There is little consensus in the literature as to which approach for classification of Whole Genome Shotgun (WGS) sequences is most accurate. In this defense, two of the most popular classification algorithms, Kraken2 and Metaphlan2, were examined using four publicly available datasets. Surprisingly, Kraken2 reported not only more taxa but many more taxa that were significantly associated with metadata. By comparing the Spearman correlation coefficients of each taxa in the dataset against more abundant taxa, it was found that Kraken2, but not Metaphlan2, showed a consistent pattern of classifying low abundance taxa that were highly correlated with the more abundant taxa. Neither Metaphlan2, nor 16S sequences that were available for two of four datasets, showed this pattern. These results suggest that Kraken2 consistently misclassified high abundance taxa into the same erroneous low abundance taxa. These “phantom” taxa have a similar pattern of inference as the high abundance source. Because of the ever-increasing sequencing depths of modern WGS cohorts, these “phantom” taxa will appear statistically significant in statistical models even with a low classification error rate from Kraken2. These findings suggest a novel metric for evaluating classifier accuracy.
Sexual and gender minority (SGM; e.g., lesbian, gay, bisexual, transgender) individuals are recognized as a health disparity population due to the undue burden of mental and physical health disorders among this population. The National Institutes of Health Sexual and Gender Minority Research Office (NIH-SGMRO) generated a social-ecological research framework for SGM health disparity research, articulating need for further research in the areas of (a) minority stress, (b) resilience, (c) violence and discrimination, and (d) intersecting identities. Informed by this research framework, the current dissertation contains three studies attending to these four research areas. Study one is a grounded theory of SGM suicide; 30 interviews with SGM adults in the United States lead to the co-construction of the SGM Suicide Risk and Protection (SuRAP) which outlines the impact of minority stress on suicide outcomes for SGM adults. Study two is a psychometric evaluation of the Brief Resilience Scale (BRS) among a sample of alternative sexuality community members (e.g., persons engaging in non-monogamy and kink), validating use of the BRS in future resilience-based research among this population. Study three is an examination of the mental health outcomes of sexual harassment, using a Psychological Mediation Framework to assess the ways in which social support, emotion regulation, and internalized minority stress explain the sexual harassment-mental health linkage among trauma-exposed sexual minority women. Taken together, findings indicate that therapeutic modalities such as Affirmative Dialectical Behavior Therapy may be of clinical utility.
Despite recurring arguments over the course of a century, intentional education geared toward the whole child in schools has not occurred (Khalsa & Butzer, 2016; Sabey, 2019). Consequently, children often emerge from high school exhibiting sufficient academic content knowledge applicable towards a successful career path, but lack social emotional skills essential for the development of optimal mental health and well-being (Butzer et al., 2016). Birth to age eight is precisely the time when the foundation of the whole child originates and when the building blocks for future academic success and social emotional well-being are established (NAEYC, 1986; Copple & Bredekamp, 2009). As a result of an existing gap underlining early elementary educator perceptions and experiences of social emotional learning (SEL), the purpose of this study was to discover the perceptions and experiences of full-time lead educators and paraprofessionals who teach SEL in Kindergarten through Second grade classrooms. Data was collected through a qualitative multiple-perspective case study design using a semi-structured interview process. Interview transcripts were analyzed and coded using a within-case analysis. Data analysis led to the development of seven themes: (1) Defining SEL, (2) Preparedness in Teaching SEL, (3) Barriers of SEL, (4) Educator Roles and Responsibilities, (5) High Priority of SEL, (6) SEL as a Positive Influence/Impact on Students, and (7) Evidence of SEL Skills. The findings of this study suggest that educators in K-2 classrooms (1) place SEL as a high priority in their classrooms, (2) perceive that SEL has a positive impact and influence on students based on observations, and (3) indicate how barriers such as under preparedness and lack of support inhibit SEL teaching in their classroom whereas positive school culture and pertinent resources greatly assist in effective facilitation of SEL.
Each year in the United States (U.S), one in five adults experience mental illness and one in six youth ages 6-17 experience a mental disorder (NAMI, 2020). While mental illness can affect individuals at similar rates, minority populations suffer from existent disparities in mental healthcare that have been exacerbated by the impact of COVID-19. Help-seeking behaviors of racial and ethnic minorities in the US have historically been influenced by the lack of trust in the medical system. When experiences of prejudice and discrimination are present in the counseling experience, they lead to damaging outcomes for minorities including misdiagnosis, receipt of less preferred forms of treatment, increased rate of premature termination, and overall dissatisfaction with service delivery in minority clients (Ridley et al., 2010; Rutgers University, 2019). Counselors who do not address biases, assumptions, and their own epistemological views risk operating within the oppressive framework of the dominant culture (Katz, 2014; Owen, 2017; Owen et al., 2018; Sue et al., 1992). Despite the growing support of cultural humility as complementary or even an alternative to cultural competence in counselor multicultural pedagogy, little has been examined about the ways in which this perspective can be enhanced in counselor education programs. Therefore, a standard multiple regression was utilized to examine the impact of intrinsic spirituality, common humanity, and affective empathy on cultural humility in counseling students. Results indicated that common humanity contributed significantly to the prediction of cultural humility accounting for 16% of the variance. Implications, limitations, and recommendations for future research are discussed.
