UBIR Repository (Univ. at Buffalo)
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Creating a Self-Help Pamphlet Presenting Self-Care and Self-Care Resources for Registered Nurses Working on a Telemetry and Non-Telemetry Medical Surgical Unit in a Hospital to Help Manage Stress and Promote Work-Life Balance
No full textUB SON, DNP Research ProjectStress is a major contributing factor for registered nurse (RN) turnover and shortages. It is estimated that approximately 55% of RNs in the United States will leave their first job within six years of graduation and that over 200,000 new RNs will be needed annually through 2026 to fill jobs and to replace retiring nurses. It is essential that employers take an active role in making RNs aware of resources available to them to promote positive coping with work related stressors and professional quality of life. The purpose of this Doctor of Nursing Practice (DNP) project was to create an educational self-help pamphlet for RNs working in a telemetry and non-telemetry medical surgical unit at a hospital on self-care and self-care resources to help manage stress and promote professional quality of life. Pender’s (2011) Health Promotion Model (HPM) served as the theoretical framework for this DNP project
Hole in One: An Element Reduction Approach to Modeling Bone Porosity in Finite Element Analysis
No full textM.A.Finite element analysis has been an increasingly widely applied biomechanical modeling method in many different science and engineering fields over the last decade. In the biological sciences, there are many examples of FEA in areas such as paleontology and functional morphology. Despite this common use, the modeling of trabecular bone remains a key issue because their highly complex and porous geometries are difficult to replicate in the solid mesh format required for many simulations. A common practice is to assign uniform model material properties to whole or portions of models that represent trabecular bone. In this study we aimed to demonstrate that a physical, element reduction approach constitutes a valid protocol for addressing this problem in addition to the wholesale mathematical approach. We tested a customized script for element reduction modeling on five exemplar trabecular geometry models of carnivoran temporomandibular joints, and compared stress and strain energy results of both physical and mathematical trabecular modeling to models incorporating actual trabecular geometry. Simulation results indicate that that the physical, element reduction approach generally outperformed the mathematical approach: physical changes in the internal structure of experimental cylindrical models had a major influence on the recorded stress values throughout the model, and more closely approximates values obtained in models containing actual trabecular geometry than solid models with modified trabecular material properties. In models with both physical and mathematical adjustments for bone porosity, the physical changes exhibit more weight than material properties changes in approximating values of control models. Therefore, we conclude that maintaining or mimicking the internal porosity of a trabecular structure is a more effective method of approximating trabecular bone behavior in finite element models than modifying material properties.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
MmWave Beam Prediction with Deep Learning: A Multivariate Parallel Time Series Approach
No full textM.S.Deep learning techniques have revolutionized many areas of science due to their unique properties like adaptability, scalability, and the potential to rapidly adjust to new and unknown challenges. This thesis aims to revolutionize the methodology behind the millimeter-wave (mmWave) beamforming in the same way. The main objective of this thesis is to reduce the time complexity for finding the best beam pair in an mmWave link by transitioning from a conventional brute force approach of testing all possible beam pairs, with polynomial time complexity of O(n2), to a deep learning solution, with time complexity of constant time of O(1). The collected SNR data of all beam pairs was interpreted to a multivariate parallel time series for the lateral motion with a fixed step size. However, the main challenge was to choose how to fit this data to an LSTM, a short form of Long Short Term Memory, considering the technical limitations to build numerous different multivariate time series models for each beam pair. Even if we somehow manage to build an independent LSTM model for each beam pair, then there would be very high chances of missing the inherent relationship among the beam pairs. Hence, we came up with an approach that combines both of the shortcomings - a multivariate parallel time series approach. To ensure that the data we used in our evaluation is reliable and an accurate representation of a real-world scenario, we collected the data using a real hardware – the X60 testbed. X60 is the first SDR-based testbed for 60 GHz WLANs, featuring fully programmable MAC/PHY/Network layers, multi-Gbps rates, and a user-configurable 12-element phased antenna array. Our evaluation shows that deep learning can considerably improve the prediction accuracy, and the model can achieve high throughput with little performance loss and with almost zero overhead.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Analyzing the Effect of Community Norms on Gender Bias
