406 research outputs found
Browntail Moth (Euproctis chrysorrhoea) Integrated Pest Management Program: Evaluation of Monitoring Traps and Biopesticides
Get PDFBrowntail Moth (BTM; Euproctis chrysorrhoea) is a non-native species currently outbreaking in Maine. BTM are polyphagous folivores and feed on a variety of woody plant species, including many economically and ecologically important ornamental and forest trees such as oaks and apples. Human health is also a concern as BTM larvae produce urticating hairs that can cause severe dermatitis in people. New monitoring and management programs are urgently needed, with the current population densities reaching a 100-year high.
The Maine Forest Service monitors BTM populations by visually assessing winter nest densities and defoliation patterns, both time and labor intensive. This research investigated the optimization of BTM sex pheromone monitoring traps in field trials during the adult flight period in 2021 and 2022. Trials in 2021 tested lure purity and two trap types, bucket style and delta style sticky traps. Results indicate that male moths were more attracted to lures with \u3e 95% purity and bucket-style traps. Trials in 2022 tested additional trap styles and color variations. Results from 2022 indicate that white traps were significantly more attractive than green or multicolored traps. The Pherocon 1C trap caught the most male BTM; however, it was not significantly different from the other white traps, indicating that any white trap could be recommended for use in future long-term monitoring programs for BTM.
In addition to monitoring evaluations, management strategies were tested for the control of BTM. Current control is the responsibility of municipalities and landowners, and broad-spectrum insecticides are commonly used due to the limitations of alternative control methods. Trials developing methods and testing the efficacy of more targeted biopesticide were conducted to determine if they were effective at reducing BTM populations. Initial trials observed BTM behavior in bioassay studies. Differences were found in the amount eaten and mass of larvae depending on the number of larvae present in bioassay cups (10, 25, 50 larvae, or the whole winter nest), which indicates that the amount of larvae present can impact lab experiment results.
Treatment bioassay trials testing the efficacy of different commercially available Bacillus thuringiensis (Bt) products were conducted in 2021 and 2022 on pre-diapause larvae. Survival and defoliation rates were determined for the various Bt treatments, both alone and including the use of spider peptides, which have the potential to increase the longevity and compound efficacy of Bt treatments. Results indicate that Bt products significantly reduce the amount eaten by larvae from control (water) treatments. Deliver (Bt kurstaki) used with peptide products was not significantly different from the current industry standard biopesticide product, Entrust (spinosad), a broad-spectrum insecticide. Peptide treatments alone did not significantly reduce the amount eaten from control treatments, but there were inconsistencies in the results of Basin and further testing is needed. The results of this research provide evidence supporting the adoption of new monitoring approaches and the potential use of less broad-spectrum biopesticides to manage BTM
AUGURES : profit-aware web infrastructure management
Get PDFOver the last decade, advances in technology together with the increasing use of the Internet for everyday tasks, are causing profound changes in end-users, as well as in businesses and technology providers. The widespread adoption of high-speed and ubiquitous Internet access, is also changing the way users interact with Web applications and their expectations in terms of Quality-of-Service (QoS) and User eXperience (UX). Recently, Cloud computing has been rapidly adopted to host and manage Web applications, due to its inherent cost effectiveness and on-demand scaling of infrastructures. However, system administrators still need to make manual decisions about the parameters that affect the business results of their applications ie., setting QoS targets and defining metrics for scaling the number of servers during the day. Therefore, understanding the workload and user behavior ¿the demand, poses new challenges for capacity planning and scalability ¿the supply, and ultimately for the success of a Web site.
This thesis contributes to the current state-of-art of Web infrastructure management by providing: i) a methodology for predicting Web session revenue; ii) a methodology to determine high response time effect on sales; and iii) a policy for profit-aware resource management, that relates server capacity, to QoS, and sales. The approach leverages Machine Learning (ML) techniques on custom, real-life datasets from an Ecommerce retailer featuring popular Web applications. Where the experimentation shows how user behavior and server performance models can be built from offline information, to determine how demand and supply relations work as resources are consumed. Producing in this way, economical metrics that are consumed by profit-aware policies, that allow the self-configuration of cloud infrastructures to an optimal number of servers under a variety of conditions. While at the same time, the thesis, provides several insights applicable for improving Autonomic infrastructure management and the profitability of Ecommerce applications.Durante la última década, avances en tecnología junto al incremento de uso de Internet, están causando cambios en los usuarios finales, así como también a las empresas y proveedores de tecnología. La adopción masiva del acceso ubicuo a Internet de alta velocidad, crea cambios en la forma de interacción con las aplicaciones Web y en las expectativas de los usuarios en relación de calidad de servicio (QoS) y experiencia de usuario (UX) ofrecidas. Recientemente, el modelo de computación Cloud ha sido adoptado rápidamente para albergar y gestionar aplicaciones Web, debido a su inherente efectividad en costos y servidores bajo demanda. Sin embargo, los administradores de sistema aún tienen que tomar decisiones manuales con respecto a los parámetros de ejecución que afectan a los resultados de negocio p.ej. definir objetivos de QoS y métricas para escalar en número de servidores. Por estos motivos, entender la carga y el comportamiento de usuario (la demanda), pone nuevos desafíos a la planificación de capacidad y escalabilidad (el suministro), y finalmente el éxito de un sitio Web.Esta tesis contribuye al estado del arte actual en gestión de infraestructuras Web presentado: i) una metodología para predecir los beneficios de una sesión Web; ii) una metodología para determinar el efecto de tiempos de respuesta altos en las ventas; y iii) una política para la gestión de recursos basada en beneficios, al relacionar la capacidad de los servidores, QoS, y ventas. La propuesta se basa en aplicar técnicas Machine Learning (ML) a fuentes de datos de producción de un proveedor de Ecommerce, que ofrece aplicaciones Web populares. Donde los experimentos realizados muestran cómo modelos de comportamiento de usuario y de rendimiento de servidor pueden obtenerse de datos históricos; con el fin de determinar la relación entre la demanda y el suministro, según se utilizan los recursos. Produciendo así, métricas económicas que son luego aplicadas en políticas basadas en beneficios, para permitir la auto-configuración de infraestructuras Cloud a un número adecuado de servidores. Mientras que al mismo tiempo, la tesis provee información relevante para mejorar la gestión de infraestructuras Web de forma autónoma y aumentar los beneficios en aplicaciones de Ecommerce
Subjective Wellbeing of Undergraduate Engineering Students: A Mixed Methods Study
Get PDFIn higher education, the prevalence of mental health issues among students has raised concerns regarding their overall success and wellbeing. While existing research often focuses on identifying and addressing mental health problems, there is a lack of emphasis on understanding the positive contributors to students\u27 mental health. In this study, I expand the concept of mental health beyond the absence of negative mental health states to include the presence of positive mental health aspects through the concept of Subjective Wellbeing (SWB) (feeling that your life is going well, not badly), of engineering undergraduate participants. Both qualitative and quantitative data were collected from engineering undergraduate students within the College of Engineering at Utah State in a Concurrent Mixed Methods paradigm through an online survey.
Analysis of the data provided valuable insights into SWB among undergraduate students and the factors perceived to contribute to it. Furthermore, this research offers recommendations aimed at enhancing the collegiate experiences of engineering undergraduates to positively influence their mental health and overall wellbeing. By focusing on the holistic understanding of subjective wellbeing, this study contributes to the broader dialogue on student mental health and the promotion of a thriving academic environment
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