Background: Over 700,000 patients per year undergo open-heart surgery. Healing complication rates can be up to 5% of patients who undergo this procedure, with a morbidity rate of 50% if mediastinitis supervenes. A secure and rigid fixation of surgically divided sternum is critical to avoid healing complications. The purpose of this study was to compare the yield load, construct stiffness, ultimate load, displacement at ultimate load, and post-yield behavior of three sternotomy closure methods (Peristernal wires or Sternalock titanium plates) when stressed in each of three directions: lateral distraction, rostro-caudal (longitudinal) shear distraction, and anterior-posterior (transverse) shear in a cadaveric model. Methods: Forty-two fresh cadaver models were divided into three test groups: group A, B, and C. A cardiothoracic surgeon divided each cadaveric sternum longitudinally and repaired peristernal wires or one of two Sternalock configurations. Tests were performed using a materials testing system that applied force at a constant displacement rate in a uniaxial direction until the construct catastrophically failed. Mechanical behavior was monitored using a 3D texture correlation system to create a real-time three-dimensional representation of strain directions. The resulting displacement pattern is analogous to a finite element contour plot of displacements, Lagrange Strain, or velocity. Statistical analysis was used to show the different mechanical properties of each closure method. Results: When loaded in lateral distraction, both Sternalock configurations surpassed the rigidity of peristernal wires by 600%. Some evidence was also found linking Sternalock with stiffer behavior in the rostro-caudal direction. Though not statistically significant, a trend was observed showing that constructs using the Sternalock also had higher yield loads, as well as, less post-yield displacement when compared to peristernal wires. Conclusions: Data gathered showed the superior performance of the Sternalock system in stiffness in both longitudinal distraction and rostro-caudal shear. Implications for use of the Sternalock system are faster healing times, lower complication rates, and success of the procedure.

This thesis is focused on the L1 regression, a possible alternative to the ordinary least squares regression. L1 regression replaces the least squares estimation with the least absolute deviations estimation, thus generalizing the sample median in the linear regres- sion model. Unlike the ordinary least squares regression, L1 regression enables loosening of certain assumptions and leads to more robust estimates. Fundamental theoretical re- sults, including the asymptotic distribution of regression coefficient estimates, hypothesis testing, confidence intervals and confidence regions, are derived. This method is then compared to the ordinary least squares regression in a simulation study, with a focus on heavy-tailed distributions and the possible presence of outlying observations. 1

Several studies have been carryout on finding optimal locations to minimize CO2 emissions from the last mile distribution perspective. In conjunction with that, there has been no study conducted in Sweden that provides a decision support system to compute the transport consequences of the modifications in the retailer’s store network. This thesis did used the following steps: requirement analysis, system design, implementation and testing to build a prototype decision support system that is to help retailers find optimal locations for a new retail store. This thesis provided a subsequent answer as to which data are needed along with the rightful user interface for said decision support system. Subsequently, this thesis does present a decision support system prototype from which some recommendations were provided as to what skills set and tools are needed for the management and maintenance of said decision support system. The primary data used during this thesis is the Dalarna municipalities, six selected retailer’s stores networks and the Dalarna Road network geo-data (Longitude and latitude). This thesis does conclude that it is possible to integrate an optimization model within the Django framework using a geo data to build a decision support system.

Neuropeptide W-23 (NPW23) and neuropeptide W-30 (NPW30) are 23- and 30-amino acid peptides recently isolated from the porcine hypothalamus. Immunohistochemical studies using a rabbit polyclonal antiserum against the rat NPW23 peptide revealed a limited distribution in the rat brain. NPW23-immunoreactive (irNPW) cells were detected in the paraventricular nucleus (PVH), mainly in the parvocellular division, supraoptic nucleus (SO), accessory neurosecretory nuclei, dorsal and lateral hypothalamic areas, perifornical nucleus, arcuate nucleus, and anterior and posterior pituitary; whereas, irNPW fibers were noted in the PVH and SO, retrochiasmatic nucleus, dorsal and lateral hypothalamic areas, median eminence, amygdala, and posterior pituitary. The pattern of distribution of irNPW in the hypothalamus corroborates a possible role of NPW on prolactin release and feeding behavior reported by others.

Distribution of the novel peptide beacon in the hypothalamus of Sprague-Dawley rats was examined by immunohistochemical methods. Beacon-immunoreactive (irBC) neurons were found in the paraventricular, supraoptic, and accessory neurosecretory nuclei, and intensely labeled fibers in the median eminence and infundibulo-pituitary stalk. Scattered cells and/or fibers were noted in the suprachiasmatic nucleus, arcuate nucleus, retrochiasmatic area, lateral and medial preoptic area, as well as anterior and lateral hypothalamic area. The wide distribution of irBC in the hypothalamus of Sprague-Dawley rats suggests that the peptide may influence, in addition to a proposed role in feeding, a multitude of biological activities associated with the hypothalamic-pituitary axis.

