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Despite the increasing popularity of latent class models (LCM) in educational research, methodological studies have not yet accumulated much information on the appropriate application of this modeling technique, especially with regard to requirement on sample size and number of indicators. This dissertation study represented an initial attempt to inform practitioners of desirable sample sizes and number of indicators under various conditions by using simulated data. The performance of LCM was evaluated in terms of both correct class extraction rates (i.e., correct identification of number of latent classes) and classification accuracy for dichotomous and continuous indicators. Manipulated factors included class separation, true number of latent classes, sample size, number of indicators, and class proportion. For both dichotomous and continuous indicators, class separation and true number of latent classes consistently demonstrated the largest effects on both correct class extraction rates and classification accuracy. The results suggest that LCM may not be recommended for use when class separation is small (operationally defined as 0.20 difference in indicator means for dichotomous indicators and half a standard deviation difference in indicator means for continuous indicators). When class separation is large (operationally defined as 0.50 difference in dichotomous indicator means and 2 standard deviation differences in continuous indicator means), models show acceptable correct class extraction rates and classification accuracy when certain conditions on sample size and number of indicators are met. Recommendations on sample size and number of indicators are provided taking into account researchers' level of knowledge of class separation and true number of latent classes. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Children’s ability to regulate emotions is very important to their socioemotional development. Maternal emotion socialization is significant in influencing children’s emotion regulation, especially among at-risk populations. The current dissertation presents the results of three studies which investigated maternal emotion socialization practices and child emotion regulation, while considering the specific risk factor in these socialization processes. In the first chapter, important concepts and theories concerning maternal emotion socialization, children’s emotion regulation, and factors influencing the socialization process are presented. Chapters 2, 3, and 4 present each individual study separately. In Chapter 2, the reciprocal relation between maternal emotion coaching and child emotionality was examined, while considering maternal parenting stress as a moderator on this reciprocal relation. In Chapter 3, the relations among maternal depressive symptoms, maternal rumination and child emotion regulation were explored. In Chapter 4, using a low-income, rural sample, the associations among emotion expression, behavioral regulation, and cortisol responses were explored, under different maternal parenting profiles. Finally, Chapter 5 presents an overall discussion of these findings with a focus on their research and clinical implications.

Main-chain poly[n]catenanes are topological macromolecules constructed by mechanicallyinterlocking many small cyclic monomer rings into a long chain. The mechanical bonds provide alarge degree of freedom to the polymer backbone and poly[n]catenanes are predicted to haveexceptional molecular flexibility and robustness. However, the synthesis of main-chainpoly[n]catenanes has not been achieved. This dissertation will discuss the first successful syntheticapproach toward main-chain poly[n]catenanes, utilizing the ring-closing reaction of a preassembledmetallosupramolecular polymer (MSP) template from rationally designed componentswith an isolation yield of 75~80%. Nuclear magnetic resonance (NMR) and gel permeationchromatography-multiangle laser light scattering (GPC-MALLS) confirms the mechanicalinterlocking structure and high molecular weight of the polycatenanes. Further study shows theproduct is a mixture of linear, branched and cyclic polycatenanes, which can be separated by sizeexclusion chromatography. Progress toward increasing the yield of polycatenane synthesis andimproving the formation of linear polycatenane will also be described.

