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Fueling the mind, feeding the world: Decision making ��� Identifying and analyzing problems (DM01)
Get PDFFall 2024 version. Created at Texas A&M University as part of a grant sponsored by the USDA.
For additional information, visit the Texas A&M University Science Communications Lab at https://scicomm.tamu.edu/.This packet contains instructional materials and online modules prepared for Fueling the mind, feeding the world: Decision making ��� Identifying and analyzing problems (DM01). It includes curriculum, PowerPoint slides, activities, handouts, grading considerations, and notes for instructors. These materials were created as part of the USDA Grant entitled "Fueling the Mind, Feeding the World: Enhancing Communication and Decision-Making Skills of Secondary Agricultural Education Students."
MODULE OVERVIEW: Decisions are made daily and affect every facet of life. Although in some situations this activity is simple and straight forward, other situations are more complex, and consequences of a poor decision can be devastating. The decision-making process can be more effective by first critically examining the problem���identifying and analyzing the problem are the key first steps in making decisions. This content focuses on four major steps to begin decision making (understand the issue, identify and analyze the problem, cause and effect analysis, and the five whys) and offers a ���deep dive mini lesson��� on structured and unstructured decision-making.Secondary Education, Two-Year Postsecondary Education, and Agriculture in the K-12 Classroom (SPECA) Challenge Grants Program no. 2019-38414-30265 and Hatch Project No. TEX09825 from the USDA National Institute of Food and Agriculture
The Metabolic Differences in Different Temperament Categories of Angus and Brahman Steers
Get PDFMeat products are priced based primarily on quality. Therefore, it is important in the beef industry for producers to be able to ensure that they are raising the highest quality cattle possible. There are three major temperaments associated with cattle - calm, intermediate, and temperamental - and research has shown that temperamental cattle are more likely to produce dark cutting or borderline dark cutting beef resulting in a lower quality product. Dark cutting occurs when an animal has experienced long term stress 24 to 48 hours prior to harvest that results in it having less glycogen available for use in the conversion of muscle to meat. My research aimed to identify specific metabolites and their prominence in the blood serum of cattle that are associated with the three different cattle temperament groups. The goal was to find metabolites that could be associated with a specific temperament group to eventually indicate how certain living animals will perform post-harvest. Cattle that are identified as more likely to be at risk of producing a lower quality product can be catered to reach a higher value product. To research this, blood serum samples from Angus and Brahman steers utilized in a temperament study were extracted and ran through a high performance liquid chromatography quadrupole time-of-flight (HPLC-qTOF) machine to identify and quantify the metabolic compounds present. The results of the Angus and Brahman steers could not be compared to each other due to unforeseen events that prevented them from being ran identically, and outside factors aside from breed. The data for each breed was interpreted independently. The preliminary results from the HPLC data suggested that specific metabolites existed in the Angus heifer samples, and the Brahman steer samples, independently, that were significant and varied in abundance based on the temperament treatment. These identified metabolites could potentially be indicators of cattle temperament and could be utilized in the industry to identify high quality risk temperamental cattle prior to harvest
Effect of Alpha-Actin Mutations on Cell-Matrix Adhesions in Vascular Smooth Muscle Cells
Get PDFThoracic aortic aneurysm is commonly found in patients with ACTA2 mutations which encodes for smooth muscle ��-actin (SM��-actin), the predominant contractile protein in vascular smooth muscle (VSM) cells. These mutations are associated with impaired VSM cell function in the aorta. This study investigates the relationship between cell adhesion and actin architecture in VSM cells isolated from aorta of mice presenting the Acta2R149C/+ mutation and wild-type controls plated on fibronectin extracellular matrix (ECM) protein. To investigate changes in integrin recruitment at cell matrix adhesions, cells were immunofluorescently labeled for integrins ��5 and ��1 and further imaged by total internal reflection (TIRF) microscopy. Also, cytoskeletal architecture was determined from confocal imaging of the same cells labelled for SM��-actin and smooth muscle ��-actin (SM��-actin). Collected data shows that both integrin ��5 and ��1 recruitment at cell-matrix adhesions are decreased in mutant Acta2R149C/+ VSM cells when compared to wild-type VSM cells. Quantification of protein fluorescence measurements of VSM cells from Acta2R149C/+ mice showed a downregulation in SM��-actin that was compensated by an upregulation of SM��-actin in comparison to wild-type cells. These results suggest that the downregulation of SM��-actin leads to reduced VSM cell contractility, while the upregulation in SM��-actin may lead to increased VSM cell stiffness. In addition, decreased ��5 and ��1 integrin recruitment at cell-matrix adhesions further reduces the ability of mutant cells to anchor within the ECM. Collectively, the results suggest that mutant ActaR149C/+ VSM cells present reduced contractility and interaction with the ECM, which are potential causative factors of thoracic aortic aneurysm
Enhancing Education Through Thoughtful Integration of Large Language Models in Assigned Work
Get PDFUndergraduate ResearchIn a world where technology is evolving rapidly, it is essential to note its significant intrusion into the field of education. Technology has made vast amounts of information accessible to students, making them over-reliant on technology and less reliant on nurturing their knowledge and imagination. While limiting technology's usage is impossible to stop, learning how to incorporate it efficiently in the educational system is essential. Integrating machine learning (ML) and artificial intelligence (AI) in education is a significant shift in educational methodologies. This transformation offers the possibility to change learning approaches while presenting challenges in the ethical field. This research paper explores the impact of machine learning (ML) and artificial intelligence (AI), particularly large language models like Chat GPT, on education in our classrooms. This topic is essential because it signifies a change in the methods that educators and students use to engage in a course, transforming the learning outcomes while upholding ethical principles. The application of ML and AI in education has attracted increasing attention, but the long-term effects of these technologies on learning achievements require further investigation. Therefore, we aim to find an approach that allows the integration of ML and AI, specifically Chat GPT, while maintaining high expectations in our classrooms. While tools like Chat GPT hold transforming educational potentials, their integration must be navigated thoughtfully, balancing technological advancements with concept learning and acquisition. In this paper, we utilize quantitative analysis of educational outcomes and observational research to understand the impact of LLM on Education. We will observe firsthand how these technologies are integrated into the classroom and how they affect teaching and learning dynamics
Greycloud Services [Adzine]
No full textNot dated.Catalog of Greycloud Services, a slash and het fanzine publisher based in the UK that published zines from the late 1970s to the mid 2000s
