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Durability Assessment of Low-carbon Concretes using Electrical Resistivity, Chloride Migration and Diffusion Modelling
No full textDurability design for reinforced concrete increasingly relies on performance-based indicators of transport processes that govern corrosion initiation. This study evaluates concretes with supplementary cementitious materials (SCMs) (fly ash (FA), ground-granulated blast-furnace slag (GGBS), limestone powder (LP), and limestone calcined clay cement (LC3)) using electrical resistivity and rapid chloride migration (RCM, NT Build 492) testing. Twelve mixes (w/b = 0.40 and 0.55), including binary and ternary binders benchmarked against Portland cement (PC), were tested. Resistivity was measured on cubes with embedded stainless-steel electrodes, whereas chloride diffusion coefficients were measured directly using the RCM method and compared with the values calculated from the resistivity data via the formation-factor approach. SCM concretes exhibited markedly higher resistivity and lower chloride transport than PC. LC3 and LP-ternary systems achieved the highest resistivity, while FA and GGBS mixes exhibited significant reductions in migration diffusion coefficients, with LC3 mix performing comparably to GGBS. Diffusion coefficients estimated from resistivity were in reasonably good agreement with RCM measurements, underscoring the consistency of the paired methods. Overall, the results confirm the durability benefits of low-carbon SCM binders under chloride exposure and highlight the value of combining resistivity with RCM to obtain transport parameters for performance-based design
Building Elementary Student Science Skills and Interest: A Reciprocal Engagement Partnership
No full textScholar-practitioner partnerships grounded in community engagement principles focus on mutually beneficial relationships that meet critical community needs while integrating learning, discovery and service. Our research aims to identify how and the degree that a physical activity-based science learning program contributes to students’ science learning and interest while aiming to support the overall wellbeing of a community elementary school that serves families from under resourced (98% free/reduced lunch) and diverse racial and ethnic backgrounds (48% non-white). Partner school teachers and staff members were invited to participate in an interview where they answered questions about their perspectives and experiences with the program itself, the degree that the program meets the needs of their students, teachers and school, and how the program demonstrates the university’s core engagement values. Interviews were transcribed and then coded through the lens of constructivism. Teachers and staff understood the challenges associated with piloting and refining the program’s curriculum while discussing how the process would benefit their students (by offering new methods of learning), teachers (creating fun student-teacher interactions), staff (integration of a complementary and innovative learning approach) and the researcher’s scholarly work (pilot of a new curriculum). Participants offered tangible solutions to program challenges including increasing awareness of the program’s research plan and communication of findings. They also discussed concerns regarding the sustainability of the program given its single-instructor approach and the difficulties of replicating this collaborative effort at new schools. As the partnership enters its third year, this presentation will also describe the evolution of the curriculum and its research agenda to better meet the needs of students and their school, and efforts to increase science rigor without increasing its burden on students, teachers and staff. Findings demonstrate opportunities and perspectives on scholar-practitioner partnerships with a community justice approach
Exploring the Efficacy of a Source-Based Writing Tutoring Intervention for Multilingual Students in the Writing Center
No full textSource-based writing skills, which include evaluating, synthesizing, and citing sources, are skills that students are expected to acquire as part of college-level writing. Unfortunately, many multilingual writers (MLWs), especially those in advanced degree programs, lack programmatic support and instruction. Thus, writing centers represent a critical site to offer MLWs tutorial-based support. Our study examined whether or not writing centers can help MLWs develop—and transfer—source-based writing skills in a sequence of three tutorials. We recruited five advanced student MLW participants from different cultural backgrounds who were uncomfortable with source use. Through pre-and postwriting samples, interviews, writing process recording videos, and a long-term follow-up, our findings indicate that our three-sequence tutorial significantly improved advanced MLWs’ source-based writing skills and transferred to the next semester. Improvements occurred in the areas of selecting, organizing, and connecting sources as well as in engaging in appropriate source use and avoiding plagiarism, although some areas showed stronger gains than others. This study contributes to the field’s development of replicable, aggregable, and data-supported best practices to explore the efficacy of tutoring for specific populations. We offer suggestions for writing centers to develop, test, and create tutoring-based MLW support programs
Methodology for evaluating precision spraying using drones.
