Stander Symposium Projects

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  Analysis of the spermtail axoneme following a substitution of Drosophila melanogaster beta 2-tubulin with Anopheles gambiae beta 2-tubulin: functional or not?

  Christian R Jensen

  How does a protein evolve while maintaining function? Nature is constantly flowing like a raging river; the consistent flow does not readily allow for a pause to chart a course through the dangerous waters. Much like navigating violent waters, nature must take a specific narrow path when making changes in the genetic code; one misstep can result in a loss of function. Our model focuses on the beta 2-tubulin found in Drosophila melanogaster; past research has demonstrated that beta 2-tubulin has a major role in the formation of a functional 9+2 spermtail axoneme. Through phylogenetic analysis it has been determined that the D. melanogaster beta 2-tubulin sequence has not been altered for at least 110 million years; this is highly unusual in the scope of nature. Although there have been no recent changes in the Melanogaster sequence, there are marked changes in the beta 2-tublin sequences among Melanogaster’s close relatives. Anopheles gambiae and Melanogaster shared a common ancestor around 220 million years ago, however there are 40 amino acid differences between the two beta 2-tubulin sequences. This proposal aims to create a transgenic organism; the Melanogaster beta-2 will be replaced with the Anopheles beta-2. If the resulting spermtail is functional, it will show that the 40 changes in the Anopheles sequence followed a specific, precise path that allows it to remain functional within the Melanogaster domain. However, it is possible that the substitution will result in the spermtail axoneme being compromised and a loss of spermtail function. This would show that there has been a significant evolutionary event since the divergence 220 million years ago; this event effectively prevents further adaptive changes from occurring in the Melanogaster beta-2 sequence.

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  An Analysis of Challenges and Solutions Facing Fraternity and Sorority Advising Programs

  Keri L Good

  Fraternity and sorority advising programs (FSAP) characterize the administrative staff employed at a college or university who provide support to Greek letter organizations. They serve as a liaison between the student and adviser leadership of the organizations, the national organization, and the institution. Four overarching challenges to professionals working in FSAP are facilitating a culture of diversity and multiculturalism, autonomy of chapters and national organizations, scrutiny from non-Greek constituents, and Greek members exhibiting unethical behavior (Whipple, 1998). Specific solutions for each of these challenges recommended to FSAP professionals are rooted in fostering self-authorship in members that is necessary to change campus culture.

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  An Analysis of International Adoption in Relation to Nationalist Sentiment

  Victoria S Szczechowski

  My thesis project seeks to answer the question: Does the level of nationalist sentiment expressed by citizens of a country affect the restrictiveness of the country’s international adoption policy and the number of children adopted out? Current literature has examined the influence of the level of nationalism expressed in a country on adoptive parents in choosing from which country to adopt; however, no study has examined the link between nationalism and country-specific intercountry adoption policy. The variable of nationalist sentiment warrants study, for the Hague Convention posits that intercountry adoption is a valid option only if “a suitable family cannot be found in his or her [the adoptable child’s] State of origin” in order to preserve the child’s nationality of birth (Varnis, 2001: 42). This statement implies that domestic adoption is considered to be in the better interest of the child versus intercountry adoption. In addition to the fact that “nationalists might subscribe to the view that children ‘belong’ to their countries of birth and are better off growing up there (Leblang et al, 2015),” countries may be reluctant to act as sending countries in intercountry adoption because adopting out their children indicates an inability of the country to care for its children and thus “injures its national pride (Varnis, 2001).” Although current literature somewhat addresses nationalist sentiment in terms of its affect on intercountry adoption, no study has empirically examined the potential link between nationalist sentiment and actual adoption policy restrictiveness; therefore, my project analyzes this potential link.

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  An Ecological Assessment of an Urban Stream Corridor and the Impact of Low Dam Removals.

  Amanda Elizabeth Angelucci, Caitlin Michele Buchheim, Catherine J Devitt, Claire T Kaminski

  This study was undertaken to understand the effects of low dam removal on the biodiversity in the Great Miami River. Samples of fish and macroinvertebrates were collected both above and below two different low dam sites, Monument Avenue and Tait Station. Fish samples were collected using boat-electroshocking and bank-electroshocking and an Index of Biotic Integrity (IBI) was calculated with the data. Samples of macroinvertebrates were obtained using artificial substrate samplers, kick nets, and sweep nets and used to calculate the Macroinvertebrate Aggregated Index for Streams (MAIS) at each sampling site. Physical characteristics of the stream channel, riparian zone and floodplain were quantified with a habitat evaluation index. Hand-held meters were used for measuring pH, conductivity, temperature, TDS, and dissolved oxygen and the float method was used to measure surface water velocity.