No full textM.S.The literature on bias in NLP has chiefly focused on the extent to which an algorithm produces outputs that can be differentiated along demographic lines. This is universally framed as undesirable and generally assumed to manifest in similar ways across different models/datasets. NLP models are claimed to play an essential role in shaping this societal bias, but it is equally important to understand how societal norms shape this bias as bias in NLP models originates from either the training corpus or the word embeddings or the algorithm. This thesis aims to find if the manifestation of bias, specifically gender bias, is different across different communities with different norms. The hypothesis is that the exhibition of gender bias is in sync with community norms, and changes along with it. We study gender bias in three different online communities - r/RoastMe, r/ToastMe, and r/RateMe. r/RoastMe roasts people who upload an image whereas in r/ToastMe, we find comments complimenting or appreciating the users. r/RateMe tries to rate a person "objectively" based on the uploaded image. Given such contrasting norms, We use NLP models to check if the data from these subreddits indeed has bias by trying to predict the gender of the person for whom a comment is made. We then see if the biases reflected in the models are in sync with the norms of the three communities by comparing the coefficients obtained from the models. The biases are also compared and contrasted across gender and communities by ranking the words associated with each gender. The evaluations show that gender bias exhibited in different communities is indeed different and depends on the context and the norms of the community. On comparing the biases in r/RoastMe and word embeddings, we also see that some words are universally gendered whereas others are context-specific.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Predicting Adolescents' Alcohol Use from Peer Bullying and Sexual Harassment
No full textPh.D.This study was aimed at (1) identifying the number of adolescent victimization and perpetration subgroups based on peer bullying and sexual harassment items, (2) investigating whether those adolescent subgroups identified would predict later alcohol use and (3) whether the relationship between peer bullying/sexual harassment subgroups and alcohol use would differ across gender and/or varied age levels among 13-to 17-year-old U.S. adolescents. This study also examined whether individual, family, and peer factors would play roles in the relationship. To this end, this study used the data from an NIAAA-funded longitudinal study of Peer Victimization as a Pathway to Adolescent Substance Use (Livingston, 2013-2018, R01021169). A total of 800 participants at baseline were asked to complete a longitudinal online survey five times over a two-year period (once every six months). Adolescent participants were recruited for the study through Address Based Sampling (ABS) in a metropolitan county in the Northeastern United States. The age range of adolescent participants was 13 to 15 at baseline, with 57.4% (N=460) females. In terms of race, 81% are Caucasians, 11.5% African Americans, 6.6% Hispanic/Latino, 1.3% Asians, 0.6% Native Americans, and 4% multiracial group. Latent class analysis (LCA) with a distal outcome was used for analysis. This study used latent classes of peer bullying and sexual harassment as predictors of alcohol use, not as outcomes, by implementing the most up-to-date statistical approach, Bakk and Vermunt's (2016) weighting by classification error approach, applied in LCA. Results indicated that four latent classes of peer bullying and sexual harassment were identified via LCA: (1) Little or no involvement group (49%); (2) pure victims (28%); (3) bully-victims (14%); and (4) high involvement group (9%). There were significant differences in adolescents' alcohol use among the four latent classes identified. More specifically, compared to little or no involvement group, the other three classes used a significantly higher amount of alcohol. Gender did not moderate the relationship between classes of peer bullying/sexual harassment and alcohol use as a whole, but the results of specific gender interactions indicated that male adolescents used alcohol more than female peers within the bully-victim group. In terms of age interactions, age did not moderate the relationship between latent classes of peer bullying/sexual harassment and alcohol use. Among the covariates, peer alcohol use was strongly associated with adolescent increased alcohol use throughout the analysis, whereas age was associated with an increase in alcohol use only in some models. Policy implications regarding the prevention and intervention of peer bullying and sexual harassment were discussed briefly with regards to a need to make concerted efforts among parents, teachers, and school. Both strengths and limitations of the study along with future research were addressed in terms of methodological and conceptual aspects.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Rapid Estimate of Hurricane Wind, Rain and Storm Surge Under Changing Climate
No full textPh.D.Hurricane-related strong winds, torrential rainfall and devastating storm surge are responsible for significant economic losses and casualties in coastal areas. Mitigation of losses due to hurricane hazards has become an increasingly urgent and challenging problem in light of the changing climate and continued escalation of coastal population density. Accurate and efficient modeling of the hurricane wind, rain and storm surge under changing climate is critical to ensure the safety and reliability of structures subject to these hazards. To this end, both physics-based and/or data-driven reduced-order modeling methodologies are utilized for rapid estimate of hurricane wind, rain and storm surge hazards. More specifically, three types of models based on analytical, semi-empirical and knowledge-enhanced deep learning approaches are developed. The analytical model is derived from the physics-based momentum equations, the semi-empirical model is obtained by fitting the field measurement data, and the knowledge-enhanced deep learning model combines the data-driven machine learning capabilities with prior knowledge in terms of both physics-based equations and/or semi-empirical formulas. The developed hurricane hazard models are then integrated into an improved hurricane risk assessment framework to generate a large synthetic database of full-track storms from the genesis to dissipation stage under observed and projected climate conditions. Accordingly, the hurricane-induced hazard risks are efficiently evaluated at the desired locations.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Damage Mechanics of Graphene Nanoribbons (GNRs) Under Electric Current Induced Wind Forces
