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Ion Acceleration Inside Foreshock Transients
Full text linkRecent observations upstream of Earth's bow shock have revealed that foreshock transients can not only accelerate solar wind ions by reflection at their upstream boundaries but may also accelerate ions inside them. Evidence for the latter comes from comparisons of ion spectra inside and outside the cores, and from evidence of leakage of suprathermal ions from the cores. However, definite evidence for, and the physics of, ion acceleration in the foreshock transients are still open questions. Using case studies of foreshock transients from Time History of Events and Macroscale Interactions during Substorms observations, we reveal an ion acceleration mechanism in foreshock transients that is applicable to similar to 25% of the transients. The ion energy flux is enhanced between several keV to tens of keV in the cores. We show that these energetic ions are reflected at the earthward moving boundary of foreshock transients, are accelerated through partial gyration along the convection electric field, and can leak out both upstream and downstream of the foreshock transients. Using ions moving self-consistently with a generic 3-D global hybrid simulation of a foreshock transient, we confirm this physical picture of ion acceleration and leakage. These accelerated ions could be further accelerated at the local bow shock and repopulate the foreshock, increasing the efficacy of solar wind-magnetosphere interactions.Publishe
Data for: Cyanobacteria and aquatic ecosystem dynamics across 28,000 years of environmental changes in subtropical North America
No full textEcological pressures on aquatic ecosystems have increased over recent centuries due to human activities and climate change. However, contextualizing ecosystem deterioration is often challenging due to limited knowledge of environmental changes over millennial timescales. Subtropical Carolina bays in North Carolina, USA, have remained unglaciated, preserving paleolimnological records that extend back to the last glacial period. Here, we analyzed a sediment core from the ecologically rich Lake Waccamaw spanning more than 28,000 years for aquatic proxies of nutrients, photosynthetic pigments, cyanotoxins, carbon isotopes, and terrestrial proxies of pollen and charcoal. The study explored paleolimnological changes in the aquatic environment connected to land changes and climate during the late Quaternary in the southeastern Atlantic Coastal Plain. Results reveal that while current levels of colonial cyanobacteria are high, past levels of cyanobacteria, other primary producers, and cyanotoxins were higher under natural climate variability. Abrupt ecosystem responses to increasing trophic conditions during Interstadial 3 (27.8-26.4 cal ka BP) and the early Holocene (11.4-7 cal ka BP) were marked by increases in primary producer abundance, deciduous vegetation expansion, and fire activity. Cyanobacteria remained dominant throughout the record, with colonial forms prevailing during the Holocene. Increases in pigment concentrations aligned with Quercus and were primarily driven by hydroclimatic variability and nutrient stoichiometry. Transitions between Pinus and Quercus pollen matched stadials and interstadials in the δ18Ο record from the North Greenland Ice Core Project (NGRIP). This study highlights the value of multi-proxy millennial-scale paleolimnological records for understanding aquatic ecosystem responses to climate conditions during the late Pleistocene.PublishedYe
Dataset: Captivity negatively affects production of red carotenoid pigments in Cardinalis cardinalis (Northern Cardinals)
No full textCarotenoid-based coloration is a well-documented example of a condition-dependent trait, but much of the evidence supporting condition dependence of red carotenoid coloration comes from species that color their feathers primarily with 3-hydroxyechinenone, a red carotenoid produced from yellow dietary carotenoids via an unknown pathway. The condition dependence of red plumage in species that use the more common CYP2J19 and BDH1L enzymes to modify dietary yellow carotenoids into red ketocarotenoids is less well studied. We tested the hypothesis that captivity would negatively affect production of red pigments by male Cardinalis cardinalis (Northern Cardinals), a songbird with extensive red coloration produced via the CYP2J19/BDH1L pathway. We confined a group of wild-caught male cardinals in cages during molt, using captivity as a physiological challenge, and compared them to free-living cardinals. We provided captive birds with abundant zeaxanthin and lutein, the dietary yellow pigments that cardinals enzymatically convert into the red ketocarotenoids astaxanthin and alpha-doradexanthin, to ensure that insufficient carotenoid access would not limit production of red pigments. During molt, we measured concentrations of carotenoid pigments in the plasma and growing feather follicles of both captive and free-living cardinals. Compared to free-living cardinals, captive birds had significantly lower relative concentrations of red carotenoids in both follicles and plasma. The observation that, compared to free-living cardinals, captive male cardinals showed reduced production of red carotenoids with lower quantities in feather follicles supports the hypothesis that red coloration produced via the CYP2J19/BDH1L pathway is a condition-dependent trait.AcceptedYe
