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Circadian Rhythms and Pollination Timing: Impact on Gene Expression in Apple Blossoms
No full textPollination is an important process for the reproduction of flowering plants, yet the molecular interactions between plants and their pollinators remain inadequately understood. This gap limits our knowledge of flower development post-pollination and its relationship with environmental factors, such as time of day. While most studies focus on behavioral ecology of pollination, the influence of circadian rhythms on floral transcriptional responses is underexplored. To study the influence of circadian rhythms on floral response to pollinator activity, we chose apple flowers (Malus domestica) from the University of Arkansas orchard as a model system since their blossoms attract a variety of insects during day and night. We collected recently pollinated flowers at two time points (1 hour and 12 hours post-pollination) around mid-morning and at night for six days in spring 2022. We compared the gene expression profiles of these pollinated flowers to unpollinated flowers of the same age, apple variety, and collection time. In addition, we also assessed whether the floral transcriptional response to being pollinated at night differed from that of being pollinated during the day. Our findings reveal that gene expression patterns shift over time post-pollination, with petals showing an early response to pollination before gene activity transitions to the ovary. Furthermore, stamen tissue consistently exhibited lower differential gene expression levels post-pollination, suggesting a reduced role in short-time post-pollination responses. Distinct RNA profiles emerged between day and night-pollinated flowers, highlighting the impact of circadian rhythms on floral gene regulation. These results highlighted the importance of considering pollination timing in studies of floral gene expression and broader plant-pollinator interactions
Testing of a Novel Piezoelectric Material and Its Implementation in a Non-Invasive Contractile Force Measuring Heart-on-Chip Device
No full textHeart on chip devices are an emerging technology that is used to mimic the physical, cellular, and signaling environment of the heart on a benchtop model. This technology allows researchers to study heart diseases and new drug therapeutic strategies with more physiological relevance to the human heart than animal models and simple cell culture systems. These heart on chip devices are incredibly useful in directly measuring the contractility of beating cardiomyocytes. However, these devices are either lacking the ability to easily and continuously measure the contractility of cardiomyocytes seeded onto their platform or have relied on stiff materials to build sensors on their device, preventing the cardiomyocytes seeded on these devices to move and flex dynamically as they would in the human body. This research has produced a novel piezoelectric material that allows cardiomyocytes to contract on a flexible material while being able to continuously measure the contractility of the cardiomyocytes. This material was studied for its electrical sensitivity, material strength, electrical fatigue, and biocompatibility. It was found that the material was not significantly different when comparing biocompatibility and material strength to other established soft cell culture substrates but was significantly improved when studying electrical sensitivity and electrical fatigue resistance of the material. These results were used to design a heart on chip device which allows cardiomyocyte cells to contract on a flexible cantilever while allowing for continuous, non-invasive contractility measurements. Studies were done to determine ideal manufacturing and processing parameters for the novel piezoelectric material. Further studies will expand on determining the ideal electrode design for collecting the non-invasive contractility measurement and using this heart on chip device, also referred to as the co-cultured cardiomyocytes on chip device (coco chip) to study disease models and new pharmaceutical drugs
Be Curious, Not Judgmental: Neurodiversity in Legal Education
Get PDFThis Article takes the position that the curiosity associated with legal education is limited to those who are neurotypical. For students who are neurodivergent, law school is a place of judgment, not curiosity. The number of neurodiverse law students is increasing, yet they are not sufficiently supported in law school. This Article will seek to show how the current structures of legal education, although fundamentally sound, have become overly rigid. Instead of providing students with intellectual foundations of legal doctrine that prepare them for the challenges of practicing law, the existing status quo stifles those goals. By limiting our practices to what we currently know and what we are comfortable doing, we limit our potential for excellence. In Part I, I introduce what neurodiversity means, especially for law students, the problems they face, how law schools fall short, and why law schools should care about this. In Part II, I explain the legal mandates designed to remove barriers and the roadblocks legal education and law schools erect. In Part III, I lay out concrete solutions and strategies for engaging our curiosity rather than our judgment
Rice Cultivar ‘Taurus’
Get PDFA rice cultivar designated Taurus is disclosed herein. The present invention provides seeds, plants, and plant parts derived from rice cultivar Taurus. Further, it provides methods for producing a rice plant by crossing Taurus with itself or another rice variety. The invention also encompasses any rice seeds, plants, and plant parts produced by the methods disclosed herein, including those in which additional traits have been transferred into Taurus through the introduction of a transgene or by breeding Taurus with another rice cultivar
The Documented Relationship between Sexual Health Knowledge, Attitudes, and Impact on Sex Behaviors for Students in the United States
Get PDFPurpose: To determine whether there is a documented relationship between sexual health knowledge, attitudes, and sex behaviors in students in the US.