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  An Investigation of Supercapacitor Design with Specific Emphasis on Energy Density

  George E Padavick

  Imagine charging your phone in minutes rather than hours. With supercapacitor technology this could become a reality. Supercapacitors offer an alternative to batteries in that they store electrical energy but provide faster charging and discharging. However, commercial supercapacitors store less energy than batteries, resulting in the widespread prevalence of batteries over supercapacitors. Recent developments in advanced carbon materials have improved the energy density of supercapacitors suggesting that further improvements can be made. This work aims to build on materials developments to provide better energy storage systems specifically by increasing the energy density of supercapacitors. Applications include electric vehicles, smart grid technology, renewable energy, and your smartphone.

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  Application of a GUS reporter system to establish hly transcription in response to oxygen and propionate.

  Erica Rinehart

  Listeria monocytogenes (LM) is a foodborne pathogen that causes listeriosis through production of the toxin listeriolysin O (LLO). In healthy individuals, the symptoms of listeriosis are minimal; however, severe illness can occur in pregnant women, immunocompromised patients, and the elderly. The Center of Disease Control and Prevention (CDC) has implicated LM to be responsible for 19% of the deaths related to foodborne pathogens. Every year 1,600 people become infected with LM and are hospitalized in the United States and 1in 5 patients do not survive. Due to these statistics, it is important to understand LM virulence and how it is regulated to ensure that the current food safety standards are effective against this pathogen. Previous work has shown that propionate, a common food preservative that also exists within the human gut, increases LLO production anaerobically with the inverse being true aerobically. Thus, if propionate affects LM pathogenesis, we expect the presence of propionate to affect the transcriptional regulation of the gene hly that encodes the protein LLO. This research verifies that a LM strain with a GUS reporter can be used to examine the effect of propionate on the transcriptional regulation of LLO production. Experiments were performed both aerobically and anaerobically in the presence of varying concentrations of propionate (0mM, 5mM, 15mM and 25mM). The results showed that anaerobically as the concentration of propionate increased the intensity of the fluorescence increased, meaning increasing hly transcription. Aerobically, however, the presence of propionate resulted in a decrease in hly transcription. These results highlight the impact propionate on hly transcription and the role of oxygen in LM response to propionate.

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  Arsenic Removal from Groundwater Using Sustainable Biochar Filters

  George W Debs

  Globally, arsenic is a widespread contaminant that enters the environment from natural geochemical sources and anthropogenic sources. Trivalent arsenic is more toxicologically potent than pentavalent arsenic. Arsenic exposure can result in gastrointestinal illnesses, various types of cancers (skin, bladder, lung, kidney, liver) and death. Arsenic is also linked with skin lesions, cardiovascular disease, neurological effects and diabetes. Although inorganic arsenic is found in soil and water, according to the World Health Organization, arsenic exposure from groundwater presents the greatest hazard to human health. Despite these environmental and public health concerns, there is no sustainable solution for mitigating arsenic contamination of water sources in developing countries such as Chile, Mexico, Bangladesh, Pakistan, India, Bangladesh. This research study investigates the use of biochar, an inexpensive, renewable material, for the removal of arsenic from groundwater. Biochar has been shown to effectively adsorb heavy metals, oxyanions and organic compounds such as chromium, lead, phosphate, atrazine, phenantherine, naphthaline, and 1-naphtol. Since biochar is a material that can be inexpensively produced from various locally-available feedstock materials (agricultural waste, unused biomass, etc.), biochar could sustainably be used to treat waters in countries that do not have access to large scale treatment plants that require reliable, readily available energy and treatment chemicals. This research project seeks to determine the biochar production methods, biochar physicochemical characteristics, and water quality conditions suitable for efficient arsenic removal from groundwater using point-of-use water treatment systems.

