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Monitoring inoculum density of the stripe rust pathogen of wheat and evaluating weather variables in relation to disease severity in eastern Washington
Full text linkPuccinia striiformis f. sp. tritici (Pst), is a foliar fungal pathogen that causes stripe rust, resulting in yield loss and quality reduction of wheat across the U.S., including the Pacific Northwest (PNW) region. Stripe rust monitoring has relied heavily on visual disease observations, but recently efforts to sample airborne inoculum followed by identification and quantification through polymerase chain reaction (PCR) have been used to detect airborne fungal pathogens early in the season. These spore sampling techniques are being used due to a need for increased monitoring as disease dynamics shift with changing interactions among hosts, pathogens, and their environment. Predictive models, which have been used and improved upon for stripe rust in the PNW since the early 1980s look at how the environment affects stripe rust severity or yield loss based on the historical weather and disease data. As the climate continues to change, the models may need to be periodically improved. Modeling based on inoculum density, which is independent of historical data, could offer a new approach for direct prediction and monitoring the disease. In this study, a spore trapping network was set up at multiple locations in eastern Washington using two types of samplers: Burkard air samplers and rotorod-like samplers, as well as a biological assay with susceptible wheat plants to monitor inoculum densities of Pst and to detect other fungal pathogens as well. Air samples were collected from each location and sent to the National Agricultural Genotyping Center in Fargo, ND, for detecting target pathogens using quantitative real-time PCR assays. Pst spores were detected in all locations at least once from 2022 – 2024. In addition to Pst, spores of Puccinia graminis f. sp. tritici (stem rust), as well as spores of wheat leaf blotch fungi, including Parastagonospora nodorum, Pyrenophora tritici-repentis, and Zymoseptoria tritici (Stagonospora nodorum leaf blotch, tan spot, and Septoria tritici blotch respectively), were also detected. In comparison of the different air samplers, Burkard air samplers collected more stripe rust spores than rotorod-like samplers, but they were inconsistent when compared to rotorod-like samplers in collecting other fungal spores.Temperature and moisture variables were evaluated for changing trends over 60 years in Pullman, WA. These variables were then evaluated using similar procedures from a previous study completed by Sharma-Poudyal and Chen in 2011 to evaluate if weather changes affect variables significantly associated with stripe rust damage. The stripe rust yield loss data and weather data from 1975 – 2024 were used to compare significant variables identified in the previous study and the current study. Several single variable models were developed using the significant variables found, and some were significant at p-value = 0.5, such as the August sum of maximum temperature (r2 adjusted = 0.189, p-value = 0.002). This portion of the study was inconclusive, as there are likely differences in variable analysis and weather data sources that contributed to the differing significance of the variables found in each study, as well as other confounding variables that were not accounted for in the single variable models.In a separate study, three candidate models were developed using monthly weather variables from 1960 – 2023 and a set of stripe rust severity data compiled from several different sources for Washington state. The logistical regression models were developed using several temperature and moisture variables, as well as the stripe rust level data. The models developed in this study varied from other models currently being utilized worldwide and in the U.S., but they all utilized similar climate components that indicate the weather plays a crucial role in stripe rust disease development. These models could be used as preliminary framework for more complex models in the future that encompass the changing weather trends and allow for more accurate predictions for growers managing stripe rust in eastern Washington
A Co-Simulation Framework for Assessing Transmission Market Impacts of New Controls on the Grid
Full text linkThe power grid is transitioning to a more integrated and complex system with increasing flexible energy resources at the distribution level. Although such resources present a huge potential for enhancing operational efficiency, improper coordination can cause operational issues impacting the stability of the grid and thereby necessitates comprehensive assessment within integrated bulk power systems. Bulk system operations typically rely on a series of complex market process coordinated over multiple time-horizons. Simulating such operations can be complicated with a high barrier to entry. This work presents wrapper-based interfaces, leveraging MATPOWER-MOST to reduce the complexities for emulating wholesale market operations and minimize the barriers for evaluating impacts of coordination designs. The wrapper contains several functions that encapsulate the complex formatting and coordination requirements between market processes and organizes the co-simulation-based information exchange. The interfaces are implemented on an 8-bus test system representing the Electric Reliability Council of Texas (ERCOT) region. Simulation results demonstrate the wrapper capabilities to model wholesale market operations and evaluate the impact of coordinating flexible resources through appropriate operational metrics
Creating a More Inclusive School: Secondary Principal Practices Supporting Inclusion
Full text linkSpecial Education has changed significantly in the United States over the last fifty years. The current policy recommendations by the state and federal government, as well as legal precedence set by the Supreme Court insist that students are served in the most appropriate least restrictive environment. In this qualitative study, seven secondary principals in Washington state were interviewed to understand how they moved their schools towards increased levels of inclusion. Through many challenges, these principals implemented organizational changes and led their schools towards more inclusion. There are several implications for educational practice; principal preparation programs must begin to institute coursework that supports principals in this work and the state of Washington must begin to fund schools in a manner that they are able to implement inclusionary opportunities for students with IEPs