No full textPh.D.Graphene is single layer of carbon atoms that are covalently bonded via sp2 bonds. Since its discovery in 2004 by the famous “scotch tape method”, graphene has attracted lots of attention during the last decade due to its excellent mechanical, thermal and electrical properties. Graphene is promising to replace Silicon in the next generation semiconducting materials not only because of its excellent material properties, but also because of its planar geometry make it more convenient to be integrated into electronic devices during mass production using traditional top-down complementary metal oxide semiconductor (GMOS) process with little variant.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Ambient Energy Information Display: Designing to Enhance Awareness and Curiosity
No full textM.S.Ambient displays are defined as abstract and aesthetic displays portraying non-critical information on the periphery of a user’s attention. (Mankoff et al., 2003) This thesis focused on designing an ambient display for an ultra-efficient house in order to raise curiosity in terms of energy consumption and the relation between environmental parameters and the net energy usage of the house.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
The Evaluation of Organizational Climate Within an Anesthesia Practice and Its Implications for Certified Registered Nurse Anesthetist Recruitment and Retention
No full textUB SON, DNP Research ProjectThe process of recruiting and retaining Certified Registered Nurse Anesthetists (CRNAs)
can be difficult for various anesthesia practices in the United States. Ensuring positive practice
environments for CRNAs may be one solution to this problem. The purpose of this study was to
evaluate CRNA perception of organizational climate in their current place of employment and to
determine if this influences willingness to remain employed at that practice. Vroom’s theory of
work and motivation was selected as the theoretical framework. CRNAs currently practicing in
the state of New York were invited to participate in a quantitative, cross-sectional, online survey.
Members of the New York State Association of Nurse Anesthetists (NYSANA) were asked to
take part in the study. Demographic data were collected and CRNA perceptions of
organizational climate, job satisfaction, and intent to leave current place of employment were
measured by the CRNA Organizational Climate Questionnaire (CRNA-OCQ), the Misener NP
Job Satisfaction Scale (MNPJSS), and the Anticipated Turnover Scale (ATS). Descriptive
statistics were utilized to analyze demographic data, while Pearson’s r Correlation was used to
determine the relationship between organizational climate, job satisfaction, and turnover intent.
Differences in perceptions of organizational climate based on type of employment and anesthesia
care model were also investigated using a one-way ANOVA. There was a positive correlation
between CRNA-OCQ and MNPJSS scores. In addition, there was a negative correlation
between these two measures and ATS scores. CRNAs with a positive perception of their work
environment were less likely to want to leave their jobs. Anesthesia practices should explore
methods to improve the workplace for CRNAs to improve retention
Perceived Benefits of the Use and Risks of Nonuse of Protective Eyewear Compared to Other Personal Protective Equipment Among Anesthesia Providers in a Western New York Hospital Setting
No full textUB SON, DNP Research ProjectAnesthesia providers are at risk for contracting infectious diseases through unintended bodily fluid exposures. Multiple studies have demonstrated that the use of personal protective equipment (PPE) including gloves, gowns, masks, and protective eyewear vary considerably with suboptimal compliance among healthcare staff. The purpose of this Doctor of Nursing Practice (DNP) project was to examine the perceived benefits of the use and risks of non-use of protective eyewear as compared to other forms of PPE among anesthesia providers including Certified Registered Nurse Anesthetists, Anesthesiologists, and Anesthesia Residents. The Health Belief Model guided the project as the theoretical framework. Project objectives were to 1) identify the barriers and facilitators to intraoperative PPE use among anesthesia providers; 2) compare and contrast types of intraoperative PPE utilized by anesthesia providers; 3) examine accidental exposure history resulting from PPE non-use or suboptimal compliance among anesthesia providers; and 4) develop recommended guidelines for intraoperative PPE use for anesthesia providers. Convenience sampling and a survey with open-ended questions were utilized to collect data. Analysis through ANOVA compared and contrasted between types of PPE to determine deficits and correlation tests (Pearson and Chi-Square) determined significance of relationships when compared to variables (demographic and exposure history). Project findings guided the development of an in-service for anesthesia providers overviewing best practice recommendations for PPE use and steps to promote individual confidence to execute protective behaviors. University at Buffalo, Institutional Review Board approval was granted prior to project implementation