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Garfield County Resource Guide - Washington
Get PDFCounty level and region-specific resource guides focused on mental health and substance use
Sustainable Alternatives for Managing Silver Scurf on Potato Microtubers and Minitubers
Get PDFSilver scurf, caused by Helminthosporium solani, is a prevalent tuber blemish disease of potato negatively impacting tuber quality. To reduce reliance on the use of synthetic fungicides for managing silver scurf, this study evaluated 4 pathogen-associated molecular patterns (PAMPs), 3 damage-associated molecular patterns (DAMPs), 5 phytohormones and their-related compounds, and 6 other compounds for their in vitro potential to suppress H. solani infection and sporulation on potato tubers using microtuber and minituber infection assays. Phosphorous acid significantly reduced pathogen sporulation, consistent with its known efficacy. Among the defense elicitors tested, Pep13 notably suppressed H. solani sporulation on microtubers, indicating its promise as a defense inducer. Additionally, cellulose nanofibers (CNFs) derived from softwood and bamboo markedly decreased infection, with bamboo CNF showing greater efficacy. This study suggests that CNFs, in addition to phosphorous acid and Pep13, offer promising sustainable alternatives for managing silver scurf, enhancing the postharvest quality and shelf life of potato tubers
Building Sustainable Change
No full text"Originally, designers imagined balance when they thought about art on the wall, pillows on the couch, and everything aligned. Although now designers know that design is more than simply what we can see, it is also about how our choices affect the people and environment around us. Design is based on lived experience, values, an memory. In The Memory Palace, Hollis (2012) explains how places influence identity and store memories. This helped me realize that interior design affects not just what we remember but also what we leave behind, which is why it has emotional and environmental significance.This understanding has a connection to what Rittel and Webber (1973) refer to as wicked problems, these are difficulties that are so complex, connected, and filled with values, both personal and societal. Sustainability is a perfect example of this. Every design choice has an impact on waste management, manufacturing processes, and the health of humans. As Spencer (2013) points out, wicked problems in design are chances to rethink our approach rather than see challenges overcome. A systemic approach is essential for sustainable design, one that considers long-term environmental, cultural, and social effects in addition to aesthetically pleasing characteristics. Goss, Tromp, and Schifferstein (2025) explain, designing sustainably requires understanding how system dynamics work across both scales and time. This allows designers to balance immediate functionality with long term ecological and social well-being.
Veterinary Medicine Extension Newsletter, July 2025
No full textIncluded in this newsletter: Recent updates on BRD management: A spotlight on antimicrobial stewardship and genomic selection; Latest developments in mastitis management; History of screwworms in the U.S
GENOME-WIDE EVOLUTIONARY CHARACTERIZATION AND MOLECULAR GENETIC ANALYSIS OF THE AT-HOOK MOTIF CONTAINING NUCLEAR LOCALIZED (AHL) GENE FAMILY IN A EUDICOT VERSUS MONOCOT SYSTEM
Get PDFThe AT-HOOK MOTIF CONTAINING NUCLEAR LOCALIZED (AHL) gene family encodes proteins characterized by the AT-hook motif, which facilitates binding to AT-rich DNA sequences, and the PLANT AND PROKARYOTIC CONSERVED (PPC) domain, involved in protein-protein interactions and nuclear localization. AHL genes play diverse roles in plant development and responses to environmental stimuli by influencing chromatin remodeling and gene transcription. This study explores the AHL gene family in Brachypodium distachyon (Brachypodium), a monocot model. This research identified 22 BdAHL genes, analyzing their structure, phylogenetic relationships, and expression profiles, and compared them to AHL genes in other plant species, particularly Arabidopsis thaliana (Arabidopsis). Examination of the evolutionary history of these genes, revealing a high degree of conservation across plant lineages, which underscores their importance in fundamental plant processes. Key findings include the evolutionary conservation of AHL genes, the presence of conserved motifs (specifically, the AT-hook motif and the PPC domain) and differences in gene structure among AHL gene types, suggesting functional diversification within the gene family. The analysis also examined how their expression varies across different tissues and developmental stages in Brachypodium compared to Arabidopsis. This research also focuses on investigating the functional conservation and divergence of AHL genes between Arabidopsis and Brachypodium. This comparative research approach strived to understand