Abstract: With the exponential growth of web image data, image tagging is becoming crucial in many image based applications such as object recognition and content-based image retrieval. However, despite the great progress achieved in automatic recognition technologies, none has yet provided a satisfactory solution to be widely useful in solving generic image recognition problems. Automatic technologies usually make certain assumptions, such as a limited number of object categories and how many objects there are in an image. With the goal of tagging generic images, so far, only manual tagging can provide precise image descriptions. However, the cost and tediousness of manual tagging is the major concern. The first effort to motivate people to tag images is the ESP game, proposed by Luis von Ahun. In the same vein, we ask the same question how can we motivate people to tag web images, which belongs to the research field of collective intelligence. So far, crowdsourcing, human computation (ESP game) and social computing are three major methods resolving the problem of motivating people to work collaboratively and to produce something intelligent. However, none of them can achieve the goal of collecting large scale tagged images at high quality for low cost. In this thesis, we propose a Social Monetization Computing (SMC) model, which incorporates monetary incentives into social computing to guarantee high quality work from both crowdsourcing workers and social web users for a low cost. In addition, we summarize a design guidance of a SMC system. In the light of SMC system design guidelines, we describe the evolutionary design and implementation of an image tagging system, called EyeDentifyIt, driven by image-click-ads framework. A series of usability studies are presented to demonstrate how EyeDentifyIt provides better user motivations, produces higher quality data, and requires less workload from workers, compared to state-of-the-art approaches. To further reduce workload involved in the image tagging process, we develop an efficient method for automatically parsing fashion images, which resolves three common problems including occlusions, background spills and over smoothing of infrequent labels, in existing fashion parsing methods. The experiment results demonstrate that the proposed method outperforms state-of-the-art clothing parsing methods from both quantity and quality perspectives.

This study tested a model of children's emotionality as a moderator of the links between maternal emotion-related socialization and depressive symptoms and child emotion regulation. Participants were 129 mother-preschooler dyads. Child affect and emotion regulation were assessed observationally during a laboratory mood induction task, and were factorized into 3 categories: passive soothing, negative focus on distress, and positive engagement. Hierarchical linear regression models indicated that child positive emotionality moderated the links between maternal emotion-related socialization and depressive symptoms and child emotion regulation; whereas child negative emotionality moderated the links between maternal support and child emotion regulation. Findings suggest a transactional perspective to understand the effects of both child characteristics and familial influence on child emotion regulation.

The purpose of this study was to examine whether infants' social attention, as well as their joint attention behaviors uniquely predicted emerging language abilities. This longitudinal study examined attention regulation skills, joint attention behaviors, infants' expressive/receptive language (current), emerging communication abilities at 16- and 17-month-old (time 1); expressive/receptive language (subsequent) at 18- 19-month-old (time 2). Infants' sustained attention was measured by their attention control to a central stimulus in the presence of a distracter competing for their attention. Dynamic human face (upright, inverted) and abstract display with their matched voice tracks were used to separately measure infants' attention regulation to different types of events. Infants' sustained attention was estimated by their latencies away from central stimuli to distracters, as well as their fixation duration and gaze count on central events and distracters. It was found that infants' latency away from the abstract figure toward the distracter was the only variable that significantly negatively predicted current expressive vocabulary. Initiating joint attention was observed to significantly predict infants' abilities in current receptive vocabulary. The emerging language communication ability predicted expressive vocabulary at two times. In addition, infants' fixation and count to the upright speaker's face and eyes contributed significant amount of variance in initiating joint attestation. The fixation and gaze count on the distracter in the upright condition significantly predicted infants' emerging language skills.

