Detecting Pathobiomes Using Machine Learning

Machine learning is a field with high growth potential due to the overall continuous progressions, developments, advancements, and improvements caused by the way it is used to help interpret and use large amounts of data [1]. One type of data that can be collected and analyzed by these machine learning models is data that is associated with DNA and information that the DNA gives. The research will be focusing specifically on using machine learning technology to detect pathobiomes indicative of salmonella pork. The pathobiome associated with salmonella is very similar to others, and this causes a problem for classification/detection with short-read sequencing platforms [2]. Because of this, it is important for decision makers to understand what kind of data is needed to help accurately predict these pathobiomes. This research consists of a variety of experiments that help determine what this kind of data is. This is done by reading data taken from various sequences from The National Center for Biotechnology Information (NCBI) database. This project is also being conducted within the backdrop of an existing project from the Walmart foundation project, Improving Food Safety of Pork Supply Chain [3]. [1] B. K, “5 essential steps for every deep learning model! — by bharath k — towards data science,” https://towardsdatascience. com/5-essential-steps-for-every-deep-learning-model-30f0af3ccc37, November 2022, (Accessed on 03/04/2023). [2] C. J. Grim, N. Daquigan, T. S. Lusk Pfefer, A. R. Ottesen, J. R. White, and K. G. Jarvis, “High-resolution microbiome profiling for detection and tracking of salmonella enterica,” Frontiers in microbiology, vol. 8, p. 1587, 2017. [3] C. E. Rainwater, “Improving food safety of pork supply chain, walmart foundation,” 2021

Detecting Pathobiomes Using Machine Learning

Machine learning is a field with high growth potential due to the overall continuous progressions, developments, advancements, and improvements caused by the way it is used to help interpret and use large amounts of data [1]. One type of data that can be collected and analyzed by these machine learning models is data that is associated with DNA and information that the DNA gives. The research will be focusing specifically on using machine learning technology to detect pathobiomes indicative of salmonella pork. The pathobiome associated with salmonella is very similar to others, and this causes a problem for classification/detection with short-read sequencing platforms [2]. Because of this, it is important for decision makers to understand what kind of data is needed to help accurately predict these pathobiomes. This research consists of a variety of experiments that help determine what this kind of data is. This is done by reading data taken from various sequences from The National Center for Biotechnology Information (NCBI) database. This project is also being conducted within the backdrop of an existing project from the Walmart foundation project, Improving Food Safety of Pork Supply Chain [3]. [1] B. K, “5 essential steps for every deep learning model! — by bharath k — towards data science,” https://towardsdatascience. com/5-essential-steps-for-every-deep-learning-model-30f0af3ccc37, November 2022, (Accessed on 03/04/2023). [2] C. J. Grim, N. Daquigan, T. S. Lusk Pfefer, A. R. Ottesen, J. R. White, and K. G. Jarvis, “High-resolution microbiome profiling for detection and tracking of salmonella enterica,” Frontiers in microbiology, vol. 8, p. 1587, 2017. [3] C. E. Rainwater, “Improving food safety of pork supply chain, walmart foundation,” 2021

Building healthy and resilient communities through service equity project evaluation : June 2022

Working in partnership with the Deddick Valley Isolated Community Group and in collaboration with the Errinundra to Snowy Community Recovery Committee, CERC (formally CERG) evaluated and validated existing data and new information in support of an appropriate health service model for the Errinundra to Snowy District of Far East Gippsland

Engaging Human-in-the-Loop for Autonomous Vehicle Simulation

Many autonomous vehicles are still in the development phase due to limited research and testing and will take a considerable amount of time to further develop before they are ready for public release. The main objective of this study is to introduce a human-in-the-loop simulation framework for supporting autonomous vehicle research. Our proposed simulation framework aims to facilitate AV assessment by providing a safer and more efficient way. Functionally, it is focused on the understanding of AVs’ operations in the presence of pedestrian users. The developed simulation framework allows a human pedestrian avatar to be integrated into the high-fidelity 3D virtual environment and interact with simulated autonomous vehicles via standard keyboard input methods or virtual reality (VR) methods. This enables safer pedestrian-AV integration research and testing, and the ability to implement a series of risky edge-case scenarios in less time and cost than would be feasible in a real-world setting

Multi-mycotoxin exposure assessment in UK children using urinary biomarkers - a pilot survey

Peer reviewedPostprin

A scoping review of community-based adult suicide prevention initiatives in rural and regional australia

The need for continued research into suicide prevention strategies is undeniable, with high global statistics demonstrating the urgency of this public health issue. In Australia, approximately 3000 people end their lives each year, with those living in rural and regional areas identified as having a higher risk of dying by suicide. Due to decreased access and support services in these areas, community-based suicide prevention initiatives provide opportunities to educate and support local communities. A scoping review was conducted to explore the literature pertaining to such programs in rural and/or regional communities in Australia. This review follows the five-stage Arksey and O’Malley (2005) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Nine databases were searched, from which studies were considered eligible if suicide prevention programs were community-based and catered for adults (age

Chinese Papermaking: A Multicultural and Environmental Education Strategy for Pre-K Teachers

Many scholars see the urgency of implementing multicultural education (ME) and environmental education (EE) in the primary level (Abdullah, 2009; Bower, 1998; Cohen & Horm-Wingerd, 1993; Trubowitz, 1995). The scholars also share how hands-on and art approaches fit well in both Multicultural Education and Environmental Education fields (Adams & Chisholm, 1999; Bower, 1998; Damm, 2006; Seltzer-Kelly, Westwood, & Peña-Guzman, 2010). Chinese papermaking, an interactive and hands-on exercise in the creation of handmade paper, can be a means of integrating concepts of multiculturalism and sustainability into a young child‘s education. To address this issue, this study aimed at (a) introducing multicultural education, sustainability, and Chinese papermaking; (b) creating a new model MATCH to synthesize multicultural education and environmental education; (c) showing how papermaking is a culturally enriching activity; and, (d) demonstrating child-centered papermaking activities

Incorporating climate change into invasive species management: insights from managers

Invasive alien species are likely to interact with climate change, thus necessitating management that proactively addresses both global changes. However, invasive species managers’ concerns about the effects of climate change, the degree to which they incorporate climate change into their management, and what stops them from doing so remain unknown. Therefore, we surveyed natural resource managers addressing invasive species across the U.S. about their priorities, concerns, and management strategies in a changing climate. Of the 211 managers we surveyed, most were very concerned about the influence of climate change on invasive species management, but their organizations were significantly less so. Managers reported that lack of funding and personnel limited their ability to effectively manage invasive species, while lack of information limited their consideration of climate change in decision-making. Additionally, managers prioritized research that identifies range-shifting invasive species and native communities resilient to invasions and climate change. Managers also reported that this information would be most effectively communicated through conversations, research summaries, and meetings/symposia. Despite the need for more information, 65% of managers incorporate climate change into their invasive species management through strategic planning, preventative management, changing treatment and control, and increasing education and outreach. These results show the potential for incorporating climate change into management, but also highlight a clear and pressing need for more targeted research, accessible science communication, and two-way dialogue between researchers and managers focused on invasive species and climate change