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  Assessing Shape Repeatability in Variable Geometry, Polymer Extrusion Dies

  James L Vogel

  Die extrusion is a manufacturing process to create parts with a fixed cross-sectional profile by passing melted plastic through a die of the desired cross-section. The resulting plastic piece then hardens as it is pulled through a water trough and is then cut into pieces with the desired length. Extrusion has significant cost savings over other plastic processing methods. In current technology, the dies have a fixed geometry creating parts with a constant cross-section. The objective of this project is to create a die that can change shape by actuating a lever resulting in a part with variable cross sections. In order to determine the feasibility of variable geometry extrusion, dies have been designed and constructed. The process is tested by the use of a laser scanner that captures data points of the cross sections at multiple locations along the variable extruded part. The data is analyzed by a numerical process to determine the repeatability accuracy by comparing multiple profiles of the same extrusion.

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  Assessing the Effect of Propionate and Oxygen on the Antimicrobial Activity of Nisin

  Andrea M Vietti

  Listeria monocytogenes is one of many common foodborne pathogens that causes infections that are extremely dangerous to individuals, especially to those with compromised immune systems. From a societal standpoint, treatment can cost hundreds to thousands of dollars per patient thus causing a significant strain on public health. The human body, specifically the gastrointestinal lumen, is equipped with an internal chemical barrier that serves to fight off dangerous pathogens such as Listeria. This chemical barrier is composed of antimicrobial peptides that target invading microbes. Alongside these antimicrobial peptides are fermentation acids such as propionate that are produced by endogenous microbes in the human body. Foodborne pathogens are contracted through contaminated food products and in order to reduce this, public health officials incorporate antimicrobial peptides such as nisin to consumer food products. Research geared towards combating foodborne pathogens typically focuses on aerobic conditions; however, Listeria is exposed to anaerobic conditions due to the anoxic environment in the human gastrointestinal tract. The purpose of this study is to understand Listeria’s susceptibility to the fermentation acid propionate and antimicrobial peptide nisin in both aerobic and anaerobic conditions. By treating Listeria to incremental concentrations of both nisin and propionate and exposing the bacteria to both anaerobic and aerobic conditions, Listeria survival can be determined. This research possesses implications for the understanding of combating foodborne pathogens such as Listeria, and research can thus allow public health personnel to reduce the societal burdens of Listeria infection.

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  Automated Particle Swarm Optimization Based PID Tuning for Control of Robotic Arm

  Ouboti Djaneye-Boundjou, Xingsheng Xu

  We revisit the Proportional-Integral-Derivative (PID) controller design for torque control of robotic manipulators, for which, appropriate tuning of the said controller could prove very burdensome, especially with increasing degrees-of-freedom (DOF) and/or when designing a Multi- Input Multi-Output (MIMO) PID controller. That is, when generating and tuning matrix P-I-D gains as opposed to single values, in order to take in account possible coupling effects between involved joints. We tackle both joint space and workspace PID control tuning problems for reference tracking from an optimization standpoint. Using a previously developed stable Adaptive Particle Swarm Optimizer, we are able to automatically and systematically tune P-I-D gains, be it as single gain values or gain matrices, while optimizing a cost or fitness function. The aforesaid cost function can be arranged to feature various aggregated performance measures, ‘normalized’ so as to overcome differences in scale if any. Taking in account some practical limitations, a 2-DOF arm is used here as a case study. Numerical simulations are provided to substantiate the adequacy of our method.

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  Automatic Intrusion Detection on Oil/Gas Pipeline Right-of-Ways

  Ming Gong

  Pipeline right-of-ways (ROWs) monitoring and safety pre-warning is a vital way to guarantee safe operation of the oil/gas transportation. Any construction equipment or heavy vehicle intrusion is a potential safety hazard to pipeline infrastructure. Since millions of miles of pipes buried along the length and breadth of the United States, monitoring is required to know if pipeline ROW is under threat or not. Taken into account of less population of the vast amount of area, high cost of labor and rapid advancements in sensor technology and automated techniques for image analysis, aerial monitoring is found to be the most viable option. The images captured by aerial data acquisition system, such as fixed-wing air-crafts or unmanned air vehicles are affected by a lot of factors including varying illumination conditions, environmental conditions, camera characteristics, etc. To deal with the above mentioned problems, an automatic intrusion detection system, which is capable of dealing with the constraints of the aerial imagery caused by low resolution, lower frame rate, large variations in illumination, motion blurs, etc., is being developed to assist the threat detection as part of the ROW automated monitoring program. The automated pipeline monitoring system is designed to be in three phases: background elimination, part-based object detection and risk assessment. In the first phase, a region of interest (ROI) detector is developed to extract potential regions that may contain objects by utilizing monogenic phase features into a cascade of pre-trained classifiers. In the second phase, a part-based object detection model is built for searching specific targets, which are considered as threat objects. In the third phase, a safe pre-warning system is built to access the severity of the threats to pipelines by computing the geolocation and temperature information of the threat objects. In addition, in order to assign more precise warning, the impacts caused by different types of vehicles will be taken into account by developing new feature extraction and classification algorithms.

