Acute megakaryoblastic leukemia (AMKL) was first described by Von Boros and Karangi in 1931, was a result of developments in ultrastructural cytochemistry and immunologic phenotyping acute myeloid leukemia (AML) of megakaryocytic lineage have been diagnosed increasingly. The French-American-British (FAB) Co-operative Group established the criteria for the diagnosis and added this category as a distinct subtype of AML (M7) in 1985. The main subtypes of AML in the infants are M4, M5, and M7. One 25-day-old infant was referred to the hospital for further examination of white blood cell. Hepatosplenomegaly and anemia were physically examined, and he was diagnosed to be an AMKL case. Abnormal karyotype 46,XY,t(1;1)(p13;p36) was observed in this patient. This study aims to identify the AMKL potentially related genes on the breakpoints of Homo sapiens autosomal (HSA) 1p13 and 1p36 in this case by candidate gene approaches. Data-mining of the AMKL potentially related genes on breakpoints of HSA1p13 and 1p36 through NCBI Map Viewer Database, OMIM Morbid Map, and OMIM Gene Map were performed. We identified three candidate genes on HSA1p13 and 15 candidate genes on HSA 1p36. RBM15-MKL1 fusion on t(1;22)(p13;q13) was reported to be AMKL genes by Ma et al., Mercher et al., and the Mitelman Database of Chromosome Aberrations in Cancer. We anticipated RBM15 is also a related gene on HSA1p13 in this AMKL case, and compared the Gene Ontology terms between MKL1 and these 15 candidate genes on HSA1p36. SKI becomes our first candidate gene on 1p36 in this case. To identify candidate genes locating at HSA1p13 and 1p36, including RBM15 and SKI were screened at both cDNA and genomic DNA levels. According to these results, RBM15 and SKI are more likely to be candidate genes. Thus RBM15 and SKI may be the novel AMKL genes in t(1;1)(p13;p36) AMKL patients.

In this thesis, We investigate the problem of when a C*-algebra is commutative through continuous functional calculus, The principal results are that: (1) A C*-algebra A is commutative if and only if e^(ix)e^(iy)=e^(iy)e^(ix), for all self-adjoint elements x,y in A. (2) A C*-algebra A is commutative if and only if e^(x)e^(y)=e^(y)e^(x) for all positive elements x,y in A. We will give an extension of (2) as follows: Let f:[a,b]-->[c,d] be any continuous strictly monotonic function where a,b,c,d in R, a<b,c<d. Then a C*-algebra A is commutative if and only if f(x)f(y)=f(y)f(x), for all self-adjoint elements x,y in A with spec(x) in [a,b] and spec(y) in [a,b].

There are two aspects in this study: cylinder penetrations and XBP (Expendable Bottom Penetrometer) interpretations. The cylinder studies firstly investigate the relationship between the soil resisting force and penetration depth by a series of rateindependent finite element analyses of pre-embedded penetration depths, and validate the results by upper and lower bound solutions from classical plasticity theory. Furthermore, strain rate effects are modeled by finite element simulations within a framework of rate-dependent plasticity. With all forces acting on the cylinder estimated, penetration depths are predicted from simple equations of motion for a single particle. Comparisons to experimental results show reasonable agreement between model predictions and measurements. The XBP studies follow the same methodology in investigating the soil shearing resistance as a function of penetration depth and velocity by finite element analyses. With the measurements of time decelerations during penetration of the XBP, sediment shear strength profile is inferred from a single particle kinetic model. The predictions compare favorably with experimental measurements by vane shear tests.

The presence of a blockage in a pipeline will alter the fluid dynamics of a flowing system in terms of the heat, mass and velocity characteristics. The analysis of the fluid dynamics is based on balances taken on the overall system to qualitatively and quantitatively assess the effects of the blockage. Pioneer work in the area of mass and momentum effects of blockages led to the development of blockage type curves useful in characterizing blockages from limited information. This work is an extension of previous work and is based on the application of a simplistic energy balance approach to characterize blockages in pipelines. The resulting heat models for the case of both a partially and fully-blocked flowline correctly predict the effect of wax deposition. Dimensionless temperature-based blockage maps developed here can be used in modeling unique cases where only two of the three necessary conditions are given. The heat model matches results from commercial software within a limited range of restricted flow conditions.

