Background: Breast milk is an ideal source of nutrition for newborns as it provides nutrients required for growth in addition to numerous bioactive factors which help to develop an infant’s immune system. However, the macronutrient content of breast milk alone is not able to support preterm infant’s rapid growth needs and requires supplementation with fortifiers. There is strong evidence that the current practice of standard fortification (SF) may lead to nutritional deficits and consequently increases an infant’s risk of inadequate postnatal growth. Furthermore, the natural variation of breast milk composition makes it increasingly difficult to provide recommended macronutrient intakes with the SF. Individualized approaches, like adjustable fortification or target fortification (TFO), have been proposed to improve growth during hospitalization. A recent pilot trial demonstrated that TFO, which individually adjusts deficient macronutrient content after SF by analyzing the breast milk for native protein, carbohydrate and fat, is feasible in clinical practice and significantly reduces variation of macronutrient intakes. Objectives: To compare the response of preterm infants to feedings of breast milk with either SF or SF+TFO with respect to: 1) weight at 36 weeks’ post-menstrual age and growth velocity during hospitalization; 2) head circumference, length and body composition; and 3) the relationship between preterm infant’s weight or growth velocity and their macronutrient intake factors including protein intake and protein:energy (P:E) ratio. Methods: This was a single-center, double-blind randomized controlled trial completed at McMaster Children’s Hospital’s Level III NICU with a study period of at least 21 days. Preterm infants (n=103) born at <30 weeks of gestation and tolerating full enteral intakes of breast milk were enrolled and randomized to the Control (SF only) or Intervention (SF+TFO) groups. Native breast milk samples were collected for all infants on each study day and were analyzed for protein, carbohydrate and fat content. In the Control group, SF was provided using Enfamil (Mead Johnson, IL) human milk fortifier at the recommended dosage. In the Intervention group, after the addition of SF, modular macronutrient fortifiers were added based on analysis of the mother’s milk to reach target values based on ESPGHAN recommendations. Adjustment of the modular fortifiers was done three times per week. The primary outcomes were weight at 36 weeks’ PMA and growth velocity during the study period. Head circumference, length and body composition were also assessed at term-equivalent age. Subgroup analysis, stratified around the median protein levels after SF, also compared the growth outcomes between Control and Intervention groups. Multiple regression analysis models examined the effect of macronutrient intake factors and infant characteristics on weight, average growth velocity and daily weight gain. Results: Infants fed with SF+TFO had significantly higher protein (p<0.001), carbohydrate (p<0.001) and fat intakes (p<0.01) in addition to higher protein:energy and carbohydrate:non-protein energy (CHO:NPE) ratios (p<0.001) compared to those fed with SF alone. The average weight at 36 weeks’ PMA and growth velocity during the 21-day study period were higher for infants in the Intervention group (p<0.001). The Intervention group had significantly higher fat-mass (p<0.05) as well as more fat-free mass than the Control group at term-equivalent age (TEA), but were still within normal limits when compared to normative data from our NICU. At TEA, infants fed with TFO also showed significantly higher change in z-scores from birth for length when compared to infants fed SF with low-protein intakes (p<0.05). Change in head circumference z-scores were not statistically significant between groups. Higher average protein intakes and P:E ratios were each positively associated with higher weight at 36 weeks’ PMA (p<0.05). Moreover, higher daily weight gain was positively associated with higher daily protein intake from the previous study day (p<0.05). The absolute difference in day-to-day macronutrient intakes, however, were not significant predictors of daily weight gain. Conclusions: This study shows that target fortification of breast milk is promising as an individualized approach to improve the quality of nutrition for preterm infants. By addressing the variation and deficits of macronutrients that occur after standard fortification, infants were able to achieve higher body weight and faster weight gain. In the short term, target fortification may reduce the preterm infant’s risk for sub-optimal postnatal growth. These improved growth outcomes also have positive clinical implications on infant’s long-term health and development. Protein intake and the P:E ratio were identified as important factors for growth and should be considered in nutritional management and future fortification strategies for breast milk fed preterm infants. / Thesis / Master of Science (MSc)

