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Evolutionarily conserved Pumilio (Pum) RNA-binding proteins act as translational repressors during embryo development and cell fate specification. Previous work in the lab has shown that over-expression of Pum2 (Pum2-EML) supports maintenance and suppresses mutilineage differentiation of murine multipotent HSC/MPP-like cell line EML. The subsequent analysis of HSC markers and functional analysis has revealed that wt EML cells share the LKS CD34 positive phenotype, whereas the majority Pum2-EML cells are similar to LKS CD34 negative. The CD34 positive wt EML cells can be divided into CD34low, CD34med and CD34high subpopulations, whereas Pum2-EML CD34 positive cells correspond to CD34low subpopulation. Colony forming assays have revealed that the overall multilineage differentiation of wt EML and Pum2-EML cells strongly correlates with the CD34 expression levels. Multiple experiments have revealed that purified CD34 negative and CD34 positive wt EML cells can generate each other and among CD34 positive wt EML cells the CD34low cells have the highest capacity to give rise to CD34 negative EML cells. We have proposed a model in which CD34 negative EML cells are more primitive cells in an "inactive" (differentiation inhibited) state, that give rise to CD3low "active" (differentiation ready) EML cells. The CD34low EML cells can revert back to the CD34 negative state or give rise to CD34med/high cells that can readily differentiate into multiple lineages. Based on that model, the over-expression of Pum2 leads to increased maintenance of cells in inactive CD34 negative state, and blocks development of CD34 positive cells past the CD34low stage. Cumulatively, these results support the notions that Pum2 could be involved in maintaining the balance between inactive and active state of multipotent hematopoietic cells. The c-kit receptor plays a vital role in self-renewal and differentiation of hematopoietic stem cells (HSC) and multipotent progenitors (MPPs). We have discovered that besides c-kit, the murine multipotent HSC/MPP-like cell line EML expresses the transcript and protein for a truncated form of c-kit, called tr-kit. Notably, the tr-kit transcript and protein levels were down-regulated during cytokine induced differentiation of HSC/MPP-like cell line EML into myelo-erythroid lineages. RT-PCR results show tr-kit is transcribed solely in cell populations enriched for LTR-HSC, STR-HSC and MPPs. The observation that tr-kit is co-expressed with c-kit only in more primitive, HSC and MPP-enriched cell populations raises an exciting possibility that tr-kit functions either as a new component of SCF/c-kit pathway, or is involved in a novel signaling pathway, present exclusively in HSC and MPPs. These findings necessitate functional characterization of tr-kit, and analysis of its potential role in the self-renewal, proliferation and/or differentiation of HSC and multipotent progenitors.

With the portable computing devices and wireless communication systems are popularly used, the power consumption became one of the major targets of VLSI design. However, multiplier is always a fundamental component and influences the power consumption and performance much in many DSP and multimedia applications. Therefore, multiplier is the crucial design and need to be concerned at first. In these systems, the data width of input data is various because the different applications are operated in the same system. According to this characteristic of input data, this paper presents architecture of reconfigurable multiplier without the necessity to completely reconfigure the internal layout of a programmable device. The multiplier employs the Booth algorithm which reduces the partial products to half to implement the sign multiplication. In order to reduce power consumption, the proposed multiplier introduces the clock gating technique to disable the circuit which does not need to be computed. Moreover, the energy-efficient multiplier presented in this thesis can perform multiplication with different data widths to further decrease power dissipation and enhance performance. In this work, we proposed two versions of multipliers. The first version is reconfigurable pipelined Booth multiplier, which can perform one n by n multiplication or two n/2 by n/2 multiplications concurrently. When the multiplier performs n-bit multiplication, it can reduce power consumption by disabling the unnecessary blocks according to the input data. The second version further deploys the truncated functionality to provide different way to make multiplication more energy-efficient. Experiment shows that the proposed multipliers can perform multiplication with less energy and lower power dissipation. It is certain that the more functions the design provides, the more area it will cost.

Prevalence is a valuable epidemiological measure about the burden of disease in a community for planning health services; however, true prevalence is typically underestimated and there exists no reliable method of confirming the estimate of this prevalence in question. This thesis studies imprecise priors for the development of a statistical reasoning framework regarding this epidemiological decision making problem. The concept of imprecise probabilities introduced by Walley (1991) is adopted for the construction of this inferential framework in order to model prior ignorance and quantify the degree of imprecision associated with the inferential process. The study is restricted to the standard and zero-truncated Poisson sampling models that give an exponential family with a canonical log-link function because of the mechanism involved with the estimation of population size. A three-parameter exponential family of posteriors which includes the normal and log-gamma as limiting cases is introduced by applying normal priors on the canonical parameter of the Poisson sampling models. The canonical parameters simplify dealing with families of priors as Bayesian updating corresponds to a translation of the family in the canonical hyperparameter space. The canonical link function creates a linear relationship between regression coefficients of explanatory variables and the canonical parameters of the sampling distribution. Thus, normal priors on the regression coefficients induce normal priors on the canonical parameters leading to a higher-dimensional exponential family of posteriors whose limiting cases are again normal or log-gamma. All of these implementations are synthesized to build the ipeglim package (Lee, 2013) that provides a convenient method for characterizing imprecise probabilities and visualizing their translation, soft-linearity, and focusing behaviours. A characterization strategy for imprecise priors is introduced for instances when there exists a state of complete ignorance. The learning process of an individual intentional unit, the agreement process between several intentional units, and situations concerning prior-data conflict are graphically illustrated. Finally, the methodology is applied for re-analyzing the data collected from the epidemiological disease surveillance of three specific cases – Cholera epidemic (Dahiya, 1973), Down’s syndrome (Zelterman, 1988), and the female users of methamphetamine and heroin (B ̈ ohning, 2009).

