The process of successful skin healing from a wound involves different combinations of interactions. Moreover, by clearly understanding this process, we can provide and determine the appropriate amount of medicine to give to patients with varying types of wounds. Thus, this can improve the healing process of patients. In this research, we use the ADI method to solve a partial differential equation that models wound healing and also determine the necessary parameters to achieve the stability of the ADI method. The data, which we are using, are pictures of the wounds, and the task is finding the initial conditions, that is exact boundary data from photos. We believe that Deep Learning is an excellent method to deal with this segmentation problem.

A group is a mathematical construct that represents the symmetries of an object. These symmetries transform the object through what is called a group action. Graphs—Cayley graphs, in particular—provide a rich source of symmetries for forming groups. A graph and its group action can be modeled by a collection of infinite matrices known as a C*-algebra. In a paper in the Journal of Functional Analysis, Gábor Elek used dynamical systems called Uniformly Recurrent Subgroups (URS) to construct a new type of C*-algebra. We further develop understanding of these C*-algebras using tools from other areas of operator theory. In particular, comparisons with the well-known crossed-product construction have proven useful.

Background: A relationship exists between perception of one’s health based on weight, and how they manage their health. Normal-weight college students who physically appear healthy may unknowingly develop a chronic disease because they view good physical appearance as verification of good health.
Objective: The purpose of this study was twofold: 1) compare the perceived health status of TCU students to their actual health status; and 2) assess the health status of TCU students of normal BMI.
Design: This study was a cross-sectional, descriptive design.
Methods: Twenty-five normal-weight college students between ages 18-24 of any sex and race were recruited to complete a health perception assessment survey 24 hours prior to their lab visit. Participant’s anthropometric measurements (height, weight, body fat percentage, waist/hip circumference, and waist-hip ratio), blood pressure, fasting blood glucose (via finger prick) and a 10mL blood sample were collected. Blood was analyzed for hemoglobin A1c and a lipid panel. Self-reported survey results were compared with results obtained during the study visit to identify any discrepancies between actual and perceived health status and evaluate the overall health status of participants.
Results: Average BMI and waist-hip ratio of participants were 22.39±1.94 and 0.76±0.04, respectively. The most commonly elevated measured values were fasting blood glucose (29% prevalence), and body fat percentage, blood pressure, and LDL cholesterol (21% prevalence each). Fifty-two percent of participants presented with at least one measured value outside normal limits and 29% presented with two or more values outside normal limits. However, 92% described themselves as “very healthy”, “healthy”, or “somewhat healthy”.
Conclusion: Despite the appearance and perception of health, a significant proportion of TCU students ages 18-24 may risk developing a chronic disease. Our results suggest that regardless of self-perceived health status, TCU students should receive regular check-ups to identify and manage physiological markers of health.

Background: Intermittent fasting has become a dietary trend, as it is reportedly attributed to weight loss, maintenance of body composition, appetite control, improved sleep patterns, and disease prevention. However, current evidence-based research may not fully support these claims. There are discrepancies regarding the definition of intermittent fasting. Additionally, it is commonly confused with traditional fasting.
Objective: The objective of the study was to determine perceptions of intermittent fasting on health in college-aged students and compare to evidence-based findings. It was hypothesized that college students would have an overall positive perception of intermittent fasting based on current popularity of the diet.
Design: Cross-sectional
Methods: An online survey was developed which assessed participants’ knowledge and practice of intermittent fasting.  Participants were recruited via email and social media. Data was analyzed using SPSS. 
Results: Among study participants (N=99), 24.2% (n=22) reported currently or previously following an intermittent fasting diet. There was a positive correlation between reported intermittent fasting and weight loss (p<0.01), as well as increased energy levels (p<0.01).  The majority of participants (63.6%, n=63) defined intermittent fasting as “controlling the times throughout the day in which food/drink can be consumed.” Participants reported obtaining knowledge of intermittent fasting from internet research (50.5%, n=50), social media (46.5%, n= 46), and friends and family (42.4%, n=42).
Conclusions: Overall, participants commonly defined intermittent fasting, with knowledge coming from friends and family, social media, and the internet.  If participants had practiced intermittent fasting, the most significantly reported benefits were weight loss and increased energy levels, which may be attributed to the current study populations’ motives for diet adherence. Further research should be conducted with a more diverse subject population and include data regarding participants’ reported desired outcomes prior to starting the diet in order to determine if additional benefits can be attributed to intermittent fasting.

