein and DNA sequences, but it is now appreciated that these features (and therefore protein:DNA complexation) may be altered (regulated) by other protein:DNA complexes, or by environmental factors such as temperature or the presence of specific organic molecules or inorganic ions. It is also now appreciated that molecules much smaller than proteins (including antibiotics of molecular weight less than 2000 and oligonucleotides) can bind to double-helical DNA in sequence-specific fashion. Elucidation of structural motifs and microscopic interactions responsible for the specific molecular recognition of DNA leads to greater understanding of natural processes and provides a basis for the design of novel sequence-specific DNA binding molecules. This thesis describes the synthesis and DNA binding/cleaving characteristics of molecules designed to probe structural, stereochemical, and environmental factors that regulate sequence-specific DNA recognition.

Chapter One introduces the DNA minor groove binding antibiotics Netropsin and Distamycin A, which are di- and tri(N-methylpyrrolecarboxamide) peptides, respectively. The method of DNA affinity cleaving, which has been employed to determine DNA binding properties of designed synthetic molecules is described. The design and synthesis of a series of Netropsin dimers linked in tail-to-tail fashion (by oxalic, malonic, succinic, or fumaric acid), or in head-to-tail fashion (by glycine, β-alanine, and γ-aminobutanoic acid (Gaba)) are presented. These Bis(Netropsin)s were appended with the iron-chelating functionality EDTA in order to make use of the technique of DNA affinity cleaving. Bis(Netropsin)-EDTA compounds are analogs of penta(N-methylpyrrolecarboxamide)-EDTA (P5E), which may be considered a head-to-tail Netropsin dimer linked by Nmethylpyrrolecarboxamide. Low- and high-resolution analysis of pBR322 DNA affinity cleaving by the iron complexes of these molecules indicated that small changes in the length and nature of the linker had significant effects on DNA binding/cleaving efficiency (a measure of DNA binding affinity). DNA binding/cleaving efficiency was found to decrease with changes in the linker in the order β-alanine > succinamide > fumaramide > N-methylpyrrolecarboxamide > malonamide >glycine, γ-aminobutanamide > oxalamide. In general, the Bis(Netropsin)-EDTA:Fe compounds retained the specificity for seven contiguous A:T base pairs characteristic of P5E:Fe binding. However, Bis(Netropsin)Oxalamide- EDTA:Fe exhibited decreased specificity for A:T base pairs, and Bis(Netropsin)-Gaba-EDT A:Fe exhibited some DNA binding sites of less than seven base pairs. Bis(Netropsin)s linked with diacids have C₂-symmmetrical DNA binding subunits and exhibited little DNA binding orientation preference. Bis(Netropsin)s linked with amino acids lack C₂-symmetrical DNA binding subunits and exhibited higher orientation preferences. A model for the high DNA binding orientation preferences observed with head-to-tail DNA minor groove binding molecules is presented.

Chapter Two describes the design, synthesis, and DNA binding properties of a series of chiral molecules: Bis(Netropsin)-EDTA compounds with linkers derived from (R,R)-, (S,S)-, and (RS,SR)-tartaric acids, (R,R)-, (S,S)-, and (RS,SR)-tartaric acid acetonides, (R)- and (S)-malic acids, N ,N-dimethylaminoaspartic acid, and (R)- and (S)-alanine, as well as three constitutional isomers in which an N-methylpyrrolecarboxamide (P1) subunit and a tri(N-methylpyrrolecarboxamide)-EDTA (P3-EDTA) subunit were linked by succinic acid, (R ,R)-, and (S ,S)-tartaric acids. DNA binding/cleaving efficiencies among this series of molecules and the Bis(Netropsin)s described in Chapter One were found to decrease with changes in the linker in the order β-alanine > succinamide > P1-succinamide-P3 > fumaramide > (S)-malicamide > N-methylpyrrolecarboxamide > (R)-malicamide > malonamide > N ,N-dimethylaminoaspanamide > glycine = Gaba = (S,S)-tartaramide = P1-(S,S)-tanaramide-P3 > oxalamide > (RS,SR)-tartaramide = P1- (R,R)-tanaramide-P3 > (R,R)-tartaramide (no sequence-specific DNA binding was detected for Bis(Netropsin)s linked by (R)- or (S)-alanine or by tartaric acid acetonides). The chiral molecules retained DNA binding specificity for seven contiguous A:T base pairs. From the DNA affinity cleaving data it could be determined that: 1) Addition of one or two substituents to the linker of Bis(Netropsin)-Succinamide resulted in stepwise decreases in DNA binding affinity; 2) molecules with single hydroxyl substituents bound DNA more strongly than molecules with single dimethylamino substituents; 3) hydroxyl-substituted molecules of (S) configuration bound more strongly to DNA than molecules of (R) configuration. This stereochemical regulation of DNA binding is proposed to arise from the inherent right-handed twist of (S)-enantiomeric Bis(Netropsin)s versus the inherent lefthanded twist of (R)-enantiomeric Bis(Netropsin)s, which makes the (S)-enantiomers more complementary to the right-handed twist of B form DNA.