Engineering the Emotional Subjective: A Deterministic Protocol for Affective Quantization Strategy for Vectorized Semantic Alignment in Generative Artificial Intelligence
Full text linkThis study addresses the core mandate of the human-AI collaboration by positioning AECL as a foundational domain for human systems engineering (HSE). We examine how AI is altering technological landscapes and reshaping human creativity, communication, and social structures. We argue that the integrity of this convergence depends on our interaction with machine intelligence: a move from passive generation to active verification within the human-in-the-loop protocol (Nardi, 1998). By replacing probabilistic guesswork with deterministic, client-side protocol, we demonstrate how engineering architectures can preserve humanities-based inquiry. This ensures that the reshaping of our social and creative worlds remains anchored in authentic human truth rather than algorithmic approximation.PublishedYe
Approaches Towards Revising Instrumentation-Based Reliability Coefficients
Full text linkThis study addresses negative Cronbach's alpha reliability coefficients observed in two constructs of a newly developed questionnaire assessing agricultural educators' adoption of artificial intelligence. A field test with ten participants revealed negative reliability in the "perceived benefits and drawbacks" (α = -.01) and "access and infrastructure" (α = -.56) constructs, indicating potential multidimensionality and reverse-coded items. Through detailed inter-item correlation matrix analysis, specific statement inconsistencies were identified. The study emphasizes the importance of transparency in reporting such irregularities to improve instrumentation. It highlights the need for careful consideration of item phrasing, reverse coding, and construct unidimensionality in early-stage instrument development, advocating for open discussion of methodological challenges and subsequent corrective actions. This research contributes to establishing guidelines for reporting and addressing instrumentation errors in social science research
Resources and Approaches for Integrating High- Leverage Teaching Practices: A Content Analysis
Full text linkImplementing high-leverage teaching practices (HLTPs) for language learning can
help ensure teachers create and deliver a high-quality curriculum, especially when
working with Novice learners who require more scaffolded instruction. This study aimed
to fill a gap by identifying print resources and approaches available to support world
language teachers’ integration of HLTPs into instructional design for Novice learners in
middle and high school classrooms (grades 6-12). In the Fall of 2022, various resources
were analyzed according to their use in assisting teachers with integrating HLTPs, state
standards, and current second language acquisition (SLA) research into instructional
design. These resources included several ACTFL publications, select world language
methods textbooks, and documents from departments of education across 13 states in
the Southern Conference on Language Teaching (SCOLT) region.
The analysis found that teachers in this Southeastern region have access to numerous
resources for implementing the HLTP of backward design, including proficiency goals
for each level and state standards that are aligned with the World-Readiness Standards
for Language Learning (National Standards Collaborative Board, 2015). However,
comprehensive instructional approaches or models to create proficiency-based,
contextualized curricula integrating the other nine HLTPs were limited. The findings
highlight a lack of adequate guidance and resources for streamlined instructional
design to assist teachers in integrating HLTPs when working with Novice language
learners in grades 6-12, particularly after proficiency and communicative goals have
been established.PublishedYe
Alabama Livestock Research Report 2024
No full textThe livestock industry continues to be a foundation of the state’s agricultural economy, supporting communities, driving innovation, and providing high-quality animal protein for a growing population. Cattle are produced in every county and cattle production represents a 77.3 billion and 273,271 jobs, which accounts for 10% of Alabama’s workforce.
