Open Research Oklahoma (Oklahoma State Univ.)
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Community and stakeholder engagement in the delivery of post-abortion care services in humanitarian emergencies in malawi, southern region
No full textThe primary focus of this qualitative study was to explore and understand various challenges stakeholders experience in providing post-abortion care services for communities in humanitarian emergencies in Malawi, in the southern region. The study had 10 individuals participate in semi-structured interviews. The primary topics addressed with participants were: 1) factors impacting Post-Abortion Care (PAC) provision within the context of humanitarian emergencies 2) strategies organizations employed to address the challenges that arise when providing PAC services in humanitarian emergencies, 3) level of communication with other local and international organizations involved in the provision of PAC services in humanitarian emergencies, 4) perceptions of communities inputs incorporated in decision-making processes. This inquiry established 6 main findings: 1) empowerment and support initiatives, 2) healthcare access, quality, and resource support, 3) cultural effects on access to services, 4) capacity building and organizational support, 5) communication disparities among partners, 6) Participation in the decision-making process. The findings indicate that stakeholders can improve the provision of important health services, such as PAC, by utilizing their combined knowledge and resources to create interventions that are both comprehensive and adaptable through collaborative efforts
Investigating children as gatekeepers to tactical athlete nutrition
No full textBackground: Chronic diseases occur at higher rates among tactical athletes (TAs) than US averages. Chronic disease prevalence continues to rise despite existing nutrition interventions. Children have emerged as a possible influence on TA nutrition. Civilian studies reveal a bidirectional relationship such that parents and children influence one another’s eating habits. Because TAs have a rigorous schedule, it is suspected that they cater to children’s food preferences as compensation. Thus, the purpose was to determine whether children act as gatekeepers to TA eating habits and nutrition.Methods: This cross-sectional study included an online survey completed by a convenience sample of TAs and significant others. Survey questions included demographics, employment status, relationship and child information, family dynamics, type of TA, perceived nutrition knowledge and attitudes, family eating patterns and child influence, and dietary quality (mini-EAT score) of themselves and their child. Statistical analyses included descriptive statistics, t-test, ANOVA, and Pearson correlations.Results: Total healthy eating readiness score was moderately and negatively associated with number of driving children (r=-0.34). TA mini-EAT total score was moderately and negatively associated with number of children (r=-0.38), perceived level of limited variety in food because of the child (r=-0.33), and perceived limit of healthy food consumption because of child (r=-0.46). TA mini-EAT total score was moderately and positively associated with child mini-EAT total score (r=0.50). Child total mini-EAT average score was 30.8/72±5.9 per significant other and 29.6±7.1 per TA. TA total mini-EAT average score was 32.0±6.6.Conclusions: Children influence TA eating habits and dietary quality. Thus, practitioners should not ignore the family and consider improving children’s nutrition as a means of improving TA eating habits and dietary quality
Land appreciation
No full textThe Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311
Art of growing older
No full textThe Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311
Debris management framework for post-disaster response
No full textIn the aftermath of disasters, efficient debris management is critical to restoring community functions and ensuring public safety. This research develops a comprehensive framework combining the Debris Vulnerability Index (DVI) and the Debris Removal Routing Optimization (DeRRO) model to enhance post-disaster response. The DVI, based on a multi-dimensional approach integrating physical, infrastructural, and environmental factors, enables prioritization of debris sites using GIS-based heatmaps. By visualizing vulnerability through heatmapping, decision-makers can quickly identify high-priority zones, thereby directing resources to areas that pose the greatest risk to community recovery and resilience. This prioritization is expected to reduce secondary damage, optimize resource allocation, and expedite the overall recovery process. The DeRRO model employs a nontraditional Particle Swarm Optimization (PSO) approach to optimize debris removal routes. This model classifies debris types, estimates the required number of trucks, and dynamically adjusts routes in real-time based on evolving conditions in the disaster field. By incorporating real-time GIS feedback, the DeRRO framework minimizes travel distances and response times, improving operational efficiency by approximately 25% compared to traditional methods. This efficiency gain translates to reduced operational costs and faster community restoration, as well as a more adaptive approach to routing that can scale to various disaster scenarios. Through validation and case studies, this research demonstrates the practical applications of the DVI and DeRRO models in diverse disaster settings. The case studies highlight the models’ adaptability and robustness, offering a replicable, data-driven framework that can be applied across multiple disaster types and locations. The combined outcomes of these models not only enhance immediate disaster response efforts but also contribute to the long-term resilience of communities by establishing systematic procedures for prioritization and route optimization. This framework ultimately provides a valuable tool for policymakers and disaster management professionals, aiming to reduce recovery time, improve resource use, and create a foundation for more resilient disaster response strategies. By advancing data-driven decision-making, this research seeks to improve the safety and recovery of affected communities, setting a new standard in post-disaster debris managemen
