TTU Published Journals @ Volpe Library
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Riparian Wetland Nitrate Retention is Influenced by both Floodwater Nitrate Concentration and Inundation Time
No full textNitrate is the most common form of nitrogen pollution in agricultural rivers. Excess nitrogen can cause harmful algal blooms and low oxygen levels in aquatic environments. Riparian wetlands in agricultural watersheds can be very efficient at removing nutrients before they reach streams and restoring agricultural wetlands for improving water quality has become a major focus of the USDA Natural Resource Conservation Service Wetlands Reserve Program (WRP). Our objective was to gain more understanding of how nitrogen concentration in flood waters impacts nitrogen uptake rates across different restoration types implemented by the USDA to restore these agricultural wetlands in the WRP. We collected 60 soil cores across four restoration types in a west Tennessee wetland. Cores were incubated in a continuous flow-through setup for 48 hours at 24°C with synthetic lab water, with 5 individual water sources of differing nitrate concentrations (0.1, 0.5, 1.0, 5.0, 10.0 mg/L). Each restorative type had 15 cores total, split up into 3 cores per nitrogen concentration. Results show that nitrate uptake varied over time with soil generally releasing nitrate initially and retaining nitrate after 24 hours. As well as nitrate uptake rates increased with more nitrate availability in all habitats. Wetlands can potentially be a source of nitrate when they are initially flooded but become nitrate sinks with a longer water residence time
The correlation between adverse childhood experiences and children's behavior
No full textThis project focused on the correlation between adverse childhood experiences (ACEs) in elementary age children and their exhibited behaviors. The problem is there are negative behaviors evident in elementary aged children who have experienced ACEs. The purpose of this project is to explore the correlation between ACEs and children's behavior. The databases searched for articles for use in this project were Google Scholar and Tennessee Tech University's Volpe library. The keywords used were child maltreatment, childhood trauma, and behavior. The inclusion of articles was based on the relevance to the topic. The participants in the reviewed studies were school aged children and adults. The three most important findings were 1. struggles with attention, learning, emotion, and memory affect emotional regulation in children, 2. different forms of childhood maltreatment have behavioral effects, and 3. children who have experienced ACEs suffer long-term effects. These results connect to the purpose of this study because they show there is a correlation between ACEs and children's psychiatric health and behaviors. The results outlined above support the notion that children who have experienced ACEs are affected both academically and mentally. Having such experiences also affect children's attention, emotions, memory, and behaviors. A child's mental state influences the way a child behaves within their environments and these effects may be long term
Should Retailers Choose to Use Sustainable Packaging to Reduce their Carbon Footprint?
No full textPlastic packaging includes advantages such as durability, water resistance, insulation, affordability, convenience, and shelf stability (Soares et al., 2021). However, plastic can end up in landfills, plastic substances can transfer into the food, and toxic gasses are released when creating the plastic packaging (Acquavia et al., 2021). The production of single-use plastic by retailers shows various environmental concerns and also proves to be deleterious to our health, in addition to being responsible for a large amount of plastic pollution. The food industry contributes to this problem greatly, since many of these items come in single-use containers or wrappers (Herrmann et al., 2022). For instance, one plastic bag takes ten thousand years to biodegrade (Johnson, 2019), and the damage caused by pollutants and climate change are permanent (Bauermeister, 2021). There are much more environmentally friendly materials that can be used such as cornstarch or mushrooms (Johnson, 2019). This research aims to determine if large retailers, such as Aldi, Trader Joe's, and Walmart, should choose to use sustainable packaging to reduce their carbon footprint
Knowledge, Perceptions, and Attitudes of AGRN 1110 Students on GM (Genetically Modified) Crops: A Survey
No full textPrior research indicates that college students are motivated to buy organic food based on their interests rather than perceived environmental or worker benefits. The underlying motivations showed discontinuity of knowledge of the benefits and reality of genetically modified (GM) crops. Therefore, we seek to determine AGRN 1110 (Plant Science Laboratory) students' knowledge, perceptions, and attitudes towards GM crops. Plant science students (n = 37) were asked to complete a survey that included the following constructs: knowledge of GM crops, purchasing habits, and personal value. The survey was distributed before and again after a GM crops unit. Preliminary results indicate that 70% believe that a GM organism is produced through genetic modification, 62.5% were unsure if GM products affected their overall health, 57.5% were unsure if GM affected the environment, 45% were unsure if GM should be given as feed to animals, and 70% believed that GM reduced pesticide use. Additionally, 78% did not seek non-GM labels, 38% were unsure if non-GM organic foods were healthier for consumption, 48% did not believe that non-GM organic fruits and vegetables taste better, and 60% had no preference if their food was non-GM or GM. Results from this study can aid educators in understanding the lacking area of knowledge surrounding GM products and understand the personal intrinsic values of collegiate students to address this controversial topic in course content
*WINNER* Predicting unknown upstream events using Convolutional Neural Network
No full textConvolutional Neural Network (CNN) is a tool that one can use to deduce information about unknown upstream events in fluid dynamics. We applied an existing CNN, GoogLeNet, to predict the shape of upstream obstacles disturbing the flow using the information collected downstream. Flow over six two-dimensional geometries was simulated to collect data needed for training the model. The geometries included a triangle, square, pentagon, hexagon, heptagon, and octagon. The input of the CNN model was the absolute values of the continuous wavelet transform (CWT) of velocity signals recorded in near, middle, and far wake regions downstream of the studied cases. CWT transforms velocity signals into functions of time and frequency called scalograms. These scalograms were then used to train the model. This study used 420 signals (either in the near, middle, or far wake region). Then, ten random signals that did not participate in the training (hence were unknown to the trained model) were employed to evaluate the model's performance. The model successfully predicted the shape of each geometry in each unknown case