The complex interrelations among the different physical processes involved in acid fracturing make it difficult to design, and later, to predict the outcome of stimulation jobs. Actual tendencies require the use of computational models to deal with the dynamic interaction of variables. This thesis presents a new study of acidized surface textures by means of a laser profilometer to improve our understanding of the remaining etched surface topography and its hydraulic response. Visualization plots generated by the profilometer identified hydrodynamic channels that could not be identified by the naked eye in acidized surfaces. The plots clarified the existence of rock heterogeneities and revealed how the processes of dissolution function in chalk rock. Experimental data showed clearly that the effect of dissolution depends on the type of rock and the fluid system; dolomite, for example, dissolves more rapidly but more roughly than limestone. Fluid leakoff rate and temperature also affect the dissolution. Further research is necessary to clarify the effects of conductivity.

This thesis utilize pulse shaping in characterization of ultra-broad bandwidth laser pulse and multi-pulse generation. Using angle-dithering technique, time-integrating phase-matching bandwidth can be increased significantly even with a thin crystal. We also characterize the pulse by angle-dithered MIIPS( intrapulse interference phase scan ) technique. An addition advantage of using a thick crystal is increased signal strength. In addition, we provide a method to generate multi-pulses and proceed Michelson interferometeric autocorrelator by controlling the spectral amplitude and phase of the pulse. To compare with the past method, the efficiency was obtained from 33% to 80% , and the stability and time resolution of delay time can be improved. We expect this method applied to narrow-band frequency-tunable THz wave genetration will be better.

Extraction of oil and gas can cause reduction in pore pressure, occasionally resulting in subsequent compaction that forms a surface subsidence bowl, especially in shallow reservoirs. In the last 10 years, there has been over 10 feet of subsidence in parts of the Lost Hills oil field in California (Bruno et al.,1992). The surface subsidence at Lost Hills not only causes damage to surface facilities and wells, but also reactivates faults and reduces rock permeability. Subsidence makes reservoir optimization difficult. Hence, it is important to assess or predict the surface subsidence and the reasons for subsidence early in the life of an oil field to make an optimization plan. We use jointly the capacitance resistance model (CRM) (Alberoni et al., 2002 and Yousef, et al., 2006) that relies only on injection and production data, and the InSAR satellite imagery of surface subsidence. From CRM simulations, we estimate the connectivity between injectors and producers as well as general water flow directions from individual injectors. We then superimpose well connectivity and InSAR imagery to diagnose the reasons for the subsidence. Using new surface subsidence models, which are based on the continuity equation of CRM and rock mechanics, we are able to predict the average surface subsidence at Lost Hills from the injection and production rates. Our work shows that there was significant volumetric rock damage at Lost Hills and the well connectivity changed dramatically with time because of reservoir compaction and the rock damage. We conclude that for a soft, fragile and nearly- impermeable rock such as the diatomite, high injection rate weakens the rock and creates dynamic water flow tubes or ‘channels’ without providing good pressure support to the reservoir. These high permeability ‘channels’ re-circulate most of the injected water between the injectors and producers. Our CRM/InSAR approach is new and gives insights into the time-dependent and spatially variable fluid flow fields in a relatively shallow waterflood. Consequently, we may be able to suggest optimum water injection strategies to enhance oil production, while minimizing rock damage and surface subsidence. In addition, the proposed surface subsidence models are convenient and reliable to predict the average surface subsidence. / text

Timing analysis is a key sign-off step in the design of today's chips, but technology scaling introduces many sources of variability and uncertainty that are difficult to model and predict. The result of these uncertainties is a degradation in our ability to predict the performance of fabricated chips, i.e., a lack of model-to-hardware matching. The prediction of circuit performance is the result of a complex hierarchy of models ranging from the basic MOSFET device model to full-chip models of important performance metrics including power, frequency of operation, etc. The assessment of the quality of such models is an important activity, but it is becoming harder and more complex with rising levels of variability and the increase in the number of systematic effects observed in modern CMOS processes. The purpose of this research is (i) to introduce special-purpose test structures that specifically focus on ensuring the accuracy of gate timing models, and (ii) to introduce methods that analyze the extracted information, in the form of path delay measurements, using the proposed test structures. The certification of digital design correctness (the so-called signoff) is based largely on the results of performing Static Timing Analysis (STA), which, in turn, is based entirely on the gate timing models. The proposed test structures compare favorably to alternative approaches; they are far easier to measure than direct delay measurement, and they are much more general than simple ring-oscillator structures. Furthermore, the structures are specified at a high level, allowing them to be synthesized using a standard ASIC place-and-route flow, thus capturing the local layout systematic effects which can sometimes be lost by simpler (e.g., ring oscillator) structures. For the silicon timing analysis, we propose methods that deduce segment delays from the path delay measurements. These estimated segment delays using our methods can be directly compared with the timing models. Therefore, it will be easy to identify the cause of timing mismatches. Deducing segment delays from path delays, however, is not an easy problem. The difficulties associated with deconvolving segment delays from measured path delays come from insufficient sampling points. To overcome this limitation, we first group the segments based on certain characteristics of segments, and adapt Moore-Penrose pseudo-inverse method to approximately solve the segment delays. Secondly, we used equality-constrained least squares methods, which enable us to find a unique and optimized solution of segment delays from underdetermined systems. We also propose another improved test structure that has a built-in test pattern generator, and hence does not require ATPG (Automatic Test Pattern Generation). It is a self-timed circuit, and this feature makes the test structure run as fast as it can. Therefore, measurements can be made under high speed switching conditions. Finally, we can study dynamic effects such as timing effects of different levels of switching activities and voltage drop with the new test structure. / text