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  Autonomous Surveillance in Real World Environments

  Gayatri Mayukha Behara

  The widespread emergence of human interactive gaming and entertainment systems based on using body gestures for control has led to the development of portable 3D depth perception cameras. Many standalone systems capable of 3D depth perception are now commercially available. Examples of such systems include Kinect motion sensing input device developed by Microsoft for Xbox 360 and Xbox One video game consoles, Creative Labs Senz3D, and ZED camera from Stereolabs which has combined a 3D Camera for depth sensing with motion tracking. In the current work, we aim to expand the functionality of such systems by combining autonomous object recognition along with depth perception which would provide the ability to both identify the object and its distance from the camera. Such capability would prove invaluable to autonomous surveillance applications, where persons carrying any forbidden and dangerous objects are detected in real-time and appropriate warnings are signaled. We have selected Microsoft Kinect V2 which includes built-in hardware algorithms to identify humans in a complex real-world setting. In addition, the system can simultaneously track 6 people at any time and provide their skeletal joint diagrams. The current work deals with using the skeletal joint diagrams and depth maps and create a focus area around the hand area of the peoples. The next phase of our developed algorithm deals with object detection after the segmentation of hands. We use machine learning techniques with establishment of training datasets that includes the library of objects we aim to detect. Finally, we believe his system could have uses in autonomous navigation of robots, vehicles and drones.

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  Behind the Stigma: An Examination of the Impact of Gender and College Adjustment on Attitudes Towards Mental Health Disorders

  Maggie L Inman

  The topic of stigmatization of mental health disorders and use of psychological services has been widely researched. Gender differences have been found in attitudes regarding acceptability and treatment of mental health disorders, with adherence to gender roles influencing these attitudes. Past research has confined gender to a binary model of self-report and has not explored the concept of nontraditional gender roles; nor has it examined the influence of social factors, namely college adjustment, on perceptions of mental health. With many studies utilizing undergraduate students, it is important to understand how college adjustment may affect attitudes toward mental health. This study tested three hypotheses: that men and women with more feminine gender roles will display more accepting attitudes toward individuals with mental health disorders, that men and women with poorer college adjustment will also display more accepting attitudes toward these individuals, and that the relationship between college adjustment and attitudes towards mental disorders will be moderated by gender role traits. Participants were PSY 101 students and received research credit for their participation. Correlations and regression analyses were used to compare responses between groups based on gender role traits and college adjustment. Results indicated no significant relationship between gender roles and attitudes towards mental disorders, but a significant relationship was found between college adjustment and these attitudes, with poorer college adjustment predicting more negative attitudes towards mental disorders. The study also found that gender role traits strengthen this relationship between college adjustment and attitudes towards mental disorders. Results of this study could help reduce mental disorder stigma by identifying which factors contribute to the stigmatization. The results could also help university counseling centers to normalize mental disorders and psychological services by using advertising to target the least accepting demographic.

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  Beyond the Macro: Determining the role of micronutrients in orthopteran communities

  Lucy E Bratton, Kaitlin M Gawkins

  Insect herbivores, such as grasshoppers, are important components of grassland ecosystems, but presently we cannot accurately predict their abundance and diversity. Macronutrients (i.e., nitrogen and phosphorus) have long been considered to be important in limiting herbivore populations, but only nitrogen and phosphorus have been examined, thus overlooking a potential role for micronutrients. We are conducting a large-scale fertilization experiment manipulating micronutrients (Ca, K, and Na) and macronutrients (N and P) to determine how micronutrients affect orthopteran communities in coastal tallgrass prairies of Texas with a large, and whether the effect of micronutrients depends on the abundance of macronutrients. We found that, contrary to previous thinking, orthopterans were not limited by macronutrients, but were limited by individual micronutrients. A species of grasshopper (Melanoplus bispinosus) and multiple species of katydid (Orchelimum concinnum and Orchelimum vulgare) were particularly responsive. This summer, we will be conducting different types of feeding trials with these species to determine whether their responses are due to direct effects (i.e. via physiological mechanisms) or indirect effects (via changes in plant communities). These results would not only help to explain the mechanisms underlying of this large-scale experiment, but also, would give more insight into the relationship between direct and indirect influences of changing micronutrient concentration, thus setting a framework for further study in the future. These results have important implications for the management of rangeland ecosystems where orthopterans are highly managed pest species.

