Ordinary mod p representations of the metaplectic cover of p-adic SL_2

We classify the genuine ordinary mod p representations of the metaplectic group SL(2,F)-tilde, where F is a p-adic field, and compute its genuine mod p spherical and Iwahori Hecke algebras. The motivation is an interest in a possible correspondence between genuine mod p representations of SL(2,F)-tilde and mod p representations of the dual group PGL(2,F), so we also compare the two Hecke algebras to the mod p spherical and Iwahori Hecke algebras of PGL(2,F). We show that the genuine mod p spherical Hecke algebra of SL(2,F)-tilde is isomorphic to the mod p spherical Hecke algebra of PGL(2,F), and that one can choose an isomorphism which is compatible with a natural, though partial, correspondence of unramified ordinary representations via the Hecke action on their spherical vectors. We then show that the genuine mod p Iwahori Hecke algebra of SL(2,F)-tilde is a subquotient of the mod p Iwahori Hecke algebra of PGL(2,F), but that the two algebras are not isomorphic. This is in contrast to the situation in characteristic 0, where by work of Savin one can recover the local Shimura correspondence for representations generated by their Iwahori fixed vectors from an isomorphism of Iwahori Hecke algebras.

A genetic and biochemical analysis of pre-mRNA splicing in Saccharomyces cerevisiae

Pre-mRNA splicing requires interaction of cis- acting intron sequences with trans -acting factors: proteins and small nuclear ribonucleoproteins (snRNPs). The assembly of these factors into a large complex, the spliceosome, is essential for the subsequent two step splicing reaction. First, the 5' splice site is cleaved and free exon 1 and a lariat intermediate (intron- exon2) form. In the second reaction the 3' splice site is cleaved the exons ligated and lariat intron released. A combination of genetic and biochemical techniques have been used here to study pre-mRNA splicing in yeast.

Yeast introns have three highly conserved elements. We made point mutations within these elements and found that most of them affect splicing efficiency in vivo and in vitro, usually by inhibiting spliceosome assembly.

To study trans -acting splicing factors we generated and screened a bank of temperature- sensitive (ts) mutants. Eleven new complementation groups (prp17 to prp27) were isolated. The four phenotypic classes obtained affect different steps in splicing and accumulate either: 1) pre-mRNA, 2) lariat intermediate, 3) excised intron or 4) both pre-mRNA and intron. The latter three classes represent novel phenotypes. The excised intron observed in one mutant: prp26 is stabilized due to protection in a snRNP containing particle. Extracts from another mutant: prpl8 are heat labile and accumulate lariat intermediate and exon 1. This is especially interesting as it allows analysis of the second splicing reaction. In vitro complementation of inactivated prp18 extracts does not require intact snRNPs. These studies have also shown the mutation to be in a previously unknown splicing protein. A specific requirement for A TP is also observed for the second step of splicing. The PRP 18 gene has been cloned and its polyadenylated transcript identified.

Optimization of single attosecond x-ray pulses by genetic algorithm control of the chirp and initial phase of 5 fs laser pulses

We show that the peak intensity of single attosecond x-ray pulses is enhanced by 1 or 2 orders of magnitude, the pulse duration is greatly compressed, and the optimal propagation distance is shortened by genetic algorithm optimization of the chirp and initial phase of 5 fs laser pulses. However, as the laser intensity increases, more efficient nonadiabatic self-phase matching can lead to a dramatically enhanced harmonic yield, and the efficiency of optimization decreases in the enhancement and compression of the generated attosecond pulses. (c) 2006 Optical Society of America.

Optimal design of building structures using genetic algorithms

A general framework for multi-criteria optimal design is presented which is well-suited for automated design of structural systems. A systematic computer-aided optimal design decision process is developed which allows the designer to rapidly evaluate and improve a proposed design by taking into account the major factors of interest related to different aspects such as design, construction, and operation.

The proposed optimal design process requires the selection of the most promising choice of design parameters taken from a large design space, based on an evaluation using specified criteria. The design parameters specify a particular design, and so they relate to member sizes, structural configuration, etc. The evaluation of the design uses performance parameters which may include structural response parameters, risks due to uncertain loads and modeling errors, construction and operating costs, etc. Preference functions are used to implement the design criteria in a "soft" form. These preference functions give a measure of the degree of satisfaction of each design criterion. The overall evaluation measure for a design is built up from the individual measures for each criterion through a preference combination rule. The goal of the optimal design process is to obtain a design that has the highest overall evaluation measure - an optimization problem.