Recently, through reporter gene studies, the novel BTB/POZ protein, Kaiso, has been identified as a transcriptional repressor. The purpose of this study was to determine if Kaiso recruited the Histone Deacetylase Complex to mediate repression and if the previously identified Kaiso Binding Site (KBS; TCCTGCNA) is a physiological target regulated by Kaiso. The two objectives are complementary because an HDAC interaction identifies the mechanism of transcriptional regulation used by Kaiso and regulation of the KBS element identifies a novel, non-methylation dependent, physiological target under transcriptional regulation by Kaiso. Through coimmunoprecipitation and Western blot analyses, Kaiso does not interact with HDAC1, HDAC2 or mSIN3A. These results were surprising since all three of these proteins are common to a variety of repression complexes. mSIN3A is a common component of SIN3 mediated repression and HDAC1/HDAC2 are part of various repression complexes including SIN3, NuRD and CtBP. Although the remaining HDAC proteins were not assayed for an interaction, Kaiso transcriptional activity was demonstrated to be insensitive to the HDAC inhibiting drug, Trichostatin A (TSA). These results indicate either a non-HDAC mechanism of action or alternatively, transcriptional activation. Complementary to the observations of no Kaiso-HDAC interaction and TSA insensitivity was the findings that Kaiso activates transcription of the KBS cis-element in HCT116, HCA-7 and 293 cells, but not MOCK cells in reporter gene assays. Taken together, these results indicate that Kaiso is a dual functioning protein capable of both transcriptional activation and repression and that the mechanism of repression is not through the direct recruitment of HDAC proteins. / Thesis / Master of Science (MSc)

In recent years previously restricted radio-frequency spectrum has been opened to civilian and industrial access in the United States. Because of this, high priority users such as the military and government need to develop systems that can adapt to the surrounding spectral environment which will suddenly be filled with new users. This thesis considers an environment with one tracking radar, a single target, and a communications system that can passively interfere with the radar system. Three separate agents, Sense and Avoid, Machine Learning, and "Optimal", are tasked with the channel selection problem for radar communications coexistence. Each agent is evaluated based on their ability to detect and avoid the interferer while also tracking a target accurately. In particular, in this thesis, we are interested in the value that machine learning algorithms can provide over and above simple approaches. This value is assessed based on the conflicting requirements of avoiding interference yet using as much of the spectrum for tracking as possible. / Master of Science / With a newfound dependence on wireless transmission, the demand for electromagnetic spectrum allocations has vastly increased. In recent years the Federal Communications Commission has auctioned some previously restricted access frequency bands to public and commercial applications. While this enables the growth of faster and more widespread civilian communications, military radar systems which had been the priority users of those bands are now at risk of interference from new users. Current radar systems typically occupy fixed bands and are not yet well adjusted to sharing their allocated spectrum with other users. Cognitive radar systems have been proposed to monitor airwaves for potential interferences and autonomously manage band allocation to avoid the interferers. In this thesis, we study a learning algorithm that enables a radar system to actively monitor and select its bandwidth to ensure proper target tracking. In particular, we are interested in the value this learning algorithm can provide over and above simple approaches. This value is assessed based on the conflicting requirements of avoiding interference yet using as much of the spectrum for tracking as possible.

The initial portion of this thesis examines the problem of tracking a maneuvering target in the 2-dimensional (X,Z) plane, vertical to the ocean floor, using passive time-delay measurements. The target is free to maneuver in velocity and make depth changes at times unknown to the observer. In the past, tracking systems have used Extended Kalman Filters to process the nonlinear measurements, but these have inherent divergence problems. To overcome this, a nonlinear prefilter is added to linearize the measurements and thus allow the use of a conventional Kalman Filter which makes the tracking system more 'robust' and also decouples the depth estimator from the polar range estimator. The depth estimator is discussed in detail here. The latter part of this thesis introduces tracking in the 2-dimensional horizontal (X, Y) plane, parallel to the ocean floor, to observe polar range and target bearing angle. The approach of using a nonlinear prefilter and a standard Kalman Filter is similar to the one described above. Subsequently, the analysis is extended to a Kalman Filter which is not 'matched', i.e. it does not possess any knowledge of the deterministic inputs which cause target motion. This necessitates the use of a bank of Kalman Filters and an adaptive weighting scheme. Test results are included to show that all source maneuvers can be tracked with a relatively high degree of accuracy. / Master of Science