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  Bicycle Safety Project

  Theus H Aspiras, Brandon M Hampshire

  The objective of the Bicycle Safety Project is to provide joggers and cyclist a sensor that can alert them of approaching dangers behind them. The dangers could be a mugger, a speeding cyclist, or approaching vehicle. The project initially approached the objective by using a camera to perform 2D image analysis such as optical flow and distance estimation. Optical flow was used for object detection and speed estimation. In addition to optical flow, the use of a 3D stereo cameras is used for object detection, distance calculation, and speed estimation. In order to detect an object approaching the camera, the 3D stereo camera initially creates a point cloud to use as a distance reference. Then the point cloud collected afterwards is subtracted from the reference point cloud and then changes the reference to the new point cloud. The difference between the point clouds creates an impression that can illustrate moving objects similar to a pinscreen. The image is used to identify objects by using image segmentation. Image segmentation creates a binary filter that allows us to find the average distance and instantaneous velocity of the identified objects. From there, above desired speeds and their objects can be red flagged as dangers. The algorithm is able to calculate and identify objects in under a second when there is a single approaching object.

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  Biomass Production of Basic Garden Plants Growing in Simulated Martian Soil

  Amber R Delvento, Tessa L Farthing, Shelby Krumpelman, Ana D Ritz, Sophie F Yurczyk

  Future manned missions to Mars will require that astronauts grow at least some of the food that they will eat. This project was initiated by an interest in a recent film, The Martian, in which a marooned astronaut grows potatoes in Martian soil to supplement his diet. Robotic spacecraft have been sent to Mars and have analyzed the Martian soil. Comparable soils similar to Martian soils have been found on Earth. We obtained a Martian Regolith Simulant from Orbit Tech, Inc., a subcontractor for NASA. Martian soil contains all micro and macronutrients essential to sustain plant life. Using a climate controlled environment chamber, seeds of radishes, peas, and lettuce were grown in Earth garden soil or simulant Martian soil. Eight seedlings of each species, four of which were planted in earth topsoil, and four of which were planted in Martian soil. A balanced liquid fertilizer was applied to half of the plants. At the end of eight weeks, the biomass of targeted edible biomass was measured. The results will be useful in determining the possibility of growing food on Mars.

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  Boosted Ringlet Features for Visual Object Tracking

  Almabrok Essa Essa, Evan W Krieger

  Accurate and efficient object tracking is an important aspect in security and surveillance applications. Many challenges exist in visual object tracking including scale change, object distortion, lighting change, and occlusion. The combination of structural target information including edge features with the intensity or color features will allow for more robust object tracking in these conditions. To achieve this, we propose a feature extraction method that utilizes both the Frei-Chen edge detector and Gaussian ringlet feature mapping. Frei-Chen edge detector extracts edge, line, and mean features that can be combined to create an edge detection image. The edge detection image will then be used to represent the structural features of the target. Gaussian ringlet feature mapping is used to obtain rotational invariant features that are robust to target and viewpoint rotation. These aspects are combined to create an efficient and robust tracking scheme. The proposed method also includes occlusion and scale handling components. The proposed scheme is evaluated against state-of-the-art feature tracking methods using both temporal and spatial robustness metrics on the Visual Object Tracking 2014 database.

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  Boots to Books: The Transition Experiences of Student Veterans from Camouflage to College

  Jamie A McCall

  Since the passing of the Post 9/11 benefit for veterans who served on or after September 11, 2001, colleges and universities are now faced with increasing veteran populations. According to the National Conference of State Legislatures (2014), there are over one million veterans and their dependents that are utilizing benefits from the Post 9/11 G.I. Bill to pursue college. Beyond the financial benefit, many student veterans are in need of additional academic, career, counseling, and social resources in order to provide a more positive and successful transition to college campuses that are predominantly catered to traditional students. While the majority of student veterans tend to be non-traditional students, colleges and universities can strengthen their community and inclusiveness by understanding the needs and experiences of their student veterans. The purpose of this research study is to understand the experiences and needs of student veterans transitioning from a military culture to a private Catholic, Marianist campus at the University of Dayton. By understanding the qualitative narrative stories of six non-traditional student veterans who balance work, family, and college responsibilities, further training and resources can be implemented to provide a more positive, supportive, and inclusive transition into the campus community.