Genetic algorithms are stochastic optimization methods that are based on evolutionary theory. They provide the exploration power necessary to explore high-dimensional search spaces to seek these optimal solutions. Two special genetic algorithms, hGA and vGA, are presented here for continuous and discrete optimization problems, respectively.

The methodology is demonstrated with several examples involving the design of truss and frame systems. These examples are solved by using the proposed hGA and vGA.

Optimization of high-order harmonic by genetic algorithm for the chirp and phase of few-cycle pulses

The brightness of a particular harmonic order is optimized for the chirp and initial phase of the laser pulse by genetic algorithm. The influences of the chirp and initial phase of the excitation pulse on the harmonic spectra are discussed in terms of the semi-classical model including the propagation effects. The results indicate that the harmonic intensity and cutoff have strong dependence on the chirp of the laser pulse, but slightly on its initial phase. The high-order harmonics can be enhanced by the optimal laser pulse and its cutoff can be tuned by optimization of the chirp and initial phase of the laser pulse.

Optimal feedback control of two-photon fluorescence based on genetic algorithm

An optimal feedback control of two-photon fluorescence in the ethanol solution of 4-dicyanomethylene-2-methyl-6-p-dimethyl-amiiiostryryl-4H-pyran (DCM) using pulse-shaping technique based on genetic algorithm is demonstrated experimentally. The two-photon fluorescence of the DCM ethanol solution is enhanced in intensity of about 23%. The second harmonic generation frequency-resolved optical gating (SHG-FROG) trace indicates that the effective population transfer arises from the positively chirped pulse. The experimental results appear the potential applications of coherent control to the complicated molecular system.

Optimization of positions and currents of tokamak poloidal field coils using genetic algorithms

Plasma equilibrium geometry has a great influence on the confinement and magnetohydrodynamic stability in tokamaks. The poloidal field (PF) system of a tokamak should be optimized to support the prescribed plasma equilibrium geometry. In this paper, a genetic algorithm-based method is applied to solve the optimization of the positions and currents of tokamak PF coils. To achieve this goal, we first describe the free-boundary code EQT Based on the EQT code, a genetic algorithm-based method is introduced to the optimization. We apply this new method to the PF system design of the fusion-driven subcritical system and plasma equilibrium geometry optimization of the Experimental Advanced Superconducting Tokamak (EAST). The results indicate that the optimization of the plasma equilibrium geometry can be improved by using this method.

Optimal feedback control of two-photon fluorescence in Coumarin 515 based on genetic algorithm

An optimal feedback control of two-photon fluorescence in the Coumarin 515 ethanol solution excited by shaping femtosecond laser pulses based on genetic algorithm is demonstrated experimentally. The two-photon fluorescence intensity can be enhanced by similar to 20%. Second harmonic generation frequency-resolved optical gating traces indicate that the optimal laser pulses are positive chirp, which are in favor of the effective population transfer of two-photon transitions. The dependence of the two-photon fluorescence signal on the laser pulse chirp is investigated to validate the theoretical model for the effective population transfer of two-photon transitions. The experimental results appear the potential applications in nonlinear spectroscopy and molecular physics. (c) 2005 Elsevier B.V. All rights reserved.

Molecular genetic studies on voltage-gated ion channels

Several different methods have been employed in the study of voltage-gated ion channels. Electrophysiological studies on excitable cells in vertebrates and molluscs have shown that many different voltage-gated potassium (K⁺) channels and sodium channels may coexist in the same organism. Parallel genetic studies in Drosophila have identified mutations in several genes that alter the properties of specific subsets of physiologically identified ion channels. Chapter 2 describes molecular studies that identify two Drosophila homologs of vertebrate sodium-channel genes. Mutations in one of these Drosophila sodium-channel genes are shown to be responsible for the temperature-dependent paralysis of a behavioural mutant para^ts. Evolutionary arguments, based on the partial sequences of the two Drosophila genes, suggest that subfamilies of voltage-gated sodium channels in vertebrates remain to be identified.

In Drosophila, diverse voltage-gated K⁺ channels arise from alternatively spliced mRNAs generated at the Shaker locus. Chapter 3 and the Appendices describe the isolation and characterization of several human K⁺-channel genes, similar in sequence to Shaker. Each of these human genes has a highly conserved homolog in rodents; thus, this K⁺-channel gene family probably diversified prior to the mammalian radiation. Functional K⁺ channels encoded by these genes have been expressed in Xenopus oocytes and their properties have been analyzed by electrophysiological methods. These studies demonstrate that both transient and noninactivating voltage-gated K⁺ channels may be encoded by mammalian genes closely related to Shaker. In addition, results presented in Appendix 3 clearly demonstrate that independent gene products from two K⁺-channel genes may efficiently co-assemble into heterooligomeric K⁺ channels with properties distinct from either homomultimeric channel. This finding suggests yet another molecular mechanism for the generation of K⁺-channel diversity.

Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.

Constraining the interpretation of 2-methylhopanoids through genetic and phylogenetic methods

Hopanoids are a class of sterol-like lipids produced by select bacteria. Their preservation in the rock record for billions of years as fossilized hopanes lends them geological significance. Much of the structural diversity present in this class of molecules, which likely underpins important biological functions, is lost during fossilization. Yet, one type of modification that persists during preservation is methylation at C-2. The resulting 2-methylhopanoids are prominent molecular fossils and have an intriguing pattern over time, exhibiting increases in abundance associated with Ocean Anoxic Events during the Phanerozoic. This thesis uses diverse methods to address what the presence of 2-methylhopanes tells us about the microbial life and environmental conditions of their ancient depositional settings. Through an environmental survey of hpnP, the gene encoding the C-2 hopanoid methylase, we found that many different taxa are capable of producing 2-methylhopanoids in more diverse modern environments than expected. This study also revealed that hpnP is significantly overrepresented in organisms that are plant symbionts, in environments associated with plants, and with metabolisms that support plant-microbe interactions; collectively, these correlations provide a clue about the biological importance of 2-methylhopanoids. Phylogenetic reconstruction of the evolutionary history of hpnP revealed that 2-methylhopanoid production arose in the Alphaproteobacteria, indicating that the origin of these molecules is younger than originally thought. Additionally, we took genetic approach to understand the role of 2-methylhopanoids in Cyanobacteria using the filamentous symbiotic Nostoc punctiforme. We found that hopanoids likely aid in rigidifying the cell membrane but do not appear to provide resistance to osmotic or outer membrane stressors, as has been shown in other organisms. The work presented in this thesis supports previous findings that 2-methylhopanoids are not biomarkers for oxygenic photosynthesis and provides new insights by defining their distribution in modern environments, identifying their evolutionary origin, and investigating their role in Cyanobacteria. These efforts in modern settings aid the formation of a robust interpretation of 2-methylhopanes in the rock record.

Special Frobenius Traces in Galois Representations

This thesis studies Frobenius traces in Galois representations from two different directions. In the first problem we explore how often they vanish in Artin-type representations. We give an upper bound for the density of the set of vanishing Frobenius traces in terms of the multiplicities of the irreducible components of the adjoint representation. Towards that, we construct an infinite family of representations of finite groups with an irreducible adjoint action.

In the second problem we partially extend for Hilbert modular forms a result of Coleman and Edixhoven that the Hecke eigenvalues a_p of classical elliptical modular newforms f of weight 2 are never extremal, i.e., a_p is strictly less than 2[square root]p. The generalization currently applies only to prime ideals p of degree one, though we expect it to hold for p of any odd degree. However, an even degree prime can be extremal for f. We prove our result in each of the following instances: when one can move to a Shimura curve defined by a quaternion algebra, when f is a CM form, when the crystalline Frobenius is semi-simple, and when the strong Tate conjecture holds for a product of two Hilbert modular surfaces (or quaternionic Shimura surfaces) over a finite field.

Development of Microfluidic Devices with the Use of Nanotechnology to Aid in the Analysis of Biological Systems Including Membrane Protein Separation, Single Cell Analysis, and Genetic Markers

Computation technology has dramatically changed the world around us; you can hardly find an area where cell phones have not saturated the market, yet there is a significant lack of breakthroughs in the development to integrate the computer with biological environments. This is largely the result of the incompatibility of the materials used in both environments; biological environments and experiments tend to need aqueous environments. To help aid in these development chemists, engineers, physicists and biologists have begun to develop microfluidics to help bridge this divide. Unfortunately, the microfluidic devices required large external support equipment to run the device. This thesis presents a series of several microfluidic methods that can help integrate engineering and biology by exploiting nanotechnology to help push the field of microfluidics back to its intended purpose, small integrated biological and electrical devices. I demonstrate this goal by developing different methods and devices to (1) separate membrane bound proteins with the use of microfluidics, (2) use optical technology to make fiber optic cables into protein sensors, (3) generate new fluidic devices using semiconductor material to manipulate single cells, and (4) develop a new genetic microfluidic based diagnostic assay that works with current PCR methodology to provide faster and cheaper results. All of these methods and systems can be used as components to build a self-contained biomedical device.