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Introduction: Wearable technologies play an important contemporary role in the measurement of physical activity (PA) and promotion of human health across the lifespan, including for young people (i.e., children, adolescents, and young adults). As new objective wearable technologies continue to develop, standardized approaches to documenting validation parameters (i.e., measures of accuracy, precision, and bias) are needed to ensure confidence and comparability in step-defined PA. Purpose: To produce validity parameters for step counting wearable technologies during treadmill walking in young people 6-20 years of age Methods: 120 participants completed 5-minute treadmill bouts from13.4 to 134.1 m·min-1. Participants wore eight technologies (two at the arm/wrist, four at the waist, one on the thigh, and one on the ankle) while steps were directly observed. Speed, wear location, and age -specific measures of accuracy (mean absolute percent error; MAPE), precision (correlation coefficient, standard deviation; SD, coefficient of variation; CoV), and bias (percent error; PE) were computed and cataloged. Results: Speed and wear location had a significant effect on accuracy and bias measures for wearable technologies (pConclusion: While the analyses indicate the significance of speed and wear location on wearable technology performance, the useful and comprehensive validity reference values cataloged herein will help optimize measurement of PA in youth. Future research should continue to rigorously validate new wearable technologies as they are developed, and also extend these standardized reference values developed in the laboratory to the free-living environment.

Learning the count list (one, two, three, …) is a critical stepping-stone for the acquisition of number concepts. Most research about counting, however, is done in the behavioral domain, and little is known about the neural representations underlying counting sequences. Here, we test the hypothesis that transitional knowledge within a counting sequence exist both at sensory and conceptual (ordinal and magnitude) levels. To test this hypothesis, we employed a passive-listening violation-to-expectation fMRI paradigm where adult participants heard auditory count sequences that were correct (4 5 6 7) or violated at the end (4 5 6 8; consecutiveness) and, orthogonally, that were ordered or unordered (orderedness). Another orthogonal dimension was the manipulation of sensory sequence violation where the voice speaking the numbers was consistent throughout the trial or could change on the last number (voice identity). This 2x2x2 factorial design was analyzed using univariate and multivariate pattern analyses. Three clusters in the right fronto-parietal network (BA44, BA46, and IPS) showed greater neural response to violations to orderedness. Of the three clusters, the anterior IFG (BA46) demonstrated the encoding of consecutiveness. Interestingly, the bilateral STG, which showed a robust effect to violations in voice identity, also demonstrated the encoding of consecutiveness. These results indicate that a right-lateralized fronto-parietal network activity can differentiate between a count list and random numbers, while BA46 and bilateral STG respond specifically to violations of the count sequence, suggesting specific mechanisms in the brain for processing consecutive numbers in both the perceptual and cognitive levels.

Subitizing, a quick apprehension of the numerosity of a small set of items, is inconsistently utilized by preschool educators to support early number understandings (Sarama & Clements, 2009). The purpose of this qualitative study is to investigate the relationship between children’s number understanding and subitizing activity. Sarama and Clements (2009) consider students’ subitizing activity as shifting from reliance upon perceptual processes to conceptual processes. Hypothesized mental actions carried into subitizing activity by children have not yet been empirically investigated (Sarama & Clements, 2009). Drawing upon Piaget’s (1968/1970) three mother structures of mathematical thinking, the theoretical implications of this study consider expanding the scope of Piaget’s (1968/1970) definition of topological thinking structures to include patterned orientations. Increasing the scope of this definition would allow for the investigation of the development of topological thinking structures and subitizing activity. An 11-week teaching experiment was conducted with six preschool aged children in order to analyze student engagement with subitizing tasks (Steffe & Ulrich, in press). To infer what perceptual and conceptual processes students relied upon when subitizing, tasks were designed to either assess or provoke cognitive changes. Analysis of interactions between students and the teacher-researcher informed this teacher-researcher of cognitive changes relative to each student’s thinking structure. Results indicated that students rely upon the space between items, symmetrical aspects of items, and color of items when perceptually subitizing. Seven different types of subitizing activity were documented and used to more explicitly describe student reliance upon perceptual or conceptual processes. Conceptual subitizing activity was redefined in this study, as depending upon mental reversibility and sophisticated number schemes. Students capable of conceptual subitizing were also able to conserve number. Students capable of conserving number were not always capable of conceptual subitizing. The symmetrical aspects of an item’s arrangement elicited students’ attention towards subgroups and transitioning students’ perceptual subitizing to conceptual subitizing. Combinations of counting and subitizing activity explained students’ reliance upon serial and classification thinking structures when transitioning from perceptual subitizing to conceptual subitizing. Implications of this study suggest effectively designed subitizing activity can both assess students’ number understandings, and appropriately differentiate preschool curriculum. / Ph. D.