RELIABLE SNOWPACK AND STREAMFLOW MODELING USING DATA-DRIVEN AND BIOPHYSICAL APPROACHES
Full text linkSeasonal snow is a critical component of the water and energy cycle in snow-dominated regions, supporting water supply, hydropower generation, agriculture, and ecosystems. Despite advances in land surface models, uncertainties in the representation of snow processes—particularly snow accumulation, melt dynamics, and precipitation phase partitioning—limit the reliability of model-based water resource forecasts. This dissertation addresses three key challenges in improving hydrologic modeling of snow-dominated basins: (1) identifying model parameters and processes most responsible for uncertainty in snow-related outputs, (2) improving precipitation phase partitioning, and (3) integrating snow metrics into model calibration. Application of a hybrid local-global sensitivity analysis on VIC-CropSyst model simulations for the Pacific Northwest USA revealed that a small subset of parameters exert disproportionate influence on snow metrics, with sensitivities varying by hydroclimatic setting. Building on these insights, an enhanced precipitation partitioning method incorporating surface relative humidity alongside surface air temperature reduced biases in snow and streamflow metrics in many, though not all, contexts. Finally, a blueprint framework for multi-objective calibration was detailed for further bias reduction by jointly optimizing snow and streamflow metrics, although computational and practical barriers to implementation need to be addressed. Together, these contributions provide both a foundation for targeted model improvements and a transferable approach for reducing hydrologic model biases in snow-dominated basins, with implications for water supply forecasting, hazard preparedness, and climate change adaptation
SCALABLE ALGORITHMS AND SOFTWARE FOR GENOME ASSEMBLY AND HYBRID SCAFFOLDING
Full text linkThe increasing accuracy and accessibility of long read sequencing technologies, such as PacBio HiFi, have revolutionized genome assembly. However, assembling complex genomes with high contiguity and minimal computational overhead remains a significant challenge. Current state-of-the-art tools struggle with scalability as genome size increases, often requiring weeks to months for mammalian-sized genomes while consuming hundreds of gigabytes of memory. Moreover, existing approaches leave substantial gaps in genome completeness—only 1.5-6.5% of assemblies in public repositories achieve reference quality, creating a backlog of over 2.5 million fragmented draft genomes. This dissertation addresses these challenges through two complementary graph-theoretic approaches: a parallel hybrid scaffolding workflow that upgrades existing draft assemblies using long reads, and a scalable long read assembly framework based on explicit vertex reordering.Our first contribution, Maptcha, is a novel parallel workflow for hybrid genome scaffolding that combines pre-constructed assemblies with newly sequenced long reads. Maptcha employs alignment-free sketch-based mapping to rapidly identify long reads spanning multiple contigs, then constructs a ⟨contig,contig⟩ graph capturing these linkages. We introduce a novel graph-theoretic "wiring" heuristic that iteratively connects contigs by selecting the most credible links based on long read support while avoiding questionable connections in repetitive regions. A batching design partitions the scaffolding problem into independent parallel subproblems, enabling efficient distributed execution while bounding memory consumption.Our second contribution, Tile-X, addresses scalability of de novo long read assembly by treating read ordering as an algorithmic problem beforehand the genome assembly starts. Rather than implicitly determining read order during graph traversal, Tile-X explicitly computes read orderings using graph-theoretic vertex reordering techniques—including Reverse Cuthill-McKee (Tile-RCM), Metis-based partitioning (Tile-Metis), and community detection (Tile-Grappolo), to group reads from similar genomic regions. We also introduce Tile-Far, a novel sparsification heuristic inspired by minimum tiling paths that selects a minimal informative subset of reads covering the genome with reduced redundancy. The computed ordering enables partitioned parallel assembly where consecutive batches of reads are independently assembled with controlled overlap, dramatically reducing per-batch memory requirements while maintaining assembly continuity.We present extensive experimental evaluation of both frameworks across diverse genomes ranging from bacteria to human. Maptcha consistently produces high contiguos scaffolds with values exceeding input contigs by over three orders of magnitude while outperforming state-of-the-art hybrid scaffolders in both assembly quality and runtime performance, reducing time-to-solution from hours to minutes while maintaining memory usage under 20 GB. Tile-X demonstrates that explicit vertex reordering and sparsification maintain assembly quality comparable to state-of-the-art long read assemblers while improving scalability and reducing computational requirements. Both frameworks are available as open-source software, providing practical and efficient solutions for generating high-quality assemblies of large and complexgenomes
FOSTERING INDIVIDUAL RESPONSIBILITY IN COOPERATIVE LEARNING: EXPLORING PERCEPTIONS, PRACTICES, SUCCESSES AND CHALLENGES AMONG SECONDARY EDUCATION TEACHER CANDIDATES