HOW SOCIAL MEDIA INFLUENCES DIETING AND EATING BEHAVIOR

D. Farmer,1 J. Goodrich, Rylee Lin, A. Vanbeber, PhD, RDN, LD, FAND, L. Dart,
1Department of Nutritional Sciences, Texas Christian University

Learning Outcome: To determine the influence of social media on dieting and eating behaviors among adults living in the United States.

Learning Needs Codes:
Primary:
Secondary:

Background: Social media plays a major role in influencing use of popular fad diets, and searching for diet-related information on social media is becoming more common. Research indicates that 45 million Americans go on a diet each year, and approximately half of all dieters report that their primary information source regarding special diets is the internet.

Design: Un-blinded, randomized trial approved by TCU IRB.

Methods: Participants completed an online SurveyMonkey® research questionnaire after providing informed consent. Population included 333 male (22%) and female (78%) individuals 18->45 years of age. Analyses assessed participants' history of fad dieting and outcomes, likelihood of being influenced by social media recommendations for food product brands, and/or following social media influencers promoting different diets. Data was analyzed using SPSS (P<0.05). Frequency distributions and correlations were analyzed for trends in dieting and eating behaviors and how these are influenced by social media.

Results: Age was the overriding factor in determining influence by social media among participants, with 18-22 year/olds more likely to follow a diet and/or try food product brands recommended by social media influencers (P=.01). Married and older participants vs. single younger participants were more likely to have attempted a weight loss diet but less likely to try a diet promoted by a social media influencer (P=.01). Additionally, regardless of age or marital status, there was a positive correlation between participants who dieted more frequently throughout the year and the likelihood of trying a diet promoted by social media influencers (P=.01).

Discussion/Conclusion: Social media provides registered dietitians/nutritionists with the unique opportunity to market their skills and to educate the public about evidence-based nutrition science.

The metabolic effects of capsaicin on college-aged men: a randomized, double-blind, placebo- controlled, crossover pilot study
J.E. Mertes,1 A.A. Graves,1 I. Marzan, 1 N. Andonie, 1 A.J. Graybeal, MS2, J.L. Willis, PhD, RDN, LD1
1Department of Nutritional Sciences, Texas Christian University
2Department of Kinesiology, Texas Christian University
Background
Capsaicin is the biologically active, spicy flavor profile component of chili peppers that has been recently touted as an anti-obesity agent. However, studies examining the effects of capsaicin on these markers have mixed results.
Objective
The purpose of this pilot study was to examine the effects of consuming a 14-d supply of 500mg/day or either capsaicin supplement versus placebo on: 1) basal metabolic rate (BMR); 2) blood glucose (BG); and 3) anthropometrics in college-aged men with BMI >25kg/m2.
Design
This study utilized a randomized, double-blind, placebo-controlled crossover design.
Methods
Six overweight/obese, sedentary men completed four visits (~45min/visit) over a 45-day intervention period. On visit 1, participants completed anthropometric and BMR measurements and were randomly assigned to either capsaicin or placebo. Participants were provided with a 14d supply of pills, a pill log, and dietary logs to take and complete daily for 14d. On day 15 (V#2), the same testing and measurements occurred. Participants then completed a 14-day washout period. Following the washout period, participants crossed-over and underwent the V#3 (days 30) and V#4 (days 45) where the same procedures as before were followed.
Results
From pre- to post-capsaicin supplementation, there were no significant changes in BMR (1.61±0.49 to 1.80±0.54 kcals/min, ns), BG (102.5±5.9 to 104.0±8.4mg/dL, ns), body weight (96.1±20.1 to 96.4±20.94kgs, ns), or BF% (22.2±9.2 to 22.7±8.6%, ns). Placebos showed no change in these markers (ns).
Conclusions
In overweight/obese college-aged men, supplementation with 500mg of capsaicin or placebo did not differentially affect BMR, BG or body composition. Overall, more research should ensue with a larger sample.
Funding Source: TCU SERC Grant # UG 190315