The ability to quickly, accurately, and autonomously identify and track objects in digital images in real-time has been an area of investigation for quite some time. Research in this area falls under the broader category of computer vision. Only in recent decades, with advances in computing power and commercial optical hardware, has this capability become a possibility. There are many different methods of identifying and tracking objects of interest, and best practices are still being developed, varying based on application. This thesis examines background subtraction methods as they apply to the tracking of small unmanned aerial systems (sUAS). A system combining commercial off-the-shelf (COTS) cameras and a pan-tilt unit (PTU), along with custom developed code, is developed for the purpose of continuously pointing at and tracking the motion of a sUAS in flight. Mixtures of Gaussians Background Modeling (MOGBM) is used to track the motion of the sUAS in frame and determine when to command the PTU. When the camera is moving, background subtraction methods are unusable, so additional methods are explored for filling this performance gap. The stereo vision capabilities of the system, enabled by the use of two cameras simultaneously, allow for estimation of the three-dimensional position and trajectory of the sUAS. This system can be used as a supplement or replacement to traditional tracking methods such as GPS and RADAR as part of a larger unmanned aerial systems traffic control (UTC) infrastructure. / Master of Science / The ability to quickly, accurately, and automatically identify and track targets in digital images has been of interest for some time now. Research in this area falls under the broader category of computer vision. Only in recent decades, with advances in computing power and commercial optical hardware, has this ability become a possibility. There are many different methods of identifying and tracking targets of interest, and best practices are still being developed, varying based on application. This thesis examines background subtraction methods as they apply to the tracking of small unmanned aerial systems (sUAS), commonly referred to as drones. A system combining cameras and a moving platform, along with custom developed code, is developed for the purpose of continuously pointing at and tracking the motion of an sUAS in flight. The system is able to map out the three-dimensional position of a flying sUAS over time.

The security of powerful systems and large networks is often addressed through complex defenses. While these types of defenses offer increased security, they are resource intensive and therefore impractical to implement on many new classes of networked systems, such as mobile phones and small, embedded network infrastructure devices. To provide security for these systems, new defenses must be created that provide highly efficient security. The Moving Target IPv6 Defense (MT6D) is a network layer moving target defense that dynamically changes Internet Protocol version 6 (IPv6) addresses mid-session while still maintaining continuous communication. MT6D was originally written in Python language, but this implementation suffers from severe performance limitations. By translating MT6D from Python to C and taking advantage of operating system specific application programming interfaces (APIs) and optimizations, MT6D can become a viable defense for resource constrained systems. The Python version of MT6D is analyzed initially to determine what functions might be performance bottlenecks that could be performed more efficiently using C. Based on this analysis, specific parts of the Python version are identified for improvement in the C version by either using functionality of the Linux kernel and network stack or by reworking the code in a more efficient way. After this analysis, the information gathered about the Python version is used to write the C version, using methods specific to a moving target defense to capture, analyze, modify, and tunnel packets. Finally, tests are designed and run to compare the performance of the Python and C versions. / Master of Science

The problem of reorienting a spacecraft to acquire a moving target is investigated. The spacecraft is modeled as a rigid body with N axisymmetric wheels controlled by axial torques, and the kinematics are represented by Modified Rodriques Parameters. The trajectory, denoted the reference trajectory, is one generated by a virtual spacecraft that is identical to the actual spacecraft. The open-loop reference attitude, angular velocity, and angular acceleration tracking commands are constructed so that the solar panel vector is perpendicular to the sun vector during the tracking maneuver. We develop a nonlinear feedback tracking control law, derived from Lyapunov stability and control theory, to provide the control torques for target tracking. The controller makes the body frame asymptotically track the reference motion when there are initial errors in the attitude and angular velocity. A spacecraft model, based on the X-ray Timing Explorer spacecraft, is used to demonstrate the effectiveness of the Lyapunov controller in tracking a given target. / Master of Science