how AHL gene function has evolved in the two major angiosperm lineages: a monocot versus eudicot. Overexpression analyses of specific Arabidopsis AHL genes in Brachypodium reveal that clade A AHL genes (AHL27 and AHL29) delay flowering, similar to their function in Arabidopsis, indicating a conserved role in flowering time regulation. In contrast, the clade B gene AHL6 promotes early flowering when overexpressed in Brachypodium, highlighting a potential divergence in function. This suggests both conserved and divergent roles for AHL genes in regulating flowering time, and possibly other developmental processes, between dicots and monocots. The implications of these findings for understanding the evolution of plant development and for potential crop improvement strategies are discussed. Studies on the AHL gene family are proposed to be a valuable tool for enhancing global crop improvement. Research in this area has the potential to significantly impact agricultural applications, including enhancing productivity, fruit quality, fiber production, grain yield, and nutritional content, as well as improving crops' resilience to climate-driven environmental stresses. The ability to translate scientific discoveries related to AHL genes into practical applications holds special significance for addressing challenges in global food security and promoting sustainable agricultural practices
Diagnostics for Ordinal Data
Get PDFThe problem we aim to address in this dissertation is to develop a more straightforward method for examining correlation-related diagnostics in ordinal data. Analyzing data that falls between numerical and categorical types can be challenging, particularly when it involves ordinal variables. One major challenge is the limited availability of diagnostics for evaluating the performance of ordinal regression models. Most often, the diagnostics performed for ordinal regression are the proportional odds assumption and the goodness-of-fit test. The proportional odds assumption evaluates whether the relationship between the predictors and the odds of being in a higher versus a lower category is consistent across thresholds, while the goodness-of-fit test assesses whether the model fits the data better than a null model. While these are somewhat easily available in software, the problem of dependence is not. The two main issues related to correlation in ordinal data are: multicollinearity, when the predictors are highly correlated, and autocorrelation or familial dependence, when the responses are correlated with each other. While diagnostics for these are easily available in the General Linear Model (GLM), this is not the case for ordinal data. The approaches that exist for ordinal data are theoretically and computationally cumbersome and time-consuming. For multicollinearity, we can directly examine the structure of the design matrix and predictors, and consider eigenvalues and condition numbers, as in GLM. However, for ordinal data, our estimates are based on maximum likelihood estimates, and thus a direct examination of the design matrix is not necessarily the best approach. Similarly, we could consider generalized estimating equations or Binary Dynamic Logit for Correlated Ordinal (BDLCO) method for modeling the dependence structure, which are computationally intensive. We aim to determine when BDLCO is needed versus using traditional methods for ordinal data, assuming proportional odds. In this dissertation, our primary objective is to develop a “quick and dirty” method to determine whether multicollinearity is indeed an issue and whether methods like ridge or lasso are warranted. In the same way, we try to quickly diagnose "dependence issues". If dependence is detected, we would suggest using a method like BDLCO. Our approach is to utilize our ordinal response and its underlying relationship with predictors through the slope estimates to estimate the underlying latent response as a function of the predictors, and then use readily available methods to perform quick checks for multicollinearity or autocorrelation. Essentially, we show that the slope estimates from the ordinal response can aid in estimating the slope estimates for the underlying latent variable in an Approximate Latent Linear Model (ALLM). The idea is that once we estimate such a continuous response, then we can use the multivariate normal distribution of the approximate latent linear response to understand autocorrelation and multicollinearity. Thus, we can utilize standard diagnostic techniques developed within the GLM framework, such as the Durbin-Watson test and variance inflation factors, to address issues of autocorrelation and multicollinearity. Our simulation results show that this procedure gives us a quick way to understand and diagnose problems that are theoretically and computationally difficult in a much faster way. We use our method on a data example, which helps to make decisions about ordinal data in the presence of dependence