As global demand for high-quality animal protein continues to rise, so do the challenges facing our producers. Innovative, targeted research is needed to ensure the long-term efficiency and resilience of food animal production systems. The Department of Animal Sciences at Auburn University remains committed to meeting these challenges. Our faculty, staff, and students continue to develop collaborative, multidisciplinary research and extension programs that support producers and consumers. They are engaged in cutting-edge work that spans nutrition, genetics, reproduction, meat science, animal health, and beyond. We are committed to developing tools and knowledge that not only improve production efficiency but also strengthen the long-term sustainability of Alabama’s livestock systems.
It is with great excitement that we introduce the third edition of the Alabama Livestock Research Report. This publication continues our goal of sharing impactful research and outreach conducted by our department, on campus and through our affiliated experiment stations. Inside these pages, you will find highlights from ongoing projects, updates from the field, and insights into the ways we are working alongside producers, policymakers, and industry stakeholders to shape the future of animal agriculture in Alabama.
We are proud to share this report with you and grateful for the support of our funding partners and stakeholders who make this work possible. Most of all, we thank the faculty, staff, and students whose efforts and curiosity drive the progress you will read about here.
We invite you to engage with this work, ask questions, share ideas, and join us as we continue to serve Alabama’s livestock industry through research, education, and innovation. This is our work.
Sincerely,
Kim Mullenix, Ph.D.
Professor and Head
Department of Animal Sciences
210 Upchurch Hall, Auburn Univ, AL 36849
[email protected]
Evaluating the Economic Impact, Equity Implications, and Long-Term Prospects of AI-Powered Personalized Learning in Education by Mid-Century
No full textThis study examines the transformative impact of artificial intelligence (AI) on education, focusing on personalized and adaptive learning systems that tailor instruction to individual student needs. It traces the historical evolution of educational technology, highlighting milestones in AI integration such as adaptive feedback, content recommendation engines, and AI-driven assessment. The analysis addresses the economic returns of AI in education, considering both direct costs, including infrastructure, training, and maintenance, and potential benefits like improved learning outcomes, reduced dropout rates, and enhanced workforce readiness. Equity and ethical considerations are emphasized, particularly regarding access disparities, algorithmic bias, data privacy, and the evolving roles of educators and learners. The work explores broader societal implications, including shifts in teacher responsibilities, cultural and social capital dynamics, and opportunities for global collaboration. Future scenarios envision sustainable AI-driven educational models supported by adaptive policy frameworks that maximize economic and social returns while promoting inclusivity. The findings underscore the necessity of comprehensive strategies encompassing technological innovation, ethical governance, professional development, and equitable access to realize AI’s full potential in advancing educational quality, workforce preparedness, and long-term economic growth by mid-century.
Keywords: Artificial Intelligence in Education, Education Economics, Human Capital Development, Learning Outcomes, Cost-Benefit Analysis, Large Language Models, Equity in Education, Digital Learning Technologies, AI-Driven Instruction, Economic Impact of A
Artificial Intelligence and Large Language Models in Energy Systems and Climate Strategies: Economic Pathways to Cost-Effective Emissions Reduction and Sustainable Growth
No full textArtificial intelligence (AI) and large language models (LLMs) are revolutionizing energy systems and climate strategies by enhancing efficiency, enabling precise resource management, and supporting sustainable economic growth. This work explores the integration of AI across diverse domains including urban energy optimization, industrial automation, transport electrification, renewable energy forecasting, grid management, and circular economy practices. It highlights AI’s role in improving emissions monitoring, carbon markets, and policy compliance while addressing economic imperatives such as cost reduction, return on investment, and labor market transformations. Challenges related to the energy consumption and carbon footprint of AI technologies, ethical considerations, data privacy, and scalability are examined alongside strategies for mitigation and responsible governance. Emerging technologies and next-generation AI models are identified as key enablers for advancing green innovation and digitalization, with emphasis on interoperability, equitable access, and long-term resilience. The synthesis underscores the necessity of interdisciplinary collaboration and adaptive policy frameworks to maximize AI’s contributions toward achieving global sustainability targets and fostering a resilient low-carbon economy.
Keywords: Artificial Intelligence in Energy Systems, Climate Economics, Energy Efficiency, Carbon Emissions Reduction, Sustainable Economic Growth, AI and Renewable Integration, Large Language Models, Green Technology Economics, Environmental Policy Modeling, Cost Optimization in Climate Strateg