No description available.

We develop a datapath generator for various arithmetic function units required in the design of the geometry subsystem in the 3D graphics application. The operations considered in the geometry subsystem include coordinate transformations and lighting. The generator will automatically generate efficient designs of function units based on the requirements of area, speed and accuracy. The major function units designed in this thesis are divided into two parts: multiplier-related function units and single-value arithmetic function units. In the generation of multipliers, we consider the design of truncated multipliers to reduce the area cost. In the design of other function evaluators, we consider two table-based methods: piecewise interpolation table-based method and the multipartite table-based method.

The ability to rationally or randomly modify proteins has expanded their employment in various bioanalytical applications. The bioluminescent protein, aequorin, has been employed as a reporter for decades due to its simplistic, non-hazardous nature and its high sensitivity of detection. More recently aequorin has been subject to spectral tuning. Techniques such as random and site-directed mutagenesis, the incorporation of coelenterazine analogues and the incorporation of non-natural amino acids have expanded the palette of aequorin by altering their emission wavelengths and/or half-lifes. Due to the increased diversity of aequorin, it can be used in multianalyte detection. Although aequorin has been studied extensively and has been used as a reporter in a wide array of applications, it has never been employed as a reporter in systems that involve the splitting of aequorin. Herein we describe the splitting of aequorin in such a way where it becomes the reporter protein in the development of protein-based molecular switches. We have created two distinct protein switches by genetically inserting the glucose-binding protein and the sulfate-binding protein into the aequorin sequence, splitting it in such a manner that it allows for the selective detection of glucose and sulfate, respectively. In a separate investigation, we developed a bioluminescence inhibition binding assay for the detection of hydroxylated polychlorinated biphenyls. These systems have shown that they can be employed in the detection of the respective analyte in biological as well as in environmental samples, which demonstrated a sensitive, fast alternative approach to current methods for on-site screening. Furthermore, we propose the rational design, preparation and use of truncated aequorin fragments in bioanalytical platforms such as multi-analyte detection, protein complementation assays and protein tagging assays based on our discovery that truncated aequorin retains partial bioluminescence emission. One such truncated aequorin demonstrated a large red shift in the emission maximum. It is envisioned that this new red-shifted truncated aequorin will find applications in multi-analyte detection. We anticipate that this work will lead to the discovery of additional functional truncated aequorin fragments that can be employed in novel protein-protein interactions or protein folding systems.

[pt] Nesta tese desenvolvemos um Modelo Dinâmico Bayesiano para a densidade Normal Truncada. A estimação clássica e estática de observações desta densidade foi desenvolvida por A.C. Cohen nas décadas de 1950 e 1960, enquanto R. C. Souza apresentou, em 1978, um modelo dinâmico Bayesiano para esta densidade, no qual utilizava idéias da Teoria de Informação. O presente trabalho estende a formulação dinâmica Bayesiana de West, Harrinson e Migon por tratar de observações que não pertencem à família exponencial. Ao mesmo tempo, estendemos os resultados de Souza por não mais supor a estacionariedade da série. Algumas séries reais e simuladas são analisadas e, em particular, comparamos nossos resultados com aqueles obtidos por Souza. / [en] This thesis describes a Dynamic Bayesian Model for a Truncated Normal distribution. The classical and static solution to the problem of finding estimators for the parameters of the original Normal distribution was treated by A.C. Cohen in the 1950s and 1960s R.C. Souza (1978) described in his Doctoral thesis a Dynamic Bayesian Model for this distribution, in which Information Theory concepts were used. The present thesis extends the dynamic formulation of West, Harrison and Migon by considering a distribution which is not a member of a an Exponential Family. Moreover, we extend the results derived by Souza by dropping the assumptions of a steady state model. Some real and simulated series are analyzed and, in particular, we compare our results with those obtained by souza.

The feedback control system is defined as the sampling of an output signal and feeding it back to the input, resulting in an error signal that drives the overall system. This dissertation focuses on the stabilization and performance of state feedback control systems. Chapters 3 and 4 focus on the feedback control protocol approaching in the multi-agents system. In particular, the global regulation of distributed optimization problems has been considered. Firstly, we propose a distributed optimization algorithm based on the proportional-integral control strategy and the exponential convergence rate has been delivered. Moreover, a decentralized mechanism has been equipped to the proposed optimization algorithm, which enables an arbitrarily chosen agent in the system can compute the value of the optimal solution by only using the successive local states. After this, we consider the cost function follows the restricted secant inequality. A dynamic event-triggered mechanism design has been proposed. By ensuring the global regulation of the distributed proportional-integral optimization algorithm, the dynamic event-triggered mechanism efficiently reduces the communication frequency among agents. Chapter 5 focuses on the feedback control protocol approaching the single-agent system. Specifically, we investigate the truncated predictor feedback control of the regulation of linear input-delayed systems. For the purpose of improving the closed-loop performance, we propose a design of the truncated predictor feedback method with time-varying feedback parameters and give the potential range of choosing the time-varying feedback parameters to replace the traditional constant low gain parameters.

We investigate the truncated moment problem, especially the Carathéodory number, the set of atoms and determinacy.