Chapter Three describes the design and synthesis of molecules for the study of metalloregulated DNA binding phenomena. Among a series of Bis(Netropsin)-EDTA compounds linked by homologous tethers bearing four, five, or six oxygen atoms, the Bis(Netropsin) linked by a pentaether tether exhibited strongly enhanced DNA binding/cleaving in the presence of strontium or barium cations. The observed metallospecificity was consistent with the known affinities of metal cations for the cyclic hexaether 18-crown-6 in water. High-resolution DNA affinity cleaving analysis indicated that DNA binding by this molecule in the presence of strontium or barium was not only stronger but of different sequence-specificity than the (weak) binding observed in the absence of metal cations. The metalloregulated binding sites were consistent with A:T binding by the Netropsin subunits and G:C binding by a strontium or barium:pentaether complex. A model for the observed positive metalloregulation and novel sequence-specificity is presented. The effects of 44 different cations on DNA affinity cleaving by P5E:Fe were examined. A series of Bis(Netropsin)-EDTA compounds linked by tethers bearing two, three, four, or five amino groups was also synthesized. These molecules exhibited strong and specific binding to A:T rich regions of DNA. It was found that the iron complexes of these molecules bound and cleaved DNA most efficiently at pH 6.0-6.5, while P5E:Fe bound and cleaved most efficiently at pH 7.5-8.0. Incubating the Bis(Netropsin) Polyamine-EDTA:Fe molecules with K₂PdCl₄ abolished their DNA binding/cleaving activity. It is proposed that the observed negative metalloregulation arises from kinetically inert Bis(Netropsin) Polyamine:Pd(II) complexes or aggregates, which are sterically unsuitable for DNA complexation. Finally, attempts to produce a synthetic metalloregulated DNA binding protein are described. For this study, five derivatives of a synthetic 52 amino acid residue DNA binding/cleaving protein were produced. The synthetic mutant proteins carried a novel pentaether ionophoric amino acid residue at different positions within the primary sequence. The proteins did not exhibit significant DNA binding/cleaving activity, but they served to illustrate the potential for introducing novel amino acid residues within DNA binding protein sequences, and for the development of the tricyclohexyl ester of EDTA as a superior reagent for the introduction of EDT A into synthetic proteins.

Chapter Four describes the discovery and characterization of a new DNA binding/cleaving agent, [SalenMn(III)]OAc. This metal complex produces single- and double-strand cleavage of DNA, with specificity for A:T rich regions, in the presence of oxygen atom donors such as iodosyl benzene, hydrogen peroxide, or peracids. Maximal cleavage by [SalenMn(III)]OAc was produced at pH 6-7. A comparison of DNA singleand double-strand cleavage by [SalenMn(III)]⁺ and other small molecules (Methidiumpropyl-EDTA:Fe, Distamycin-EDTA:Fe, Neocarzinostatin, Bleomycin:Fe) is presented. It was found that DNA cleavage by [SalenMn(III)]⁺ did not require the presence of dioxygen, and that base treatment of DNA subsequent to cleavage by [SalenMn(III)]⁺ afforded greater cleavage and alterations in the cleavage patterns. Analysis of DNA products formed upon DNA cleavage by [SalenMn(III)] indicated that cleavage was due to oxidation of the sugar-phosphate backbone of DNA. Several mechanisms consistent with the observed products and reaction requirements are discussed.