Reservoir models are generally constructed from seismic, well logs and other related datasets using inversion methods and geostatistics. It has already been recognized by the geoscientists that such a process is prone to non-uniqueness. Practical methods for estimation of uncertainty still remain elusive. In my dissertation, I propose two new methods to estimate uncertainty in reservoir models from seismic, well logs and well production data. The first part of my research is aimed at estimating reservoir impedance models and their uncertainties from seismic data and well logs. This constitutes an inverse problem, and we recognize that multiple models can fit the measurements. A deterministic inversion based on minimization of the error between the observation and forward modeling only provides one of the best-fit models, which is usually band-limited. A complete solution should include both models and their uncertainties, which requires drawing samples from the posterior distribution. A global optimization method called very fast simulated annealing (VFSA) is commonly used to approximate posterior distribution with fast convergence. Here I address some of the limitations of VFSA by developing a new stochastic inference method, named Greedy Annealed Importance Sampling (GAIS). GAIS combines VFSA with greedy importance sampling (GIS), which uses a greedy search in the important regions located by VFSA to attain fast convergence and provide unbiased estimation. I demonstrate the performance of GAIS on post- and pre-stack data from real fields to estimate impedance models. The results indicate that GAIS can estimate both the expectation value and the uncertainties more accurately than using VFSA alone. Furthermore, principal component analysis (PCA) as an efficient parameterization method is employed together with GAIS to improve lateral continuity by simultaneous inversion of all traces. The second part of my research involves estimation of reservoir permeability models and their uncertainties using quantitative joint inversion of dynamic measurements, including synthetic production data and time-lapse seismic related data. Impacts from different objective functions or different data sets on the model uncertainty and model predictability are investigated as well. The results demonstrate that joint inversion of production data and time-lapse seismic related data (water saturation maps here) reduces model uncertainty, improves model predictability and shows superior performance than inversion using one type of data alone. / text

The incorporation of rare earth-V (RE-V) semimetallic nanoparticles embedded in III-V compound semiconductors is of great interest for applications in solid-state devices including multijunction tandem solar cells, thermoelectric devices, and fast photoconductors for terahertz radiation sources and receivers. With regard to those nanoparticle roles in device applications and material itself, electrical and thermal properties of embedded RE-V nanoparticles, including nanoscale morphology, electronic structure, and electrical and thermal conductivity of such nanoparticles are essential to be understood to engineer their properties to optimize their influence on device performance. To understand embedded RE-V semimetallic nanostructures in III-V compound semiconductors, nanoscale characterization tools are essential for analysis their properties incorporated in compound semiconductors. In this dissertation, we used atomic force microscopy (AFM) with other secondary detection tools to investigate nanoscale material properties of semimetallic RE-V and GaAs heterostructures, grown by molecular beam epitaxy. We used scanning capacitance microscopy and conductive AFM techniques to understand electronic and electrical properties of ErAs/GaAs heterostructures. For the electrical properties, this thesis investigates details of statistical analysis of scanning capacitance and local conductivity images contrast to provide insights into (i) nanoparticle structure at length scales smaller than the nominal spatial resolution of the scanned probe measurement, and (ii) both lateral and vertical nanoparticle morphology at nanometer to atomic length scales, and their influence on electrical conductivity. To understand thermal properties of ErAs nanoparticles, in-plane and cross-sectional plane of ErAs/GaAs superlattice structure were investigated with a scanning probe microscopy technique implemented with 3[omega] method for thermal measurement. By performing detailed numerical modeling of thermal transport between thermal probe tip and employed samples, and estimation of additional phonon scattering induced by ErAs nanoparticles, we could understand influences of ErAs nanoparticles on the host GaAs thermal conductivity. Investigation of ErAs semimetallic nanostructure embedded in GaAs matrix with scanned probe microscopy provided detailed understanding of their electronic, electrical and thermal properties. In addition, this dissertation also demonstrates that an atomic force microscope with secondary detection techniques is promising apparatus to understand and investigate intrinsic properties of nanostructure materials, nanoscale charge transports, when the system is combined with detailed modeling and simulations. / text