Full text linkIndividual responsibility is a key component of cooperative learning that demonstrates how each group member is responsible for their own learning and for supporting the learning of others. It involves taking ownership of one’s progress, contributing to group work, and ensuring that all members fulfill their assigned duties to achieve a collective goal. This concept promotes active participation, collaboration, deeper engagement, and a strong understanding of the subject matter. This study employed a qualitative case study design to investigate how secondary education teacher candidates perceive and implement individual responsibility in cooperative learning settings. Data was gathered through interviews, classroom observations, and document analysis. The findings revealed three main themes: perceptions of individual responsibility, strategies to promote it, and the successes and challenges encountered. Codes that were consistently repeated under the themes mentioned above included: motivation through peerresponsibility, learning through reflection and peer perspectives, active participation through collective commitment, preparing for future collaboration in teaching, fostering responsibility through communication, teaching roles and group expectations, the role of familiarity and trust, enjoyment in group work, navigating emotional barriers, and promoting fairness and shared responsibility. Overall, the study highlights the positive impact of cooperative learning when individual responsibility is emphasized. A key implication is that secondary education teacher candidates can apply individual responsibility within group tasks to improve participation and collaboration in the classroom.Keywords: Cooperative learning, individual responsibility, free ridin
Transforming MARC for a Linked Data Age
No full textThis talk will focus on the transition of MARC to a linked data environment and summarize the Core MARC Formats Transition Interest Group’s program during the 2025 ALA Core IG Week. The talk will cover Ex Libris' efforts to facilitate MARC to Linked Data workflows within Alma and Primo, the Library of Congress' BFProd (BIBFRAME in Production) initiative and "Modern MARC" effort for better alignment with linked data, OCLC's approach to leveraging linked data in the hybrid environment, and pedagogical strategies for teaching linked data to future librarians. These presentations will offer valuable insights, tools, and methodologies for libraries navigating the hybrid MARC and linked data environment, enhancing interoperability, discovery, and metadata quality in this evolving landscape. The session will conclude with a brief open discussion.</p
Washington Green Transportation Program report to the Washington State Legislature November 2025
Full text linkIn 2019, the Washington State Legislature passed “Advancing green transportation adoption,” legislation which directed the Washington State University (WSU) Energy Program to establish and administer a technical assistance and education program for public agencies on the use of alternative fuels and vehicles (Engrossed Second Substitute House Bill 2042, Chapter 287, Laws of 2019). Since our foundation, WSU Energy Program’s Green Transportation Program (GTP) has provided our services to all public agencies, including cities, counties, Tribes, transit agencies, school districts, colleges and universities, utilities and public utility districts (PUDs), public ports, and other public entities to accelerate the transition to zero-emission vehicles (ZEVs). This report summarizes the recent accomplishments and impacts of the GTP during the 2023-25 biennium. It details our extensive education program, the results of our direct technical assistance, several focused initiatives addressing the targeted needs of our partners, and our plans for integration into the new Washington Zero-Emissions Incentive Program (WAZIP)
Here's What You're Not Hearing About Electric School Buses
Full text linkIf you’ve read a headline or heard a story about electric school buses (ESBs) not working in the cold, getting stranded in places where charging isn’t available, or being too expensive to maintain—you’re not alone. These stories make the rounds in Washington school districts, sparking concern and hesitation about adding ESBs to a school bus fleet. But we’ve looked closely at the facts, the context behind those stories, and what’s actually happening here in Washington
Wicked Problem: Toxic Waste Disposal in Historic Restoration
No full text"Design theory is a system that explains the fundamental principles and elements of design. It is the understanding of the physical aspects of design as well as the psychological angles in design. It helps designers to understand not only how to make spaces more visually appealing, but also how to create an environment that influences well-being and sustainability. This ties into the context of historic restoration, and the wicked problem of the disposal of toxic materials. Materials like asbestos, lead paint, and PCBs, all of which pose complex challenges that do not have simple solutions for design, health, and the environment.The disposal of toxic materials is a wicked problem. The complexities of handling potentially harmful materials include balancing ethical decisions, such as choosing materials that honor human health, with practical decisions, such as managing historic elements and spaces. These decisions affect not only the future occupants; they can also impact the laborers and the proximal neighbors of a site. The social consequences of these disposal decisions will affect the communities that live near these disposal sites and may suffer from poor waste management. Regulations and preservation standards are also conflicting aspects that designers must navigate around and between to protect buildings with historic authenticity and the safety of the communities and environment.Understanding design theory and its importance allows designers to approach this wicked problem systemically. The disposal of these toxic and harmful materials involves ethical, environmental, and cultural trade-offs that can still cause negative impacts on the health of the surrounding community. The theoretical framework of these types of problems encourages designers to consider how the ripple effect of their disposal choices, such as where these materials end up, whose lives are impacted by these decisions and what values are preserved or compromised in this historic restoration effort. This paper uses the Ten question framework to explore toxic waste disposal in historic restoration, examining how values, bournaries, lived experience, sensory and ethical considerations, materials, ecological systems, and a case study reveal the complexity of designing within this issue.