Chapter Five describes progress on some additional studies. In one study, the DNA binding/cleaving specificities of Distamycin-EDTA derivatives bearing pyrrole N-isopropyl substituents were found to be the same as those of derivatives bearing pyrrole N-methyl substituents. In a second study, the design of and synthetic progress towards a series of nucleopeptide activators of transcription are presented. Five synthetic plasmids designed to test for activation of in vitro run-off transcription by DNA triple helix-forming oligonucleotides or nucleopeptides are described.

Chapter Six contains the experimental documentation of the thesis work.

Biological Activity of Rhodium Metalloinsertors and the Design of Bifunctional Conjugates

The Barton laboratory has established that octahedral rhodium complexes bearing the sterically expansive 5,6-chrysene diimine ligand can target thermodynamically destabilized sites, such as base pair mismatches, in DNA with high affinity and selectivity. These complexes approach DNA from the minor groove, ejecting the mismatched base pairs from the duplex in a binding mode termed metalloinsertion. In recent years, we have shown that these metalloinsertor complexes also exhibit cytotoxicity preferentially in cancer cells that are deficient in the mismatch repair (MMR) machinery.

Here, we establish that a sensitive structure-activity relationship exists for rhodium metalloinsertors. We studied the relationship between the chemical structures of metalloinsertors and their effect on biological activity for ten complexes with similar DNA binding affinities, but wide variation in their lipophilicity. Drastic differences were observed in the selectivities of the complexes for MMR-deficient cells. Compounds with hydrophilic ligands were highly selective, exhibiting preferential cytotoxicity in MMR-deficient cells at low concentrations and short incubation periods, whereas complexes with lipophilic ligands displayed poor cell-selectivity. It was discovered that all of the complexes localized to the nucleus in concentrations sufficient for mismatch binding; however, highly lipophilic complexes also exhibited high mitochondrial uptake. Significantly, these results support the notion that mitochondrial DNA is not the desired target for our metalloinsertor complexes; instead, selectivity stems from targeting mismatches in genomic DNA.

We have also explored the potential for metalloinsertors to be developed into more complex structures with multiple functionalities that could either enhance their overall potency or impart mismatch selectivity onto other therapeutic cargo. We have constructed a family of bifunctional metalloinsertor conjugates incorporating cis-platinum, each unique in its chemical structure, DNA binding interactions, and biological activity. The study of these complexes in MMR-deficient cells has established that the cell-selective biological activity of rhodium metalloinsertors proceeds through a critical cellular pathway leading to necrosis.

We further explored the underlying mechanisms surrounding the biological response to mismatch recognition by metalloinsertors in the genome. Immunofluorescence assays of MMR-deficient and MMR-proficient cells revealed that a critical biomarker for DNA damage, phosphorylation of histone H2AX (γH2AX) rapidly accumulates in response to metalloinsertor treatment, signifying the induction of double strand breaks in the genome. Significantly, we have discovered that our metalloinsertor complexes selectively inhibit transcription in MMR-deficient cells, which may be a crucial checkpoint in the eventual breakdown of the cell via necrosis. Additionally, preliminary in vivo studies have revealed the capability of these compounds to traverse the complex environments of multicellular organisms and accumulate in MMR-deficient tumors. Our ever-increasing understanding of metalloinsertors, as well as the development of new generations of complexes both monofunctional and bifunctional, enables their continued progress into the clinic as promising new chemotherapeutic agents.