Modification of major lipid raft components, such as cholesterol and ceramide, plays a role in regulation of Ultraviolet B light (UVB)-induced apoptosis. Upon UVB irradiation, an alternation of major lipid raft components can lead to the recruitment/activation of raft-associated proteins and initiation of downstream apoptotic signaling pathways. To identify potential regulators of UVB-induced apoptosis, we used two-dimensional gel electrophoresis and mass spectrometry fingerprint analysis to identify proteins that are altered in the rafts after UVB irradiation. Our data shows that levels of several proteins, including prohibitin (PHB), were changed in lipid rafts after UVB irradiation. PHB plays a critical role in many cell functions, such as cell-cycle control, cell proliferation, senescence, development, apoptosis, and tumor suppression. However, until now, no report has identified a role for PHB in mediating apoptosis upon UVB irradiation. We now demonstrate that while total and cell surface PHB expression was not changed, the protein was enriched in lipid rafts after UVB irradiation. Reduced expression of PHB using siRNA knockdown resulted in an increase in apoptosis after UVB irradiation.To reveal the detailed mechanism for PHB-mediated apoptosis upon UVB irradiation, we evaluate whether PHB is involved in regulation of Akt and Raf activity as well as oxidative stress in UVB-irradiated HaCaT cells. Our data shows that upon UVB irradiation PHB is translocated to the lipid rafts, which is correlated with a release of both Akt and Raf from membrane. Overexpression of Akt and/or Raf impedes UVB-induced lipid rafts translocation of PHB. Immunoprecipitation analysis indicates that UVB alters the interactions among PHB, Akt, and Raf. Reduced expression of PHB leads to a decreased phosphorylation of Akt and ERK, as well as a decreased activity of Akt, and an increased apoptosis of the cells after UVB irradiation. In addition, our data shows that the effect of LNAC on UVB-mediated apoptosis and proliferation is independent of PHB knockdown, suggesting an alternative pathway independent of UVB-induced oxidative stress. These results suggested that PHB regulates UVB-induced apoptosis of keratinocytes via a mechanism that involves detachment from Akt and Raf on the plasma membrane, and sequentially lipid rafts translocation.

Vehicle-to-vehicle (V2V) communication research has been growing steadily over the past decade. The V2V channel differs significantly from classic cellular wireless channels specifically in its relatively low transmitter (Tx) and receiver (Rx) antenna heights, and that both Tx and Rx and some significant scatterers are all mobile. Given the dynamic nature of the V2V environment, the channel may be statistically non-stationary (NS), and traditional wide-sense stationary uncorrelated scattering (WSSUS) channel models will only be applicable for short durations. In this dissertation, we propose and evaluate NS V2V channel models in the 5 GHz band. We present TDL models for additional values of channel bandwidth. Together with the previously reported results for 5 MHz and 10 MHz channel bandwidths, they comprise a set of V2V TDL models for a wide range (from 1 MHz to 50 MHz) of channel bandwidths. New Small City measurements were conducted in two small cities with antennas inside the cars. The results were discussed and compared to previously measured Small City data. We also improve our Markov modeling of multipath persistence processes via the development of higher order homogeneous, 1st-order non-homogeneous and correlated 1st-order homogenous discrete time Markov chain (DTMC) models for persistence. Based upon the trade-off between model fidelity and implementation complexity, the 2nd-order homogeneous DTMC model is preferable, and the correlated DTMC models may be useful when highest model fidelity is needed. Empirical two-tap approximation of V2V channels is also discussed. With parameters directly derived from the measured delay spread statistics, the two-tap models yield RMS-DS distributions that agree well with the measured data. Further evaluation of the two-tap models on the BER performance for BPSK indicates a good match of the simulation results between the two-tap and the complete models, especially for low SNR’s. Thus our simple two-tap model could be useful as an informative alternative to the complete NS models. The GBS model is another common type of V2V channel model. An example V2V geometry model is developed and compared to our TDL model both qualitatively and quantitatively.

Several studies have found that adult caretakers usually hyperarticulate to infants by modifying their voice in ways that promote and sustain infants' attention. This articulation when engaging in infant directed speech (IDS) can result in "clear speech" by the expansion of the vowel space area. The degree of speech clarity produced by caregivers appears to provide advantages for young language learners to promote lexical perception and learning. However few studies have ever examined whether infants are able to perceive the difference between hyperarticulation and normal speech. In this study, 7-to 12-month-olds' (n=17) speech discrimination when hearing hyperarticulated and non-hyperarticulated words in mothers' natural speech production was examined. The degree of speech clarity was determined by the relations of the first (F1) and second formant frequencies (F2) of the vowel. The result showed that there was no discrimination between listening to hyperarticulated and non-hyperarticulated words, indicating that the benefit accrued by exposure to clear speech may require no selective attention on the part of the infant. Thus the advantages of hyperarticulation might be related to other characteristics.