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  Business Cycle Patterns, Portfolio Weighting, and S&P Industrial Stock Returns: An Empirical Analysis 2006-2016

  Nicholas C Jacobs

  In this study, I explain the returns of Industrial sector stocks during a period where both a downturn phase and a rebound phase in the U.S. economy occur. Using the profitability factor ROE, I test the hypothesis that a concentrated portfolio of ROE weighted Industrial sector stocks outperforms the S&P SPDR ETF (XLI) as well as SPY, the S&P 500 SPDR ETF. In addition, I use a stock weighting scheme based on the standard deviation of individual stocks and assume both "risk on" and "risk off" market conditions operate throughout the time period.

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  Camera pose estimation for 3D scene reconstruction based key frame extraction

  Almabrok Essa Essa, Ruixu Liu

  Estimation of camera pose is a fundamental problem in many computer vision areas, such as simultaneous localization and mapping, robot navigation, 3D scene reconstruction, etc. Recently, using low-cost RGB-D camera to perform 3D scene reconstruction is an active area of mobile robotics research. The ability to localize a camera moving is a very important step. To estimate the camera trajectory, we need to compute the geometry relationship between a set of images. Regardless of which 3D reconstruction algorithm is used for an application, the quality of the results depends heavily on the quality and consistency of the input image sequence, which are required to approximately cover the entire scene and at the same time minimize the content redundancy between the selected frames. Therefore, we introduce the use of a key-frame selection strategy as a preprocessing technique, which not only greatly saves the computation time, but also helps significantly reduce the number of repeated features to improve the camera pose estimation quality. The key frame selection strategy that has been used in this research utilizes the pixel intensity differences among subsequent frames to automatically select only the frames that contain the desired contextual information and discard the rest of the insignificant frames. Our pose estimation for 3D reconstruction system has been applied successfully to video from handheld RGB-D camera and a RGB-D camera mounted on a ground robot. The performance of the proposed technique is observed to be significantly improved using our key frame selection strategy.

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  Characterization of Refractive Index for Potassium Terbium Fluoride

  John D Kunkel

  Potassium Terbium Fluoride (KTF) has the potential for application as an effective optical isolator. It would be valuable for use in high-power laser systems to prevent reflected beams from coupling back into the pump laser. Characterization of the material, including the dependence of the refractive index on wavelength and temperature, are important for incorporating KTF into these laser systems. The method of minimum deviation was used to measure the refractive index for wavelengths ranging from 0.400 to 5.20 microns and in temperatures ranging from 20 to 225°C. Results of this characterization will be presented.

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  Characterizing the Interaction of Mytilus edulis Foot Protein-5 with HY80 Steel

  Brooke N Bennett

  Mytilus edulis foot protein-5 (Mefp-5), an adhesive protein found in the adhesive plaque of the common blue mussel Mytilus edulis (L), contains high amounts of amino acids L-3,4-dihydroxyphenylalanine (L-dopa, 27 mol%) and lysine (20 mol%). While Mefp-5 has been shown to provide significant corrosion inhibition to a high strength low alloy steel (HY80), the mechanism of inhibition remains elusive. It has been suggested that the close proximity of L-dopa and lysine in Mefp-5 results in a synergy that plays a vital role in the adsorption of the protein to solid substrates. This proposed synergy and its effect on iron oxide films has yet to be elucidated. To characterize how Mefp-5 interacts with the HY80 steel, a variety of analytical spectroscopy techniques were implemented. Solutions of Mefp-5, L-dopa, or lysine dissolved in deionized water, 5% acetic acid, 0.05 M potassium phosphate buffer (pH 5.5), or the same buffer containing mushroom tyrosinase were adsorbed onto HY80 and glass substrates. Raman spectroscopy suggests that adsorbate, solution composition and pH play a role in the type of iron oxide formed and how the protein orients itself on the HY80 surface. At a pH of 5.5, the isoelectric point (pI) of the Fe2O3 oxide suggests the negatively charged oxide surface attracts lysine’s positively charged ε-amine group. Infrared spectroscopy indicates that L-dopa is also intimately involved in the adsorption of the protein on HY80 steel. Overall, the data suggests there is synergy between L-dopa and lysine, where lysine aids in iron availability for L-dopa complexation.