Background: Dairy-free diets have gained popularity within the United States based off of minimal scientific evidence to support the overall healthfulness of eliminating dairy. There is limited existing research as to factors that influence dairy consumption or how many people adhere to a dairy-restricted diet.
Objective: The objective of this study was to determine public perception of the healthfulness of dairy and consumption patterns. It was hypothesized that due to recent media coverage and dietary trends, dairy products have gained a negative connotation and consumption has decreased.
Methods: An online survey was created to assess participants’ perception of the healthfulness of dairy and consumption trends of dairy and dairy substitutes. Participants age 18-65 were recruited via email and social media. Data was analyzed using SPSS.
Results: Among survey participants (N=213), the majority consume dairy (91%, n=194), with 77% (n=164) stating they consume 1-2 cups daily. There was a significant correlation (p≤0.01) between whether participants consume dairy and how healthy they view dairy products. The majority of respondents believe that dairy is healthy in moderation (70.4%, n=150), though 34.3% (n=73) believe that cow’s milk is nutritionally inferior to milk alternatives. There was a significant correlation (p≤0.01) between current dairy consumption and consumption of dairy during childhood. However, 42.7% (n=91) of participants stated that their preference for dairy has decreased over the past 5 years. Of the participants who had a decreased preference for dairy, their primary reasons were due to personal research (26.3%, n=56) and media influence (15%, n=32).
Conclusions: The majority of respondents reported consumption of dairy products and perceived dairy to be healthy in moderation. However, a large number of participants’ preference for dairy has decreased in recent years due to personal research and media influence. Future research should also include comparison of consumption trends to evidence-based dietary recommendations.

Previous reports show that it is not uncommon for patients to have two viruses at the same time. At the current time, we do not know how to treat co-infections. In order to test the effects of having these concurrent infections, we simulate the two infections using a mathematical model. We use our model to simulate influenza A virus co-infected with respiratory syncytial virus and parainfluenza virus co-infected with human rhinovirus. Using the model, we can estimate the co-duration of the viruses, the individual duration, and the peak virus amount for both viruses, both with and without drug treatment of the infections to figure out the best treatment strategies for co-infections. We find that sometimes treating one infection can lead to the lengthening of the other infection.

Treatment of complex conditions, such as cancer, has been substantially advanced by a field of molecular therapeutics. However, many of these therapies are limited by the dose toxicity and lack the predictive power of tomography-guided approaches. Nanomaterial platforms can address these drawbacks, safely delivering therapeutics, concomitantly imaging their delivery pathways, and presenting sites for targeting agent attachment. Graphene quantum dots (GQDs) possess physical properties that are critical for biomedical applications, including small size (3-5 nm), high quantum yield, low cytotoxicity, and pH-dependent fluorescence emission. Nitrogen doped graphene quantum dots (N-GQDs) are now utilized as a platform for a targeted treatment formulation geared toward cancer therapeutic. Our work utilizes nitrogen-doped GQDs as an emissive platform for covalent attachment of a targeting agent (hyaluronic acid (HA) targeted to the CD44 receptors on several cancer cell types) and oxidative stress-based cancer therapeutic (ferrocene (Fc)). The synthesized multifunctional formulation is characterized and its efficacy evaluated in vitro. Elemental mapping indicates that the purified from reactants synthetic product has an average iron content of 0.64 atomic percent, suggesting the successful attachment of the therapeutic, while FFT analysis of TEM images confirms the crystalline structure of the GQDs. Although GQDs alone yield no cytotoxicity as quantified via the MTT assay up to the maximum imaging concentrations of 1 mg/mL, the Fc-HA-GQD formulation exhibits a higher cytotoxic response in the cancer cells (HeLa) targeted by the HA as opposed to healthy ones (HEK-293) that do not overexpress CD44, suggesting cancer-selective targeted efficacy. As Fc induces oxidative stress that is less mitigated in cancer cells, we expect it to also contribute to the observed cancer-selective treatment response. As a result, we propose Fc-HA-GQD formulation as a multifunctional targeted delivery, imaging, and cancer-specific treatment agent further to be studied in vivo.