This study investigates the use of different strategies for translating puns in Alice’s Adventures in Wonderland. The material chosen for this study consist of the two Swedish translations by Nonnen (1870/1984) and Westman (2009). Six puns were selected for the analysis which greatly relies on Delabastita’s (1996) eight strategies for translating puns, and Newmark’s (1988) translation methods. The analysis shows that Westman empathises with the readers of the TT while Nonnen empathises with the ST. This entails that Westman tends to use a more ‘free’ translation and is more inclined to adapt the ST puns to make them more visible for the readership of the TT. The priority for Nonnen, on the other hand, is to remain faithful to the contextual meaning of the ST. Paradoxically, to be faithful to the ST does not necessarily entail that the translator respects the semantic aspects of the ST, but that they adapt the culture of the ST to better fit the cultural and linguistic framework of the TL. Since Westman adapts the ST puns so that they are still recognised by the reader of the TT, her translation appears to be more suitable for the TL readership than Nonnen’s.

Within the PANDA experiment, proton anti-proton collisions will be studied in order to gain knowledge about the strong interaction. One interesting aspect is the production and decay of charmed hadrons. The charm quark is three orders of magnitude heavier than the light up- and down-quarks which constitue the matter we consist of. The detection of charmed particles is a challenge since they are rare and often hidden in a large background. There will be three different targets used at the experiment; the cluster-jet, the untracked pellet and the tracked pellet. All three targets meet the experimental requirements of high luminosity. However they have different properties, concerning the effect on beam quality and the determination of the interaction point. In this thesis, simulations and reconstruction of the charmed D-mesons using the three different targets have been made. The data quality, such as momentum resolution and vertex resolution has been studied, as well as how the different targets effect the reconstruction efficiency of D-meson have been analysed. The results are consistent with the results from a similar study in 2006, but provide additional information since it takes the detector response into account. Furthermore, a new target distribution have been implemented in the software package. This is the first results obtained from a cylindrical target distribution. The results are very important for PANDA since they show the limitations of different target types regarding the possibilities to reduce background. Simulations with the new target distribution have been made for all three targets and the results are presented.

The detection of weak, ground-moving targets can be improved through effective utilization of additional target signal energy collected over an extended dwell time. The signal model used in conventional radar processing limits integration of signal energy over an extended dwell. Two solutions that consider the complexity of the extended-dwell signal model and effectively combine signal energy collected over a long dwell are presented. The first solution is a single-channel algorithm that provides an estimate of the optimal detector to maximize output signal-to-interference-plus-noise ratio for the extended dwell time signal. Rather than searching for the optimal detector in an intractably large filter bank that contains all combinations of phase components, the single-channel algorithm projects dictionary entries against the data to estimate the signal’s linear and nonlinear phase components sequentially with small, phase-specific dictionaries in a multistage process. When used as the detector, the signal model formed from the estimated phase components yields near optimal performance for a wide range of target parameters for dwell times up to four seconds. In comparison, conventional radar processing methods are limited to an integration time of approximately 100 milliseconds. The second solution is a multichannel, multistage algorithm based on element-space pre-Doppler space-time-adaptive processing with two modifications that make it suitable for detection of weak targets whose energy is collected over an extended dwell time. The multichannel solution detects targets with lower radial velocities at significantly lower signal-to-noise ratios (SNRs) than conventional radar processing methods. The decrease in required input SNR for the multichannel solution as compared to conventional methods nearly doubles the detection range for a typical target of interest. Future related research includes extension of these concepts to other radar applications and investigation of algorithm performance for the multiple-target scenario.