Medical X-ray imaging is an important tool in diagnostic radiology. The ionising-radiation dose to the patient is justified by the clinical benefit of the examination. Nonetheless, detectors that operate at even lower doses and provide more information to the radiologist are desired. A hybrid pixel detector has the potential to provide a leap in detector technology as it incorporates a more advanced signal-processing capability than currently used detectors. The DIXI digital detector is a hybrid pixel detector developed for X-ray imaging. It consists of a readout chip and a semiconductor sensor. The division in two parts makes it possible to optimise each part individually. The detector is divided into square pixels with a size of 270 x 270 μm2. DIXI has the ability to count single photons and every readout pixel has two embedded counters to allow the acquisition of two images close in time. A discriminator enables the selection of photons with energies above a preset threshold level. The readout chip Angie has been developed and its performance has been evaluated in terms of noise, threshold variation and capability to perform energy weighted counting. Silicon sensors have been fabricated, and a control system for DIXI has been designed and built. An electroless process for deposition of Ni/Au bumps on the chip and sensor has been optimised as a preparation for the assembly of a complete detector, which is being assembled by flip-chip bonding using anisotropic conductive film. A simulation library for the DIXI detector has been set up and results on the image quality are reported for different exposures and working conditions. A theoretical model for hybrid pixel detectors based on the cascaded linear system theory has been developed. The model can be used to investigate and optimise the detector for different detector configurations and operating conditions.

Boolean propositional satisfiability (SAT) and probabilistic reasoning represent two core problems in AI. Backtracking based algorithms have been applied in both problems. In this thesis, I investigate structure-based techniques for solving real world SAT and Bayesian networks, such as software testing and medical diagnosis instances. When solving a SAT instance using backtracking search, a sequence of decisions must be made as to which variable to branch on or instantiate next. Real world problems are often amenable to a divide-and-conquer strategy where the original instance is decomposed into independent sub-problems. Existing decomposition techniques are based on pre-processing the static structure of the original problem. I propose a dynamic decomposition method based on hypergraph separators. Integrating this dynamic separator decomposition into the variable ordering of a modern SAT solver leads to speedups on large real world SAT problems. Encoding a Bayesian network into a CNF formula and then performing weighted model counting is an effective method for exact probabilistic inference. I present two encodings for improving this approach with noisy-OR and noisy-MAX relations. In our experiments, our new encodings are more space efficient and can speed up the previous best approaches over two orders of magnitude. The ability to solve similar problems incrementally is critical for many probabilistic reasoning problems. My aim is to exploit the similarity of these instances by forwarding structural knowledge learned during the analysis of one instance to the next instance in the sequence. I propose dynamic model counting and extend the dynamic decomposition and caching technique to multiple runs on a series of problems with similar structure. This allows us to perform Bayesian inference incrementally as the evidence, parameter, and structure of the network change. Experimental results show that my approach yields significant improvements over previous model counting approaches on multiple challenging Bayesian network instances.

We consider variations of range searching in which, given a query range, our goal is to compute some function based on frequencies of points that lie in the range. The most basic such computation involves counting the number of points in a query range. Data structures that compute this function solve the well-studied range counting problem. We consider adaptive and approximate data structures for the 2-D orthogonal range counting problem under the w-bit word RAM model. The query time of an adaptive range counting data structure is sensitive to k, the number of points being counted. We give an adaptive data structure that requires O(n loglog n) space and O(loglog n + log_w k) query time. Non-adaptive data structures on the other hand require Ω(log_w n) query time (Pătraşcu, 2007). Our specific bounds are interesting for two reasons. First, when k=O(1), our bounds match the state of the art for the 2-D orthogonal range emptiness problem (Chan et al., 2011). Second, when k=Θ(n), our data structure is tight to the aforementioned Ω(log_w n) query time lower bound. We also give approximate data structures for 2-D orthogonal range counting whose bounds match the state of the art for the 2-D orthogonal range emptiness problem. Our first data structure requires O(n loglog n) space and O(loglog n) query time. Our second data structure requires O(n) space and O(log^ε n) query time for any fixed constant ε>0. These data structures compute an approximation k' such that (1-δ)k≤k'≤(1+δ)k for any fixed constant δ>0. The range selection query problem in an array involves finding the kth lowest element in a given subarray. Range selection in an array is very closely related to 3-sided 2-D orthogonal range counting. An extension of our technique for 3-sided 2-D range counting yields an efficient solution to adaptive range selection in an array. In particular, we present an adaptive data structure that requires O(n) space and O(log_w k) query time, exactly matching a recent lower bound (Jørgensen and Larsen, 2011). We next consider a variety of frequency-based range query problems in arrays. We give efficient data structures for the range mode and least frequent element query problems and also exhibit the hardness of these problems by reducing Boolean matrix multiplication to the construction and use of a range mode or least frequent element data structure. We also give data structures for the range α-majority and α-minority query problems. An α-majority is an element whose frequency in a subarray is greater than an α fraction of the size of the subarray; any other element is an α-minority. Surprisingly, geometric insights prove to be useful even in the design of our 1-D range α-majority and α-minority data structures.