4-H crafts: Metal hammering, weaving
No full textThe Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311
Minerals for horses: Calcium and phosphorus
No full textThe Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311
Weakness in semi-empirical broadband noise prediction: Investigation with RANS CFD for small scale moderate camber airfoil propellers
No full textThe understanding and characterization of aerial systems acoustic properties for noise reduction, once afterthought save for specialized fields or situations, in recent decades has become of critical importance as a design criterion to capture completely. Exploding unmanned aerial system (UAS) usage is leading to increased importance due to growing complaints about aircraft noise from populations due to increased UAS encroachment into the public airspace. Aerial system noise can be thought of as tonal or broadband in character with tonal mechanism being well understood and predicted. Broadband mechanisms are much more difficult to predict, requiring either computationally intensive methods to capture or using simplified lower fidelity models that are limited in applicability and/or accuracy. This work explores the applicability of the lower fidelity broadband airfoil self-noise prediction method of Brooks, Pope, and Marcolini to the analysis of moderate camber propellers operating in a lower Reynolds number regime. Experimental flow and boundary layer (BL) data was collected for a series of computational fluid dynamics (CFD) studies examining differing airfoils over a range of Reynolds numbers and angles of attack. Comparisons were conducted examining the results for Brooks, Pope, and Marcolini BL modelling against those from CFD. Also compared were Brooks, Pope, and Marcolini acoustic predictions using modelled BL data against those using CFD BL data. To investigate methods to address weaknesses found in the model, proof of concept CFD investigations using LES turbulence modeling to provide unsteady loading data for prediction of self-noise using Ffowcs-Williams Hawkings (FW-H) were conducted. Preliminary findings for the NACA 1412 for average flow condition CFD TE BL data and modeled TE BL data driven Brook’s self-noise predictions against FW-H unsteady loading predictions are presented. Finally, as an investigation of a Reynolds Averaged Navier Stokes trailing edge BL correction method, noise predictions for an OSU custom 18 x 18 3 blade propeller were investigated using a blade element method implementation of Brooks, Pope, and Marcolini. The results of these studies showed weakness in the method when predicting cambered airfoil self-noise, demonstrating weakness in BL modelling for both Reynolds number and angle of attack. Further it is shown that accurate BL capture is important to both frequency content and OASPL for model total self-noise and individual mechanism noise predictions. Suggestions are provided for further work to refine the identification of weaknesses in the model and develop improved prediction models and methodology
Study in the use of virtual reality to increase self-efficacy and training performance in beginning professional pilot students at a university flight school
No full textThe purpose of this study was to gain deeper understanding of student perspectives when using Virtual Reality (VR) to enhance knowledge acquisition in the early stages of flight training. Flight training costs are rising quickly, and the advent of Personal Computer (PC) based VR shows potential to help new flight students strengthen their knowledge while learning skills in an immersive environment that will make future flight training more efficient using a cost-effective platform. The review of the literature shows a consensus that using VR simulation does provide benefits to the users, but often the focus is on the efficiency of the process with less emphasis on the thoughts and feelings of users. This qualitative, phenomenological study answered four research questions using four one-on-one guided VR simulator sessions plus pre-study and post-study interviews with eight participants. Video recordings of these sessions and interviews were analyzed to determine if there are trends in overall perceptions related to VR use, and to discover if using the VR technology has any noticeable effects on participants’ self-efficacy and willingness to encourage others to use the VR technology. The findings show that all four research questions were answered affirmatively, and that self-efficacy was increased after completing the VR training sessions. Additional insight resulting from data analysis indicates a connection between previous experience and the amount of increase in self-efficacy, and perceived importance of structured and guided VR training sessions. This study fills a gap in the available literature and contributes to overall knowledge about student perceptions of using VR flight simulation to assist in the early stages of flight training
Investigation of multimodal aspect based sentiment analysis using a Crossmodal Model
No full textMultimodal aspect-based sentiment analysis, the task of identifying a target aspect and obtaining its sentiment, has begun to gain more and more attention in the natural language processing community. Although the field started with simply focusing on textual data, there are many datasets such as Twitter 2015 and 2017 that require models to apply both textual and visual focuses. In this work, the model we propose is the Cross Modal Model (CMM). This model contains a BERT model and a CNN, which extract textual and visual features from the dataset, then obtaining the attention on features, and finally concatenating the features together to obtain the sentiment prediction. We saw significant performance gains with this model that achieve breakthrough results on the Twitter 2015 and Twitter 2017 datasets. These results demonstrate how useful our method could be applied to other multimodal datasets and potentially other multimodal problems