Methods: This study conducted an expanded literature review. Multiple databases were utilized including EBSCO host academic complete search, CINAHL, and Google Scholar. Searches included the following phrases: “sexual health education”, “united states”, “sexual health knowledge”, “sex behavior”, “risk seeking behavior”, and “sex attitudes or perceptions or opinions.” Studies were included based on relevance to topic, geographical location, age group, and recency.
Result: 40 peer-reviewed articles were reviewed. The majority of students failed in knowledge based assessments on sexual health. Students had the least amount of understanding related to contraceptives, anatomy, consent, sexually transmitted infections, and condom use. There is an inverse relationship between a higher understanding of sexual health with more positive sex behaviors. Evidence on whether sexual health attitudes relate to sexual health knowledge is conflicting. Literature suggests there is a greater impact on attitude in relation to source and timing of teaching rather than amount of knowledge.
Conclusion: These results support the need for an increase in sexual health knowledge in students, further research on the development of attitudes toward sexual health, and promoting positive sex behaviors
Arkansas Rice Research Studies 2024
Get PDFResearch reports contained in the publication may represent preliminary or only a single year of results; therefore, these results should not be read as a basis for long-term recommendations.
Several research reports in this publication will appear in other University of Arkansas System Division of Agriculture’s Arkansas Agricultural Experiment Station publications. This duplication is the result of the overlap in research coverage between disciplines and our effort to inform Arkansas rice producers of all the research being conducted with funds from the rice check-off program. This publication also contains research funded by industry, federal, and state agencies.
Use of products and trade names in any of the research reports does not constitute a guarantee or warranty of the products named and does not signify that these products are approved to the exclusion of comparable products
Usage of Natural Language Processing and Deep-Learning Techniques on Thematic Apperception Tests to Predict Big Five Personality Traits
Get PDFThe usage of personality as a method of behavioral prediction and outcomes of success has grown considerably over the last few decades. This project explores predicting user personality profiles via the Big Five personality index through the integration of advanced natural language processing techniques as well as neural networks. Using a dataset provided by Dr. James W. Pennebaker, participants analyze an image—formally referred to as a thematic apperception test—and write a thorough paragraph describing the details. This free-form text, along with their personality test results, is captured in a structured dataset. Many deep-learning and machine learning models have been used in the field of psycholinguistics before, but the usage of the Big Five personality model has been relatively scarce, despite it having the highest validity and reliability amongst modern personality indexes. The proposed model extracts personality using word embeddings while incorporating sentiment concentration, typo density, and other linguistic features to capture meaningful insights from participant responses. These features enable the neural network to identify complex linguistic patterns linked to personality traits, presenting a novel approach that leverages many advancements made in the fields of language analysis, psycholinguistics, and modern applications of machine learning. The model’s performance is evaluated by measuring the Mean Squared Error (MSE) between the predicted Big Five traits and the actual traits obtained from the user’s given quiz results. While there is improvement to be made in expanding the scope and accuracy of the model, this project contributes toward advancing accurate computational approaches to personality assessment in the field of computer science
Design, Simulation, and Testing of Planar Transformer for Smart Green Power Node (SGPN) Isolation using Ansys
Get PDFThe goal of this project was to design and simulate a small, high-frequency, planar, ferrite-core transformer which can be used in a variety of applications, the most relevant of which is photovoltaic (PV) converter systems, which often require bulky transformers to function properly. The current research involved several processes: (1) Understanding and designing a tutorial for the use of Ansys software to aid in the efficient development and modeling of transformers, (2) designing and simulating a planar transformer in Ansys to be used in a solar converter, specifically the Smart Green Power Node (SGPN), and (3) testing the planar transformer using a series of tests in a controlled laboratory environment. The importance of this work lies in its future implications: its proper implementation could allow for far more sustainable and cost-effective solar energy solutions for everyone, relying on small but effective magnetics rather than the current bulky transformer options. The result of this research is an optimized planar transformer designed using Ansys Electronics Desktop, complete with its simulation results which accurately predict the core losses of the transformer throughout its use, as supported by data collected through its implementation and testing