Short-term load forecasting (STLF) is a conventional process at power companies to serve for better decision-making in their daily operations. Weather factors play a key role in STLF. In practice, an online STLF system typically requires the use of weather forecasts as input when projecting the future load, with associated weather forecast errors. This type of forecasting is known as ex-ante forecasting. Nevertheless, most existing academic literature developed load forecasting techniques under the ex-post forecasting settings, where the actual weather information is used in the forecast period. Meanwhile, the robustness of STLF models to the real weather forecast errors has rarely been studied in the literature. The gap between the practice and the research study is often due to the shortage of historical weather forecasts. In this research, we aim to close this gap by proposing two new frameworks to select better models in short-term ex-ante load forecasting. Compared to the conventional research which focuses on ex-post load forecast accuracy in the model development, both frameworks consider the impact of real weather forecast errors and are better fitted to field practices.
The effectiveness of the proposed frameworks is confirmed using an empirical case study at a medium-sized US utility with load data from multiple supply areas and real temperature forecasts. Compared to a state-of-the-art benchmark that uses the historical ex-post load forecast accuracy for model selection, the first framework leads to 2.4% improved accuracy on average. A further study among the weather sensitive hours (i.e., the hours when a smaller error in the temperature forecast may lead to a greater inaccuracy in the load forecast) suggests that the first framework outperforms the benchmark by 3.1% on average, although its performance is subpar when the predicted temperature forecast accuracy gets worse. The second framework addresses this issue effectively and improves the accuracy of the first framework by 7.4% for the hours with worse predicted temperature forecast accuracy. Overall, the second framework leads to an average of 0.8% improvement over the first framework and 3.9% improvement over the benchmark among the weather sensitive hours.
Customer churn leads to higher customer acquisition cost, lower volume of service consumption and reduced product purchase. Reducing the outflow of the customers by 5% can double the profit of a typical company. Therefore, it is of significant value for companies to reduce customer outflow. In this dissertation research, we mainly focus on identifying the customers with high chance of attrition and providing valid and trustworthy recommendations to reduce customer churn.
We designed and developed a customer attrition management system that can predict customer churn and yield actionable and measurable recommendations for the decision makers to reduce customer churn. Moreover, reviews from leaving customers reflect their unfulfilled needs, while reviews of active customers show their satisfactory experience. In order to extract the action knowledge from the unstructured customer review data, we thoroughly applied aspect-based sentiment analysis to transform the unstructured review text data into a structured table. Then, we utilized rough set theory, action rule mining and meta-action triggering mechanism on the structured table to generate effective recommendations for reducing customer churn. Lastly, in practical applications, an action rule is regarded as interesting only if its support and confidence exceed the predefined threshold values. If an action rule has a large support and high confidence, it indicates that this action can be applied to a large portion of customers with a high chance. However, there is little research focused on improving the confidence and coverage of action rules. Therefore, we proposed a guided semantic-aided agglomerative clustering algorithm to improve the discovered action rules.
Studies assessing health disparities in the United States primarily compare White and Black individuals without accounting for the heterogeneity within racial groups. The present study utilizes the racial context of origin framework to identify potential mechanisms that can explain differences in health between foreign-born Black (FBB) and US-born Black (USB) individuals. Using self-report questionnaires, this study examined the interactive effects of internalized racism, perceived discrimination, and racial context of origin on physical health and perceived discrimination reactivity. Further, motivation to succeed, belief in meritocracy, shared racial fate, and connection and belonging to the Black race were assessed to discern factors contributing to differential interactions by racial context of origin. Results indicate that internalized racism is negatively associated with physical health for FBB, but not USB. The 3-way interactions of internalized racism, perceived discrimination, and racial context of origin on physical health and perceived discrimination reactivity were not significant. Motivation to succeed, belief in meritocracy, shared racial fate, and connection and belonging to the Black race did not provide insight to differences in the role of racial context of origin in the association between internalized racism and physical health. Exploratory analyses revealed that racial centrality is a promising factor in understanding health differences by racial context of origin. Notable preliminary analyses and group differences are also discussed. These findings contribute to the understanding of racial context of origin and provide insight to race-related variables that may aid in understanding of differences in health by racial context of origin.