Trees are fundamental structures in computer science, being widely used in modeling and representing different types of data in numerous computer applications. In many cases, properties of objects being modeled are stored as weights or labels on the nodes of trees. Thus researchers have studied the preprocessing of weighted trees in which each node is assigned a weight, in order to support various path queries, for which a certain function over the weights of the nodes along a given query path in the tree is computed [3, 14, 22, 26]. In this thesis, we consider the problem of supporting several various path queries over a tree on n weighted nodes, where the weights are drawn from a set of σ distinct values. One query we support is the path median query, which asks for the median weight on a path between two given nodes. For this and the more general path selection query, we present a linear space data structure that answers queries in O(lg σ) time under the word RAM model. This greatly improves previous results on the same problem, as previous data structures achieving O(lg n) query time use O(n lg^2 n) space, and previous linear space data structures require O(n^ε) time to answer a query for any positive constant ε [26]. We also consider the path counting query and the path reporting query, where a path counting query asks for the number of nodes on a query path whose weights are in a query range, and a path reporting query requires to report these nodes. Our linear space data structure supports path counting queries with O(lg σ) query time. This matches the result of Chazelle [14] when σ is close to n, and has better performance when σ is significantly smaller than n. The same data structure can also support path reporting queries in O(lg σ + occ lg σ) time, where occ is the size of output. In addition, we present a data structure that answers path reporting queries in O(lg σ + occ lg lg σ) time, using O(n lg lg σ) words of space. These are the first data structures that answer path reporting queries.

<p>An experimental study of the two-neutrino double-beta (2&nu;&beta;&beta;) decay of <super>150</super>Nd to various excited final states of <super>150</super>Sm was performed at Triangle Universities Nuclear Laboratory (TUNL). Such data provide important checks for theoretical models used to predict 0&nu;&beta;&beta; decay half lives.</p> <p>The measurement was performed at the recently established Kimballton Underground Research Facility (KURF) in Ripplemeade, Virginia using the TUNL-ITEP double-beta decay setup. In this setup, two high-purity germanium detectors were operated in coincidence to detect the deexcitation gamma rays of the daughter nucleus. This coincidence technique, along with the location underground, provides a considerable reduction in background in the regions of interest.</p> <p>This study yields the first results from KURF and the first detection of the</p> <p>coincidence gamma rays from the 0<super>+</super>₁ excited state of <super>150</super>Sm. These gamma rays</p> <p>have energies of 334.0 keV and 406.5 keV, and are emitted in coincidence through a 0<super>+</super>₁&rarr;2<super>+</super>₁&rarr;0<super>+</super>_gs transition. The enriched Nd₂O₃ sample obtained from Oak Ridge</p> <p>National Laboratory consists of 40.13 g <super>150</sub>Nd. This sample was observed for 391 days, producing 29 raw events in the region of interest. This count rate gives a half life of T_1/2 = (0.72<super>+0.36</super>_&#8722;0.18 &plusmn; 0.04(syst.)) &times; 10<super>20</super> years, which agrees within error with</p> <p>another recent measurement, in which only the single deexcitation gamma rays were detected (i.e., no coincidence was employed). Lower limits were also obtained for decays to higher excited final states.</p> / Dissertation