Fiber-optic Bragg grating (FBG) sensors are a very attractive technology for the measurement of strain and temperature. They have many advantages over conventional sensors in sensing applications such as sensitivity, immunity to electromagnetic interferences,large bandwidths,capability of remote operation and the potential power to sense micro strain at high temperature. They can be directly embedded into many structures such as concrete to evaluate the material deformation. FBGs are fabricated by photo-inscribing through a phase mask technology on a photosensitive fiber. A periodic refractive index is formed in the fiber core, introducing a reflection at the Bragg wavelength. Since the FBG is characterized by a low insertion loss and controllable reflectance, it has the potential to be multiplexed in very large numbers. The major purpose of this dissertation research is to develop an innovative, high- resolution fiber Bragg grating sensing system using photon-counting optical time domain reflectometry (pc-OTDR) based multiplexing technology. The system uses a Fresnel reflection OTDR with a zero deadzone to detect FBG sensors, which improves both the system detection ability and spatial resolution. A low reflectance FBG with broad bandwidth has been developed that is appropriate for the pc-OTDR measurement. Hundred of multiplexed sensors have been implemented in this system. Two theoretical analyses and preliminary results are presented. The greatest advantage of the system is to increase the maximum multiplexing sensor number to one thousand within a short fiber range. Self-referencing demodulation is necessary to eliminate multiplexed system noise caused by the source power fluctuation and fiber bending effects. A referencing FBG with a different wavelength from the sensing FBG has to be introduced to achieve compensation of disturbances in the measurement. The spectral properties of the FBGs and the combination of WDM/TDM are also discussed to evaluate multiplexing sensor performance. The sensor crosstalk and other noise performances are assessed to evaluate the possibility of large scale multiplexing. / Ph. D.

A network (graph) is a powerful abstraction for interactions among entities in a system. Examples include various social, biological, collaboration, citation, and co-purchase networks. Real-world networks are often characterized by an abundance of triangles and the existence of well-structured communities. Thus, counting triangles and detecting communities in networks have become important algorithmic problems in network mining and analysis. In the era of big data, the network data emerged from numerous scientific disciplines are very large. Online social networks such as Twitter and Facebook have millions to billions of users. Such massive networks often do not fit in the main memory of a single machine, and the existing sequential methods might take a prohibitively large runtime. This motivates the need for scalable parallel algorithms for mining and analysis. We design MPI-based distributed-memory parallel algorithms for counting triangles and detecting communities in big networks and present related analysis. The dissertation consists of four parts. In Part I, we devise parallel algorithms for counting and enumerating triangles. The first algorithm employs an overlapping partitioning scheme and novel load-balancing schemes leading to a fast algorithm. We also design a space-efficient algorithm using non-overlapping partitioning and an efficient communication scheme. This space efficiency allows the algorithm to work on even larger networks. We then present our third parallel algorithm based on dynamic load balancing. All these algorithms work on big networks, scale to a large number of processors, and demonstrate very good speedups. An important property, very related to triangles, of many real-world networks is high transitivity, which states that two nodes having common neighbors tend to become neighbors themselves. In Part II, we characterize networks by quantifying the number of common neighbors and demonstrate its relationship to community structure of networks. In Part III, we design parallel algorithms for detecting communities in big networks. We propose efficient load balancing and communication approaches, which lead to fast and scalable algorithms. Finally, in Part IV, we present scalable parallel algorithms for a useful graph preprocessing problem-- converting edge list to adjacency list. We present non-trivial parallelization with efficient HPC-based techniques leading to fast and space-efficient algorithms. / Ph. D.

