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Comparing fungal communities in Tsuga heterophylla seedling roots across nurse log decay stages and the forest floor
Get PDFNurse logs are fallen, decaying trees that have been shown to facilitate the survival, establishment, and growth of tree seedlings, therefore making vital contributions to forest regeneration. Plant-fungi interactions may play a role in influencing seedling survival across nurse log decay and the forest floor. We sought to examine how fungal communities in seedling roots change between nurse logs and forest floor as well as across nurse log decay stages. To study this, we collected western hemlock (Tsuga heterophylla) seedlings (5-10 cm) from nurse logs of each decay stage and the forest floor at three field sites on the Olympic Peninsula, WA. We then removed the root tips and sent them to Jonah Ventures lab for DNA extraction, PCR, and next generation sequencing. We preliminarily categorized fungal OTUs into ecological roles using the FunGuild database and literature search. Fungal community composition varied across substrates with forest floor composition being most similar to nurse log decay stage 3 and least similar to nurse log decay stage 1. No significant trend emerged across substrates for mycorrhizal and pathogenic OTUs, however saprotrophic OTUs increased in nurse logs of decay stages 1 and 2. Future analyses and further literature search may reveal a pattern in mycorrhizal and pathogenic OTUs, specifically when looking into T. heterophylla-specific symbionts and when incorporating distance to parent tree data. Overall, fungal communities change across nurse log decay and the forest floor, which could influence patterns of seedling abundance across these substrates
Does Faceted Ice Growth Follow a Characteristic Pattern
Get PDFUnder certain heat conditions, ice crystals can form differently from the snowflakes that generally grow. Instead of attaching on the boundaries of a plane of ice, under these conditions, new water molecules will permeate a quasi-liquid layer above the ice that causes them to attach closer to the center of the plane and build up from there. These ice formations are close to cylindrical with patterns of roughness on the sides and top at the micrometer scale. The growth can be modeled with a system of partial differential equations that is similar to a reaction diffusion system. This project tries to fit the roughness on the ice to a Turing Pattern, a common phenomenon in reaction diffusion systems. This was done first by finding existing Turing Pattern models and altering them to fit the ice model. Then the pattern was assumed and parameters were tested for how they influence the frequency of roughness
Megalithic Art in the Boyne Valley Passage Tombs
Get PDFThe purpose of this study is to quantify the locations of megalithic art within the main passage tombs at Knowth and Newgrange, in the Boyne Valley of Ireland, with the aim of better understanding meanings associated with the art as well as their social contexts. Of particular interest to this study was the identification and analysis of the location of “endogenously-derived arts” as a way to take into account the often overlooked role that altered states of consciousness (ASC) play in rituals throughout prehistory and history. Furthermore, this study places megalithic art at the forefront of its analysis in the context of the tomb’s function as a whole, rather than only analyzing the art or including it as a small piece of evidence. The resulting study identified the kerbstone as the main location for megalithic art, especially endogenous arts. This, in turn, provides evidence against the somewhat dominant belief that huge megalithic tombs were the result of a centralization of power as the Neolithic era progressed. Instead, this research supports the idea that the tombs’ role was primarily communal rather than serving the interests of a specific elite
Sensory-Based Interventions in Inpatient Mental Health
Get PDFThis systematic review aimed to answer the following question: What are effective sensory-based interventions that increase self-regulation skills and decrease maladaptive behaviors for adults in inpatient mental health settings? Researchers collaborated with local occupational therapy practitioner, Katrina LaRossa, from a Multicare Behavioral Health Hospital in Western Washington. Sixteen articles met the inclusion criteria and were rigorously reviewed and categorized by the researchers. Evidence from the literature indicates that sensory-based interventions can be an inexpensive and effective method to reduce agitation and maladaptive behaviors.
The knowledge translation project involved development of a guide that provided implementation strategies for the sensory-based interventions identified in the research process. The implementation guide was organized in a binder, and included the implementation methods, outcomes, credibility, cost breakdown, and special considerations for each sensory-based intervention, as well as the article itself. To monitor the impact of our knowledge translation project, a survey was conducted to measure the clinician’s perception and satisfaction with the implementation guide. Researchers recommend that future research focuses on sensory-based interventions for adults in inpatient mental health and that studies take into account restrictions that are typical for inpatient mental health
What Motivates Highly Active Mothers? A Self-Determination Theory Perspective
Get PDFWhat Motivates Highly Active Mothers? A Self-Determination Theory Perspective
Natalie McDaniel, SPT; Stephane Robert, SPT
Mentor: Danny McMillian, PT, DSc, OCS
Background: Physical inactivity is a major global health concern linked to high mortality rates. Extensive research demonstrates the role of physical activity (PA) in enhancing overall well-being, longevity, and disease prevention. Mothers living with children face significant challenges in pursuing PA.
Purpose: This qualitative research uses Self-Determination Theory (SDT) to investigate experiences and beliefs influencing PA motivation and satisfaction in highly active mothers.
Methods: (N=5). Participants completed the Motives for Physical Activities Measure - Revised (MPAM-R) and the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS) and participated in semi-structured interviews which were subsequently coded.
Results: Based on coding frequency from the interviews, participants collectively expressed greater psychological satisfaction (32) than frustration (19). Coding further reveals the following motivational themes in order of magnitude: Competence (80), Fitness (49), Autonomy (46), Social/Relatedness (45), Interest (40), and Appearance (18). MPAM-R scores indicated high satisfaction across Fitness (6.36), Interest (6.17), Competence (5.97), Appearance (3.7), and Social (3.52). BPNSFS outcomes consistently favored psychological satisfaction over frustration in Autonomy (r=0.57), Relatedness (r=0.634), and Competence (r=0.63).
Conclusion: Motivational factors influencing PA were most associated with competence, suggesting the importance in mastery of PA. The frequent expressions of psychological frustrations demonstrate this demographic’s ability and motivation to overcome these obstacles and maintain high levels of PA. Clinicians working with this population should be equipped to assist with inevitable challenges and provide mothers with the resources to overcome them
An Expansion on Marginalized Functioning: A Necessary Condition for Disability
No full textAn Expansion on Marginalized Functioning: A Necessary Condition for Disability
Eleanor Jeffers (Whitworth University)
Comments by Lauren Rice (Puget Sound)
Chair: Zoe Brinne
Political Bias in Large Language Models
Get PDFRecent research has found that large language models consistently capture and replicate undesirable societal biases relating to race, religion, and gender. However, political bias is not well explored. This study investigates the political bias present in the state-of-the-art large language model GPT-3. To investigate political bias, I apply Natural Language Processing techniques to develop a political sentiment analysis model. Using this model, I analyze the ideological bias present in political essays written by GPT-3, finding that GPT-3 has a moderate left-leaning bias and tends to replicate the ideological bias of prompt text