Fluorescence has proved itself to be a useful tool in a wide variety of fields, ranging from environmental sensing to biomedical diagnostics. In this study, we propose to utilize a novel fluorescence-based technique called Surface Plasmon Coupled Emission (SPCE) to monitor molecular binding and to detect low concentrations of physiological markers (e.g. biomarkers present in the human body as a result of a disease). SPCE is characterized by directional emission that allows for a superior sensitivity and selectivity for detection. The development of an SPCE-based detection platform will allow for simple, fast and sensitive detection in a compact configuration that can be relatively easily implemented in the field or in primary care offices. Surface plasmon induced fluorescence at the interface of a thin metal layer (e.g. 50 nm of silver or gold) and a dielectric (e.g. glass) allows for highly enhanced excitation of fluorophores deposited on top of the metal film and very efficient detection due to the directional nature of this emission. As a result, we expect highly improved detection sensitivity compared to other fluorescence detection methods or other surface detection methods such as surface plasmon attenuated reflection (SPR).

Tryptophan is one of the few amino acids that is intrinsically photoluminescent. This is because its side chain consists of indole. Indole’s photoluminescence has both fluorescence (emits for nanoseconds) and phosphorescence (emits for microseconds). Fluorescence emission comes from a singlet to singlet transition, while phosphorescence from a forbidden triplet to singlet transition. Taking advantage of tryptophan’s intrinsic emission, we can use it as a label-free probe for protein dynamics. For some of these dynamics, such as myosin binding to actin, the fluorescence lifetime of nanoseconds is too fast to monitor changes. The phosphorescence lifetime is much better suited to monitor these changes of large biomolecule interactions. Before any binding studies are developed, we have characterized the basic properties of indole’s phosphorescent properties. We began by embedding indole (as well as 5 – bromoindole) in a polymer matrix (PVA) to immobilize and thus increase the phosphorescence at room temperature. We discovered that using a longer wavelength of excitation (405 nm instead of 290 nm) we excite directly from the singlet state to the triplet state of indole, a typically forbidden process. This populates the triplet state without any transitions to the singlet state. This allows the polarization of phosphorescence emission to be preserved, and anisotropy measurements can be used to monitor biomolecular processes.

In a virus study, the inoculum dose is the initial amount of virus used. It is correlated to the initial
amount of cells that become infected at the start of the study and thereby also correlated with the
amount of virus that will be produced by infected cells at the beginning of that study. Those virus spread
through a body in two known ways: cell free transmission and cell to cell transmission. While previous
research has investigated viruses based on free cell transmission, few models have incorporated cell to
cell transmission leading to unclear results and bias to certain variables. This research accounts for both
modes of transmission, using an agent-based framework, and varies the initial amount of virus, to
understand how inoculum dose affects the two transmission modes. Utilizing parallel processing, the
model represents virus infection and spread in a two-dimensional layer of cells in order to generate total
virus over time graphs for corresponding initial amount of virus. This project demonstrates how a
combination of agent-based models and parallel processing can allow researchers to perform the rapid
and large simulations necessary for viral dynamics research efficiently and affordably.

In order to calculate the ground and excited states of a perturbed harmonic oscillator, we use computer codes developed from the results of coupled cluster techniques. More specifically, we have implemented a diagrammatic approach in order to efficiently derive cluster amplitude and energy equations, along with iterative Bogoliubov transformations in order to improve the accuracy of computed energies. Such Bogoliubov transformations improve the zeroth order Hamiltonian, which is shown for a quadratic and quartic perturbation. These results are then compared to exact results obtained from numerical integration of the Schrödinger equation, though we note that numerical integration cannot be performed for more complex systems of coupled harmonic oscillators under perturbation. Explicit coupled cluster equations are also presented for such coupled systems subjected to similar perturbations.

Respiratory Syncytial Virus (RSV) is a common, contagious infection of the lungs and the respiratory tract. Syncytia are multinuclear cells that have fused together. It is so common that it effects all ages, but most people have experienced RSV by age two. Symptoms typically present similar to the common cold, with minimal effects and are easily treatable. RSV can, however, have detrimental effects on young children, the elderly, and those with compromised immune systems. As an individual infected cell can produce virus, so can syncytia cells. But, because of experimental limitations, it is difficult to measure characteristics such as viral production and lifespan of the syncytia cells. We will use mathematical models to study how different assumptions about the viral production and lifespan of syncytia change the resulting infection to determine whether less direct measurements can be used to determine syncytia viral production rates and lifespans.