This dissertation addresses a novel approach to assessing users' interaction tendencies on social media as a basis for personalized interventions that can make the truth louder and mitigate the spread of misinformation. This research leverages users' high and low interaction tendencies to amplify truth by increasing users' interactions with verified posts and decreasing their interactions with unverified posts. For designing personalized interaction-focused interventions, this dissertation presents an Active-Passive (AP) framework and three principles of social media interactions to make the truth louder on social media. This dissertation presents a study including tasks and questionnaires to investigate users' differences in the Active-Passive (AP) framework for utilizing platforms' basic interaction functionalities, such as like, comment, or share buttons. The results show that users use the interaction functionalities differently due to their interaction tendencies; users with high interaction tendencies use more interaction functionalities, and users with low interaction tendencies use less.
This dissertation presents an analysis of participants' responses to the design principles and investigates users' additional sharing functionality usage and preference for platform-based incentives. The results show that users with lower interaction tendencies share verified information more when they receive additional interaction support. Furthermore, due to the interaction tendencies, users exhibit opposite preferences for platform-based incentives that can encourage their participation in making the truth louder. Users with high interaction tendencies prefer incentives that highlight their presence on the platform, and users with low interaction tendencies favor incentives that can educate them about the impact of their participation on their friends and community. This dissertation concludes with a discussion on personalized interaction-focused interventions and provides directions for future research.
Fertility preservation would benefit young males who must undergo treatments that can result in sterilization, such as radiation treatments for cancer. This can be achieved by removing some testicular tissue before treatment and putting it into frozen storage for later use, a process known as cryopreservation. Cryopreservation requires the use of cryoprotective agents (CPAs), such as dimethyl sulfoxide (DMSO), to reduce injury from ice crystal formation. Because DMSO can be toxic at high exposure levels, it is important to determine the exposure time that is necessary to achieve adequate concentrations for freeze protection, without over-exposing the tissue. Mass diffusion models can be used to predict this loading time, but these models depend on property parameters that are often unknown, such as the mass diffusion coefficient for a given CPA in a specific tissue.
To facilitate the development of cryopreservation protocols for testicular tissue, we determined the mass diffusion coefficient for DMSO in thin (~1 mm) tissue sections that were precision cut from feline testes that were discarded from veterinary sterilization procedures. Samples were placed in a custom tube that was mounted on the surface of an Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) and then exposed to DMSO on the opposite side. Spectra were recorded for 60 minutes, and the area of peak centered at 950 cm-1 was determined as a function of time. This time course absorbance data was then fit to an equation developed by Barbari and Fieldson (1993) that considers both mass diffusion and tissue absorption properties. By minimizing the sum of squares, estimates for the DMSO diffusion coefficient were obtained from each time sequence. Samples were analyzed at 22°C and 4°C.
Because of the inherent variability in biological tissues, alginate-gelatin and agarose were also evaluated for their potential as reference standard materials, to facilitate methodology development and training. Alginate compacted to thicknesses of 1.7 ± 0.2 mm resulting in an effective DMSO diffusion coefficient of 4.3 ± 0.3 x 10-6 cm2/s (n=4). Agarose compacted to thicknesses of 1.1 ± 0.1 mm. The effective diffusion coefficient of DMSO in agarose was 9.2 ± 0.2 x 10-6 cm2/s at 22°C (n=9) and 5.6 ± 0.2 x 10-6 cm2/s (n=9) at 4°C. Although alginate and agarose had similar variability in their thicknesses, agarose had much lower within batch and between batch variability than alginate-gelatin for the effective diffusion coefficients and thus is the preferred reference material for ATR-FTIR diffusion studies. Testicular tissue samples compacted to 2.1 ± 0.7 mm. The effective diffusion coefficient was 10.3 ± 4 x 10-6 cm2/s at 22°C and 7.1 ± 5 x 10-6 cm2/s at 4°C. The high variability is likely due to native variability in the testicular tissue samples. However, these nominal values can be used to inform preservation procedure planning.
Diversity initiatives are often ineffective because they characterize differences at the group-level, and therefore, do not adequately address individuals’ specific identity-related challenges. The purpose of this study is to use a network-based approach to studying identity to provide a comprehensive examination of the wide range of identities that are salient and important for individuals who are members of diverse race and gender groups, namely White and Black men and women at work. Additionally, I apply intersectionality theory to understand how multiple identities are constructed into overall self-concepts at work and more specifically, how individuals perceive intersections between their multiple identities. According to intersectionality theory, I expect that multiple identities will co-exist and subordinate (i.e., historically marginalized) social identities will be more central for women and racial minorities employees as opposed to dominant (i.e., historically non-marginalized) identities. I also integrate job-demands resources theory to develop and test hypotheses concerning the structural relationships between identities (i.e., conflict, compatibility, centrality) and authenticity at work. Specifically, I propose that identity conflict, compatibility, and centrality are identity structures that serve as resources that can enable or constrain authentic self-expression at work. I test these hypotheses across two studies. In summary, this work sheds theoretical and empirical light on the complex nature of multiple identities at work and how diversity initiatives can more effectively address identity dimensions that intersect and affect personal work experiences.