Metaconcrete: Engineered aggregates for enhanced dynamic performance

This work presents the development and investigation of a new type of concrete for the attenuation of waves induced by dynamic excitation. Recent progress in the field of metamaterials science has led to a range of novel composites which display unusual properties when interacting with electromagnetic, acoustic, and elastic waves. A new structural metamaterial with enhanced properties for dynamic loading applications is presented, which is named metaconcrete. In this new composite material the standard stone and gravel aggregates of regular concrete are replaced with spherical engineered inclusions. Each metaconcrete aggregate has a layered structure, consisting of a heavy core and a thin compliant outer coating. This structure allows for resonance at or near the eigenfrequencies of the inclusions, and the aggregates can be tuned so that resonant oscillations will be activated by particular frequencies of an applied dynamic loading. The activation of resonance within the aggregates causes the overall system to exhibit negative effective mass, which leads to attenuation of the applied wave motion. To investigate the behavior of metaconcrete slabs under a variety of different loading conditions a finite element slab model containing a periodic array of aggregates is utilized. The frequency dependent nature of metaconcrete is investigated by considering the transmission of wave energy through a slab, which indicates the presence of large attenuation bands near the resonant frequencies of the aggregates. Applying a blast wave loading to both an elastic slab and a slab model that incorporates the fracture characteristics of the mortar matrix reveals that a significant portion of the supplied energy can be absorbed by aggregates which are activated by the chosen blast wave profile. The transfer of energy from the mortar matrix to the metaconcrete aggregates leads to a significant reduction in the maximum longitudinal stress, greatly improving the ability of the material to resist damage induced by a propagating shock wave. The various analyses presented in this work provide the theoretical and numerical background necessary for the informed design and development of metaconcrete aggregates for dynamic loading applications, such as blast shielding, impact protection, and seismic mitigation.

Fast numerical methods for mixed, singular Helmholtz boundary value problems and Laplace eigenvalue problems - with applications to antenna design, sloshing, electromagnetic scattering and spectral geometry

This thesis presents a novel class of algorithms for the solution of scattering and eigenvalue problems on general two-dimensional domains under a variety of boundary conditions, including non-smooth domains and certain "Zaremba" boundary conditions - for which Dirichlet and Neumann conditions are specified on various portions of the domain boundary. The theoretical basis of the methods for the Zaremba problems on smooth domains concern detailed information, which is put forth for the first time in this thesis, about the singularity structure of solutions of the Laplace operator under boundary conditions of Zaremba type. The new methods, which are based on use of Green functions and integral equations, incorporate a number of algorithmic innovations, including a fast and robust eigenvalue-search algorithm, use of the Fourier Continuation method for regularization of all smooth-domain Zaremba singularities, and newly derived quadrature rules which give rise to high-order convergence even around singular points for the Zaremba problem. The resulting algorithms enjoy high-order convergence, and they can tackle a variety of elliptic problems under general boundary conditions, including, for example, eigenvalue problems, scattering problems, and, in particular, eigenfunction expansion for time-domain problems in non-separable physical domains with mixed boundary conditions.

Algebraic Techniques in Coding Theory: Entropy Vectors, Frames, and Constrained Coding

The study of codes, classically motivated by the need to communicate information reliably in the presence of error, has found new life in fields as diverse as network communication, distributed storage of data, and even has connections to the design of linear measurements used in compressive sensing. But in all contexts, a code typically involves exploiting the algebraic or geometric structure underlying an application. In this thesis, we examine several problems in coding theory, and try to gain some insight into the algebraic structure behind them.

The first is the study of the entropy region - the space of all possible vectors of joint entropies which can arise from a set of discrete random variables. Understanding this region is essentially the key to optimizing network codes for a given network. To this end, we employ a group-theoretic method of constructing random variables producing so-called "group-characterizable" entropy vectors, which are capable of approximating any point in the entropy region. We show how small groups can be used to produce entropy vectors which violate the Ingleton inequality, a fundamental bound on entropy vectors arising from the random variables involved in linear network codes. We discuss the suitability of these groups to design codes for networks which could potentially outperform linear coding.

The second topic we discuss is the design of frames with low coherence, closely related to finding spherical codes in which the codewords are unit vectors spaced out around the unit sphere so as to minimize the magnitudes of their mutual inner products. We show how to build frames by selecting a cleverly chosen set of representations of a finite group to produce a "group code" as described by Slepian decades ago. We go on to reinterpret our method as selecting a subset of rows of a group Fourier matrix, allowing us to study and bound our frames' coherences using character theory. We discuss the usefulness of our frames in sparse signal recovery using linear measurements.

The final problem we investigate is that of coding with constraints, most recently motivated by the demand for ways to encode large amounts of data using error-correcting codes so that any small loss can be recovered from a small set of surviving data. Most often, this involves using a systematic linear error-correcting code in which each parity symbol is constrained to be a function of some subset of the message symbols. We derive bounds on the minimum distance of such a code based on its constraints, and characterize when these bounds can be achieved using subcodes of Reed-Solomon codes.