*WINNER* Fatigue Analysis of Carbon Fibre Reinforced Composite Components Manufactured by Fused Filament Fabrication
No full textThe development of fiber composites in recent years has been remarkably strong, owing to their high performance and durability. The fatigue behavior of components is an important knowledge, as cyclic loading is a common feature of most engineering applications. The scope of this paper is to present the fatigue properties of carbon fiber-reinforcing Polyethylene terephthalate glycol (CF-PETG) components manufactured by FFF with a focus on different printing orientation. Simplify 3D and stacker S2 are used to slice and to manufacture the components respectively. The printing orientation and direction used are XY-00, XY 450, XY 900 and YZ 900. Fatigue testing is carried on 70% of Ultimate Tensile Strength (UTS). Analysis of Variance (ANOVA) is used to analyze the data obtained from the fatigue test
A New Histogram-based Visualization Tool for Analyzing Anomaly Detection Algorithm Performance
No full textPerformance visualization of anomaly detection algorithms is an essential aspect of anomaly and intrusion detection systems. It allows analysts to highlight trends and outliers in anomaly detection models results to gain intuitive understanding of detection models. This work presents a new way of visualizing anomaly detection algorithm results using a histogram. The approach presented in this work provides a better understanding of detection algorithms performance by revealing the exact proportions of true positives, true negatives, false positives, and false negatives of detection algorithms. The histogram-based approach was used to visualize the prediction confidence and performances of anomaly detection algorithms on multiple datasets to provide insights into the strengths and weaknesses of these algorithms on different aspects of the datasets. The proposed approach is compared with previous histogram-based visualization methods that rely on only positive and negative anomaly scores. The results show that the proposed method provides a better meaning of detection algorithms performances. Finally, this work presents further results that show how the proposed method can be applied to performance visualization and analysis of supervised machine learning techniques involving binary classification of imbalanced datasets
*WINNER* Novel Conservative Reversible Logic Gate Logic Function Implementations with Minimal Garbage
No full textConservative and reversible logic gates are widely known to be compatible with and exhibit great efficiency on revolutionary computing paradigms such as low power, optical, and quantum computing. The fundamental conservative reversible logic (CRL) gate is the Fredkin gate. Functionally complete, Fredkin gates can implement any digital logic function, including those commonly used in classical computing. While some researchers have used the Fredkin gate to build assorted logic functions, this work describes a systematic study to discover efficient implementations of all two-input and the most common three-input logic functions using both the Fredkin gate and CRL gates of size 4. The results of this study have been observed to have useful results in implementing more than one single primitive logic function in their outputs for specific CRL gate implementations. The garbage outputs that are observed to be useful primitive logic functions will allow for minimized gate counts in the design of a system
Optimization of Bacterial Cell Culturing by Multiphysics Modeling
No full textBacteria are often used as host cells for the propagation of plasmid DNA and recombinant proteins for applications in bioprocess, biomedical, and genetic engineering and biochemistry. To ensure that only bacteria of interest are growing, the solid media (i.e., agar) is sterilized at 121°C and prepared in the presence of specific quantities of particular antibiotics during cooling. The cooled temperature at which the antibiotic is added to the media is crucial due to the propensity of thermal degradation. Typical approaches to addressing this issue fail to incorporate cooling environments, and direct measurement can pose contamination risks. A time dependent study of the heat transfer from sterilized media in the heated vessel to the environment has been conducted in COMSOL Multiphysics, coupling the kinetics of the thermal degradation of ampicillin or penicillin to viable antibiotic concentration. In effect, an optimal time to add the antibiotic is predicted. The vessel used to prepare agar is modeled as a beaker, and temperatures are predicted as the simulated agar cools to room temperature after which an average volume temperature and the final expected concentration of viable antibiotics over time are determined. The ease of determining accurate cooling times for agar preparation will allow for more precise concentrations of antibiotic in the agar, thus allowing for better experimental control in the quality and yield of product obtained from cell/bacteria cultures
Preservice Mathematics Teachers' Perspectives of Mathematics Tasks during a Mathematical Letter Writing Exchange
No full textThe author interviewed participants individually and conducted a focus group interview with three preservice mathematics teachers (PSMTs) attending a southern university in this interpretive case study. The author also gathered the PSMTs' final reflection papers related to a mathematical letter writing exchange (MLWE) in which they participated. The research questions were: What were the PSMTs' perceptions of value after participating in a MLWE with high school students? How did PSMTs' thinking about the qualities of a good mathematical task evolve as they participated in a MLWE? For this study, the author used open coding and inductively analyzed the interviews. In comparison, directed content analysis guided analysis of the papers, letters, and mathematical tasks to determine the PSMTs' perceived value of the MLWE experience. PSMTs should form strong relationships with students to help build students' confidence in doing mathematics. Also, explicit and implicit structures existed in the descriptions of a good mathematical task. For example, the participants reported they needed to find or create mathematical tasks that matched their penpals' interests. Additionally, one intrinsic theme indicated that preservice teachers should consistently prioritize mathematics in their feedback and discussions with students. Finally, the findings built off of prior literature surrounding MLWEs. This will help future PSMTs become more successful in their future teaching practices