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  Chemotherapy: What Does That Even Mean?

  Austin E Hillman, Kaitlin Leigh Restrepo, Jennifer H Sebell

  In an effort to acknowledge the importance of health literacy and respond to a health information need, the purpose of this project was to make an article explaining chemotherapy accessible to Intensive English Program (IEP) students with a third or fourth grade reading level. We revised an existing webpage from Cancer Treatment Centers of America about chemotherapy to make it more accessible for the IEP students. The original web page had a reading level of grade 14 and 7 months (14.7), and the intended audience is patients or loved ones of patients who do not know much about chemotherapy. The methods employed by our team to simplify the inaccessible article included SMOG tests and a Health Literacy Load Analysis to assess the reading level, visits to an IEP class for feedback, and creating/editing a brochure. The final brochure that was formed through these methods had a reading level of grade 5 and 9 months (5.9), which was more than half of the reading level of the original article (which was 14.7). The brochure enabled IEP students to understand need-to-know information about chemotherapy from the original health document. From our results, there is evidence that taking the time to assess the readability of a health document can facilitate informed health decisions by individuals whose first language is not English.

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  Climate Change in Dayton, Ohio: Identifying the Impacts and the Community's Understanding

  Emily E Skill

  This project examines the local impacts of climate change on the City of Dayton and analyzes what citizens from some of Dayton’s neighborhoods understand about climate change and sustainable behaviors. The purpose of this project is to connect threats of climate change in Dayton with sustainable actions that can be performed at home to reduce the effects of climate change. This project addresses the common misconception that climate change will only affect cities with elevations near sea level. While mainland cities, such as Dayton, are not at risk of flooding from rising sea levels, changes in precipitation and temperature can still pose great economic and social threats to these cities. Climate change will increase the amount of precipitation Ohio receives as well as flood frequency. The projected increased temperatures for Ohio will increase the likelihood of heat- rashes, heat-exhaustion, heatstroke, and even death. Increased temperatures from climate change will largely affect the poor, and in the City of Dayton, approximately 35% of population are living in poverty. Furthermore, the City of Dayton is identified as the largest food desert in the state. In addition to many of the problems climate change has on human health, temperature fluctuations and precipitation changes are also threats to agriculture, which will exacerbate food insecurities in Dayton. The survey portion of this project will identify knowledge gaps about climate change and its effects on the Dayton area as well as distinguish awareness of sustainable behaviors so that environmental education programs can be designed to address the needs of the community. This project was developed with the intention of being used as a starting point to help Dayton become a more sustainable city with sustainable citizens.

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  CNN Based HAPNet for Deep Learning

  Patrick K Martell

  Neural Networks have become increasingly popular in recent years due to their ability to accurately classify images in complex tasks. This began with AlexNet in 2012, which led to better performing networks such as GoogLeNet, and ResNet. The network architecture used in this work is the nonlinear line attractor (NLA) network. The method we use will utilize a polynomial weighting method rather than a linear weighting method. The architecture was also improved with a Gaussian weighting scheme, which provides a modularity in the architecture and reduces redundancy in the network. The polynomial weighting scheme improves the network on the tested datasets and yielded better convergence characteristics, quicker training times, and improved recognition rates than the linear counterpart. These changes led to a polynomial network which modifies the NLA architecture to include different ways to use polynomial weighting. In each layer, we can have orders of each input connected by a weight set, which can be trained by a backpropagation algorithm. While this network performed very well, we believe that there is still room for improvement. The previous method performs near the top of it's class, though does not perform better than the best deep learning networks for the MNIST database. By combining the polynomial network and region based approach with the current state of the art techniques for deep learning based methods, we believe that the combination will outperform the regular the polynomial based networks, regardless of polynomial order and region based connections. This expected increase will come from the ability for the polynomial method to further augment the ability of deep learning networks to understand the space. This accuracy increase will most likely also come at the cost of complexity and training time, as this is usually an accepted cost for the use of deep learning networks.