Platelet rich plasma (PRP) is a popular autologous biological therapy used for the treatment of various equine ailments, including tendon and ligament injuries, osteoarthritis, and cutaneous wounds. A number of commercial products are available for producing PRP, each generating a slightly different product. Variations in platelet numbers and white blood cell (WBC) counts are believed to be the most critical variables, as they are directly related to concentrations of growth factors and inflammatory cytokines. Accurate documentation of platelet numbers is essential for prospective evaluation of clinical outcomes, but can be problematic in platelet concentrates depending on the counting method employed. The objectives of this study were to compare the performance of four platelet counting technologies in equine platelet concentrates and to evaluate the ability of the Magellan PRP system to concentrate equine platelets. We hypothesized that there would be no differences in platelet counts among the four counting technologies and that the Magellan system would generate platelet concentrations greater than 500,000/μL. Citrated whole blood was collected from 32 horses and platelet, WBC, and red blood cell concentrations were measured using a commercial hematology analyzer (Advia 2120) prior to preparation of PRP using the Magellan system. Platelets were quantified in individual identical aliquots of equine PRP produced by the Magellan system (n=32) using three different technologies: optical scatter (Advia 2120), impedance (CellDyn 3700), and hand count using direct microscopy (Thrombo-TIC). An immunofluorescent counting method was performed on a subset of 15 of the 32 samples using a mouse monoclonal anti-sheep antibody against integrin alpha αIIbβ₃ (anti-CD41/CD61) and a fluorescent secondary antibody. Measured platelet concentrations were compared using Passing and Bablok regression analyses and mixed model ANOVA. The Magellan PRP system yielded mean (± SD) platelet and WBC counts of 893,090 ± 226,610/μL and 35,806 ± 9,971/μL, respectively. Platelet counts generated by optical scatter were consistently higher than those generated by impedance. Systematic and proportional biases were observed between these two automated methods. No bias (systematic or proportional) was observed among any of the other counting methods. Despite the bias detected between the two automated systems, there were no significant differences on average among the four counting methods evaluated, based on the ANOVA. All four platelet counting methods tested are therefore suitable for quantifying platelets in equine PRP for clinical applications. The Magellan PRP system consistently generated desirably high platelet concentrations as well as higher than expected WBC concentrations. The high platelet concentrations served as a good test medium for the study; however, the concurrent high WBC counts may be undesirable for selected orthopedic applications. / Master of Science

Predicting fatigue failure is a critical design element for many engineering components and structures subject to complex service conditions. In high-temperature and corrosive environments, many materials exhibit rate dependent phenomena that can significantly alter safe service life predictions. Existing cycle processing techniques such as Peak Counting, Simple Range, and the Rain Flow method are able to resolve complex service histories into sets of simple cycles, but these methods are unable to handle time-related parameters such as engage rate and cycle sequence. To address this, a cycle processor was written in FORTRAN 95 later termed the Multi-Algorithm Cycle Counter (MACC). This code was utilized as a platform to develop, test, and study various methods of extracting and interpreting rate parameters extracted from cycles defined by existing counting algorithms.

<p dir="ltr">X-ray computed tomography (CT) based on photon counting detectors (PCD) extends standard CT by counting detected photons in multiple energy bins. PCD data can be used to increase the contrast-to-noise ratio (CNR), increase spatial resolution, reduce radiation dose, reduce injected contrast dose, and compute a material decomposition using a specified set of basis materials [1]. Current commercial and prototype clinical photon counting CT systems utilize PCD-CT reconstruction methods that either reconstruct from each spectral bin separately, or first create an estimate of a material sinogram using a specified set of basis materials and then reconstruct from these material sinograms. However, existing methods are not able to utilize simultaneously and in a modular fashion both the measured spectral information and advanced prior models in order to produce a material decomposition. </p><p dir="ltr">We describe an efficient, modular framework for PCD-based CT reconstruction and material decomposition using Multi-Agent Consensus Equilibrium (MACE). Portions of this dissertation appear in [2]. Our method employs a detector proximal map or agent that uses PCD measurements to update an estimate of the path length sinogram. We also create a prior agent in the form of a sinogram denoiser that enforces both physical and empirical knowledge about the material-decomposed sinogram. The sinogram reconstruction is computed using the MACE algorithm, which finds an equilibrium solution between the two agents, and the final image is reconstructed from the estimated sinogram. Importantly, the modularity of our method allows the two agents to be designed, implemented, and optimized independently. Our results on simulated data show a substantial (2-3 times) noise reduction vs conventional maximum likelihood reconstruction when applied to a phantom used to evaluate low contrast detectability. Our results with measured data show an even higher reduction (2-12 times) in noise standard deviation. Lastly, we demonstrate our method on a Lungman phantom that more realistically represents the human body. </p>