In Drosophila melanogaster, sex is determined at the preblastoderm stage via an Xchromosome counting mechanism. During this process embryos that carry two X chromosomes begin to develop as females while embryos with one X start the male developmental program. The Xlinked genes involved in sex determination, also called Xsignal elements (XSEs), are: sisterlessA (sisA), sisterlessB (sisB), unpaired (upd), and runt. These genes are responsible for the transcriptional activation of the master regulatory gene Sexlethal (Sxl). Expression of Sxl is initially accomplished only in females through activation of the establishment promoter SxlPe. Later in development, Sxl is transcribed in both sexes through a maintenance promoter, SxlPm, but functional Sxl protein is only produced in female flies. Since Sxl is at the top of the sex determination cascade, understanding its regulation is key to comprehend the process of sex determination. The experiments in this dissertation were designed to better understand two aspects of the sex determination mechanism: How the protein encoded by XSE element sisA interacts with SxlPe, and how the transition from regulation by SxlPe to regulation by SxlPm occurs. The sisA protein (SisA), as part of the bZIP protein family, is thought to bind to its target as a dimer, but a dimerization partner has not yet been found. This work uses knockouts and germline clones to examine interaction between sisA and three SisA partner candidates, atf4, CG16813, and CG16815. Although the evidence described here suggest that none of the three SisA partner candidates genetically interact with Sis, we cannot rule out the possibility of redundancy between the different candidate proteins. This research unravels the timing and regulation of SxlPm expression. I have shown, contrary to previous thought, that expression of SxlPe and SxlPm overlaps for a brief period. Several of the same proteins that are involved in the regulation of SxlPe, including the XSE sisB, also regulate SxlPm. This sex specific regulation leads to a sexually dimorphic pattern of activation and early expression of SxlPm. A common enhancer region was found to regulate SxlPe as well as SxlPm. These results highlight the importance of the transition between SxlPe and SxlPm for the proper establishment of sex determination and have implications for how the sex determination mechanism evolved.

This research proposes a method for estimating the residual capacity of Li-ion batteries. The charging and discharging characteristics of Li-ion batteries are investigated and analyzed by a battery test system. The measurement of the initial capacity is based on the improved open-circuit voltage measurement, which compensates the effects of battery aging and self-discharging. The measurement of the used capacity is based on the improved coulomb counting measurement, which compensates the effects of output current and environmental temperature. The designed system provides various functions for battery charging and discharging, battery voltage measuring and recording, battery capacity estimation and calculation, and the log files can be used for further battery characteristics analysis.

The topic of this study is to develop a battery capacity management system. The main purpose is to monitor the state of battery during charging and discharging. Form this, user can know the battery status and to avoid loss of data before sudden system power down caused by a spent battery. Different states of battery were collected in different conditions by a battery measurement system, after which characteristics were analyzed. A fast-charge and residual capacity estimation system was developed according to the battery characteristics. The fast-charge system is a technique that emphasizes not only fastness charging but also safety. In this study a fast-charge end method was adopted to terminate the fast charging state of the battery and the initial state had been estimated before charging. Furthermore, the battery was charged with the optimum method according to the battery initial state. That can recover the capacity of the battery within a short period without causing any side effects from repeated usage. The residual capacity estimation system works by first estimating the initial capacity of the batteries, and then recording the current of batteries continuously using the coulomb counting method to make compensation for the effects of battery aging, environmental temperature, self-discharging, and output current.

In this thesis, the development and implementation of fluorescence lifetime imaging microscopy that integrates time correlated single photon counting (TCSPC) and a confocal microscope will be described. The TCSPC method has high detection efficiency, with a time resolution limited only by the transit time spread of the detector, and directly delivers the decay functions in the time domain. TCSPC can also be used to obtain images that indicate the fluorescence resonance energy transfer (FRET) effect between critical fluorophores, an important method distinguish the difference between binding and co-localization. Estimation of distances between RET fluorophore pairs can also be established. Additionally, the effects of ion concentration, oxygen concentration, pH value, ..etc. can also be revealed.

Although a component satisfies all operating static requirements, failures can still occur due to vibration induced fatigue. Vibration induced fatigue is a frequent phenomenon, in cases where the natural frequencies of the structures are excited by the loading. Hence, the methods which consider all dynamic characteristic of the structure should be used to obtain accurate fatigue life predictions. These methods in frequency domain are called vibration fatigue methods which give accurate, reliable and fast results. In this thesis, a numerical code is developed in order to predict fatigue life of structures and it is used for a bracket that is installed on an air platform. However, for verification of the numerical code, a cantilever beam is used as a case study at the beginning. First, finite element model of the cantilever beam is constructed and experimental analyses are performed to verify the finite element model. Then fatigue life is calculated using the numerical code and it is verified comparing the results obtained by both commercial software and performed fatigue tests. For predicting fatigue life of the bracket, flight test is performed in order to obtain acceleration loading. Finite element modeling of bracket and verification of it by experimental analyses are performed and finally, accelerated fatigue life of the bracket is obtained by the developed numerical code, commercial software and fatigue test. It is concluded that the results obtained from the fatigue analyses and fatigue test are considerably close enough to justify that the analysis is significantly accurate.