This research study was designed to help illuminate if there is a relationship between the quality of career and technical education programs from centralized and decentralized-controlled systems in relation to the level of authority exerted by state governing/coordinating boards over the community college system. This study included data from the 50 states that are part of the United States of America. This study used a quasi-experimental, nonequivalent design. This study did not include randomly selected groups and was a nonequivalent control group design. The independent variables included: centralized or decentralized governance, median household income, the percent of community colleges that are rural, unemployment rate, and amount spent per full time enrolled community college student. The independent variable data that was collected came from the Bureau of Labor and Statistics, the United States Census Bureau, and the Integrated Post-Secondary Education Data System (IPEDS). The dependent variable was the mean score of Carl Perkins Act reporting data that each state is required to report to federal authorities every year. The states were divided in two separate groups, centralized or decentralized form of governance. A regression analysis was performed in order to analyze if a relationship exists between the independent and dependent variables for each group. The research indicated that the form of governance does impact Carl Perkins Act reporting scores in a decentralized form of governance in relation to median income, but overall the model is not a good predictor of overall scores. A significant difference was found in states that have a decentralized form of governance and median household income in relation to Carl Perkins Act reporting data. However, the model, as a whole, did not produce significant results in relation to the independent and dependent variables. Considerations for future research are discussed.

Data from the McMaster Occupational Biomechanics Laboratory were consolidated to evaluate overall trends relating to tissue motion and blood flow in the carpal tunnel. Regarding tissue motion, displacements of the flexor digitorum superficialis (FDS) tendon and its subsynovial connective tissue (SSCT) were found to decrease with greater movement speed and a flexed wrist posture. Notably, changes to shear outcomes including relative tendon-SSCT displacement, the shear strain index (SSI), and maximum velocity ratio (MVR) demonstrate that greater movement speed contributes to SSCT damage according to the shear strain mechanism of injury theorised to promote carpal tunnel syndrome (CTS). Median nerve blood flow was also found to be implicated by wrist flexion, and appeared to decrease with greater CTS severity status. Finally, induced blood flow alteration of the carpal tunnel was found to elicit a median nerve blood flow response similar to the level found in CTS subjects, confirming its effectiveness as an intervention to study tissue motion in a CTS-like state. The influence of altered blood flow on tissue motion was differential, where the higher supradiastolic condition altered FDS displacement, and the lower subdiastolic condition affected SSCT displacement and SSI. These findings provide valuable evidence for changes in median nerve blood flow—and by extension, the local fluid environment within the carpal tunnel—not only being a consequence of SSCT fibrosis characteristic of CTS, but potentially also acting as a cause for said changes in carpal tunnel tissue motion. / Thesis / Master of Science in Kinesiology / This thesis aimed to evaluate and summarize key findings from the McMaster Occupational Biomechanics Laboratory relating to tissue motion and blood flow in the carpal tunnel. Performing repetitive finger movements faster and with a flexed wrist posture were found to decrease the distance travelled of the underlying finger tendon. Blood flow of the median nerve, which is implicated in carpal tunnel syndrome (CTS), is higher with forceful exertion and flexed wrist posture, and lower with greater severity of CTS. Finally, altering blood flow to the carpal tunnel was found to create a CTS-like environment, affected tissue motion in the carpal tunnel, and promoted movement disparity between these tissues that is associated with injury. This suggests that fluid/blood flow changes affecting the carpal tunnel is a plausible mechanism for increasing the likelihood of developing CTS.

In recent years, sparsity and compressive sensing have attracted significant attention in parameter estimation tasks, including frequency estimation, delay estimation, and localization. Parametric dictionaries collect signals for a sampling of the parameter space and can yield sparse representations for the signals of interest when the sampling is sufficiently dense. While this dense sampling can lead to high coherence in the dictionary, it is possible to leverage structured sparsity models to prevent highly coherent dictionary elements from appearing simultaneously in a signal representation, alleviating these coherence issues. However, the resulting approaches depend heavily on a careful setting of the maximum allowable coherence; furthermore, their guarantees apply to the coefficient vector recovery and do not translate in general to the parameter estimation task. We propose a new algorithm based on optimal sparse approximation measured by earth mover's distance (EMD). Theoretically, we show that EMD provides a better metric for the performance of parametric dictionary-based parameter estimation and $K$-median clustering algorithms has the potential to solve the EMD-optimal sparse approximation problems. Simulations show that the resulting compressive parameter estimation algorithm is better at addressing the coherence issuers without a careful setting of additional parameters.

The detection of variable stars in open clusters is an essential component of testing stellar structure and evolution theories. The ability to detect low-amplitude variability among cluster members is directly related to the quality of the photometric results. Point Spread Function (PSF) fitting is the best method available for measuring accurate magnitudes within crowded fields of stars, while high-precision differential photometry is the preferred technique for removing the effects of atmospheric extinction and variable seeing. In the search for new variable stars among hundreds or thousands of stars, the Robust Median Statistic (RoMS) is proven more effective for finding low-amplitude variables than the traditional error curve approach. A reputable computer program called DAOPHOT was used to perform PSF fitting, whereas programs, CLUSTER and RoMS, were created to carry out high-precision differential photometry and calculate the RoMS, respectively, on the open clusters NGC 225, NGC 559, NGC 6811, NGC 6940, NGC 7142, and NGC 7160. Twenty-two new variables and eighty-seven suspected variable stars were discovered, and time-series data of the new variables are presented.

Concerns regarding Mean Length of Utterance (MLU) has led to adaptations of this method of analysis. A recent study by Johnston (2001) introduced an alternative to MLU called MLU2. The current study investigates the split-half reliability of MLU and MLU2 as well as another alternative, Median Length of Utterance (Med-LU). Split-half reliability was found for these methods when segmented into Phonological and Communication Units. Split-half reliability of MLU2 was generally higher than that of MLU, and both were higher than Med-LU. The study suggests that MLU2 may also be a valuable tool for clinicians in analyzing child language.