DNA biomarkers are of growing significance for the personalized medicine, with applications including diagnosis, prognosis, and determination of targeted therapies. However, even unicellular organisms can represent a heterogenous system on a molecular level. Improving the detection limits for low DNA concentrations will allow for better decision making, e.g., in clinical medicine, research endeavors, and human identification in forensic investigations where frequently only a minute amount of evidence material is available.
The first step for DNA collection is typically collecting specimen by specialized medical swabs. Medical swabs come in all different materials, shapes and sizes. They are not the same, but they are often used interchangeably. For DNA testing swabs can be used in buccal and surface swabbing for DNA. Then the swab with DNA on it is sent for analysis. A common analysis technique is using fluorescence. But what if the swab itself has some fluorescence? Do different types of swabs have different fluorescence? We want to test the inherent fluorescence of a variety of different types and brands of medical swabs to determine the kind with the best properties for highly sensitive DNA detection. If the swab’s fluorescence is short-lived, we expect that we will be able to separate out the swab’s signal from the DNA’s signal by using long-lived dyes and our novel multipulse excitation scheme.

With the advent of graphene, there has been an interest in utilizing this material and its derivative, graphene oxide (GO) for novel applications in nanodevices such as bio and gas sensors, solid state supercapacitors and solar cells. Although GO exhibits lower conductivity and structural stability, it possesses an energy band gap that enables fluorescence emission in the visible/near infrared leading to a plethora of optoelectronic applications. In order to allow fine-tuning of its optical properties in the device geometry, new physical techniques are required that unlike existing chemical approaches yield substantial alteration of GO structure. Such desired new technique is one that is electronically-controlled and lead to reversible changes in GO optoelectronic properties. In this work, we for the first time investigate the methods to controllably alter the optical response of GO with the electric field and provide theoretical modelling of the electric field-induced changes. Field-dependent GO emission is studied in bulk GO/PVP films with up to 6% reversible decrease under 1.6 V/µm electric fields. On an individual flake level, a more substantial over 50% quenching is achieved for select GO flakes in polymeric matrix between interdigitated microelectrodes subject to two orders of magnitude higher fields. This effect is modelled on a single exciton level by utilizing WKB approximation for electron escape form the exciton potential well. In an aqueous suspension at low fields GO flakes exhibit electrophoretic migration indicating a degree of charge separation and a possibility of manipulating GO materials on a single-flake level to assemble electric field-controlled microelectronics. As a result of this work, we suggest the potential of varying the optical and electronic properties of GO via the electric field for the advancement and control over its optoelectronic device applications.

Rhinovirus is the most prevalent virus in humans and is often the cause of the common cold. Modeling the dynamics of rhinovirus can allow us to observe important aspects of the virus including the general growth of the virus, the remaining target cells, the number of cells in the eclipse phase, and the number of infected cells. Following that, we can attempt to estimate parameters such as how much virus an infected cell produces or how long it takes an infected cell to start producing virus. We can use a method called Markov Chain Monte Carlo (MCMC) to try and gain more accurate estimates of those parameter based off observed data. Modeling rhinovirus will give us deeper insight into the workings of rhinovirus and allow us to try better and more accurate models of the virus.

Non-invasive temperature sensing is necessary for the analysis of biological processes occurring in the human body including cellular enzyme activity, protein expression, and ion regulation. Considering that a variety of such biological processes occur at the microscopic scale, a mechanism allowing for the detection of the temperature changes in microscopic environments is desired. Although several such techniques have been developed involving nanomaterials, there is still a need in deterministic non-invasive biocompatible approach allowing for temperature measurements both outside the cells and in the intracellular compartments. Here we develop a novel approach utilizing graphene quantum dots (GQDs) as agents for such detection. Because of their small 2-5 nm size, non-invasive optical sensitivity to temperature change and high biocompatibility, GQDs enable biologically safe sub-cellular resolution imaging. Both bottom-up synthesized nitrogen-doped graphene quantum dots and quantum dots produced from reduced graphene oxide via top-down approach in this work exhibit temperature-induced fluorescence variations used as sensing mechanism. Distinctive quenching of quantum dot fluorescence by up to 19.8 % is observed, in a temperature range from 25℃ to 49℃, in aqueous solution, while the intensity is restored to the original values as the temperature decreases back to 25℃. A similar trend is observed in vitro in HeLa cells as the cellular temperature is increased from 25℃ to 41℃. Our findings suggest that the temperature-dependent fluorescence quenching of bottom-up and top-down-synthesized graphene quantum dots can serve as non-invasive reversible deterministic mechanism for temperature sensing in microscopic sub-cellular biological environments.