No full textThis study presents a comprehensive methodology for evaluating precision spraying in agriculture using drone technology. Precision spraying has become a key innovation in sustainable farming, offering increased accuracy, reduced waste, and minimized environmental contamination. However, to ensure these benefits are realized, drones must be properly tested, calibrated, and validated under real field conditions. The proposed methodology integrates drone flight calibration, field-based spraying trials, and post-field analysis using hydrosensitive cards processed through specialized software tools, such as ImageJ and StainMaster. By systematically varying flight parameters such as altitude, speed, and nozzle type, the study assesses how these factors influence droplet size, density, and overall spray coverage. Field data collection remains an essential component, as it provides ground-truth verification that technology alone cannot replace. Results emphasize that the effectiveness of drone-based spraying depends not only on equipment precision but also on careful field evaluation to ensure that sprayed products reach the plant target. Software analysis complements this by quantifying spray quality, helping optimize operational parameters for improved efficiency and sustainability. Ultimately, this methodology offers a replicable framework that bridges advanced technology and practical agronomic evaluation. It reinforces that while drones and digital tools are transforming agriculture, the success of precision spraying depends on maintaining a strong connection between technological innovation and hands-on field validation
High Throughput Phenotyping for Improved Sorghum Protein Digestibility
No full textProtein digestibility (PD) is a quantitative trait that is generally lower in sorghum than other cereals such as corn & rice. This affects the ability for humans and animals to obtain vital nutrients from sorghum food products and feedstuffs. Previous efforts helped create and identify sorghum lines with highly digestible protein (HDP) phenotypes using mutagenesis. This creates variation for the trait that can be exploited by breeding programs. However, phenotyping large populations is highly time consuming using wet-chemistry techniques and can exhaust resources quickly, leading to bottlenecks in development of breeding objectives. Near-Infrared Spectroscopy (NIRS) offers a fast, non-destructive alternative to this approach. Increased ability to identify and characterize HDP phenotypes from diverse populations allows for effective trait utilization, specialized downstream applications, and identification of causative alleles for novel gene discovery and germplasm development. Here, we utilize a phenotyping pipeline that takes advantage of NIRS to predict PD in unknown mutant genotypes across generations, validate NIRS positives with wet chemistry, and eventually will be integrated with genetic analysis to investigate potential genetic and allelic variation for this sorghum PD. After wet chemistry validation, four candidate mutant EMS lines were found to display a 20-30% increase in PD compared to the wild-type progenitor line BTx623, the reference genome for sorghum. Screening large mutant populations for novel mutants with increased PD via NIRS allows for high-throughput and forward genetics approaches to efficiently develop germplasm for this trait, and shows potential as an approach for improvement of grain quality traits that are infeasible to phenotype in the field
Applied Statistical and Deep Learning Methods for Multi-Environment Genomic Prediction in Maize
No full textPredictive breeding has quickly become a powerful tool for plant breeding because of its ability to apply a high level of genotypic selection in non-target environments. However, much of the work regarding predictive breeding has used training data that is highly replicated and maintains the same genotypes and locations over multiple years, for instance the Genomes2Fields project. In commercial breeding programs, selection from predictive breeding could have the greatest return early on, when there is a great deal of genetic diversity. However, training models on this early pipeline data is difficult because genotypes are generally not replicated, and locations may not be static over time. The greatest difficulty that arises from a lack of replication is effectively parsing genotypic and environmental effects. This research, through the Purdue Data Mine and Becks Hybrids, has sought to use machine learning and deep learning to develop predictive breeding models that are able to accurately parse and predict genotypic and environmental effects for novel hybrids in unknown environments. We have developed methods for representing environmental and genotypic data that limits overfitting and emphasizes within location ranking accuracy. This poster shows our findings for the best model types and architecture to provide accurate predictions for unknown genotypes and environments and details some of the unique challenges caused by working with a commercial breeding dataset
Was Spinoza a Deleuzian? Rethinking the Politics of Emotions and Affects
No full textA salient tradition in contemporary affect theory heavily relies on distinguishing between emotions and affects. The former refers to structured categories of socially coded affective states, while the latter denotes the pre-social libidinal flow underlying emotions. This distinction is commonly attributed to Spinoza and is thought to have been further developed by Deleuze. In this article, I argue that this overall historical picture is misleading and inaccurate. Deleuze radically transforms Spinoza’s theory of affect for the ends of his own ethical-political philosophy. Moreover, I argue that Deleuzian and similar conceptualizations of affect fail to fulfill their political and ethical promises due to two critical problems. In the last section, I show that a unified notion of emotion inspired by Spinoza, which does not create a sharp rift between emotions and affect, can perform the same explanatory function intended by the emotion-affect distinction while allowing us to circumvent these problems
Unpacking Identity Work Mechanisms for a Person-Centered Approach to Business and Management Education
No full textWe explore identity work among undergraduate business students who resist the identity prevailing in traditional business schools. The study investigates an educational program that fosters identity work, allowing students to add facets to their emergent identity. Through in-depth interviews, the researchers uncovered a process in which students resist the hegemonic identity of business administrators, seeking alternative experiences that redefine their identity. Our research contribution is two-fold. First, we extend the concept of identity workspaces by introducing three mechanisms: autonomy, a psychological safe space, and group embeddedness. These mechanisms enable students to engage in an identity work process and reidentify with their business and management courses. Second, we show that the concept of a dichotomy between a real self and a fake self must be overcome in favor of a multifaceted conception of identity. The study also offers valuable insights for educators, practitioners, and policymakers, encouraging initiatives that support multifaceted identities in the educational context by adopting new learning and teaching methodologies
Building Your Epic Life: Your Journey, Your Way, Your Masterpiece
No full textBuilding Your Epic Life empowers young people to understand that failure is an inevitable—and essential—part of the journey to success. The author shares his own challenges and struggles, showing that no path to success is linear and without setbacks. The book teaches the value of building a healthy body, mind, and spirit, and includes exercises that offer actionable plans for individuals to realize a meaningful, self-defined life based on their core values. A proven roadmap workbook and short lectures guide readers through a series of practical steps to discover their purpose, vision, and understand the value of mentorship—and why each of these is fundamental in identifying life’s important moments and opportunities. Building Your Epic Life also recommends a range of books, affirmations, and daily routines for students and professionals who want to reach their full potential.https://docs.lib.purdue.edu/purduepress_ebooks/1089/thumbnail.jp
Applied Research for Corn Production in Indiana, 2024
No full textThe 2024 edition of Applied Research for Corn Production in Indiana offers accessible, research-based tips for farmers who want to improve corn production practices by using applied field-research trials. Daniel Quinn and the Purdue University Corn Agronomy team reveal practical ways to boost yields, reduce costs, and improve sustainability on the farm. Their findings are derived from applied research trials across the state and relate to important topics such as planting practices, fertilizer use, crop nutrition, cover crops, and new technologies. Applied Research for Corn Production in Indiana distills complex research into clear insights and supplies corn producers with effective methods to enhance farm efficiency and productivity.https://docs.lib.purdue.edu/purduepress_ebooks/1095/thumbnail.jp