Star clusters are key age-dateable tracers of the chemical history of the Milky Way. Star clusters can provide significant constraints on galaxy chemical evolution models. The large discrepancies between different small studies limit the accuracy of these constraints, so a large uniform study is needed. To create a large uniform sample, we observed stars in 63 clusters with the same telescope. We then determined the chemical makeup of these stars using a machine learning tool called The Cannon. Using this sample, we examine the change in chemical abundance over the radius of our galaxy.

Nano- and microcrystalline ZnO is a low-cost material, employed in many applications due to its optoelectronic, structural and chemical properties as well as a great variety of synthesis methods. Among these applications, antibacterial action of ZnO is a budding field of interdisciplinary research. Despite numerous studies of this antibacterial action, the physical and chemical mechanisms behind it are still largely not understood. In particular, the influence of the crystal surface morphology and surface-surface interactions between the bacteria and ZnO are largely unknown. Hexagonal (wurtzite) ZnO crystals terminate with three different types of crystallographic surfaces: charged polar hexagonal (Zn or O), electrically neutral nonpolar rectangular and partially polar pyramidal slanted. In our studies we employ a hydrothermal growth procedure to synthesize nanocrystals and microcrystals of ZnO with tunable morphology to investigate the influence of surface types on interactions with bacteria as well as surface charge dynamics. To quantify the antibacterial action we employ minimum inhibitory concentration (MIC) assays of staphylococcus aureus with hydrothermally-grown ZnO microcrystals. Scanning electron microscopy (SEM) is used to characterize the morphology of the as-grown ZnO specimens as well as the organization of these particles after their interactions with bacteria. To characterize electronic structure and dominant charge transport mechanisms at ZnO surfaces we performed photovoltage (SPV) experiments. Our results confirm that antibacterial action is a result of ZnO surface interactions with extracellular material, whereas internalization of ZnO particles (happening in the case of nanoscale ZnO) is not necessary for inhibition. We also report that the electronic transitions at the surface of the ZnO particles are consistent the theoretically predicted electronic structure of ZnO, with the spectral signatures of surface states which could be the source of the antimicrobial action.

Reportedly, hydrophobic surfaces of polysulfone (PSu) thin films become hydrophilic following exposure to UV radiation and it can affect PSu novel applications in microfluidics and biophysics. Fundamental mechanisms behind this effect remain unknown. To elucidate them, in our work we study surface charge transport employing surface photovoltage (SPV) on thin PSu polysulfone films spin-cast on silicon substrates. Since exposure of PSu even to an ambient UV light could affect the surface properties we ran SPV spectroscopy as well as SPV transient experiments on both as-received samples fabricated in darkness and UV-irradiated films of varying and controllable thicknesses. We report on the comparison of the SPV response in the as-deposited and UV-irradiated polysulfone samples.

Modern astronomical catalogs consist of up to billions of stars and measure various properties of these objects. There have been recent data releases from two of these surveys, GAIA which measures positions and distances, and APOGEE which measures radial velocities and stellar physical properties. By combining these datasets we have the full 6D phase space information for each star and can compute orbital characteristics and kinematics properties. APOGEE targeted specific stellar populations in our Milky Way and determined some of their physical properties. By cross matching with GAIA, we are able to fully describe the orbits of these populations and look for potential new members that have the same physical and kinematic properties but are not located in the immediate vicinity. We will present kinematic properties of the full cross matched dataset as well as information on the targeted stellar populations of the Milky Way.

Metal nanoparticles on a substrate have gained significant attention in recent years as novel systems for new generations of catalysts. Among other metals, iron attracts constant attention due to its low cost. Iron possess either the body-centered cubic (bcc) or the face-centered cubic (fcc) structure. Up to 917 °C, iron exists in its α-form (α-Fe) with the thermodynamically bcc lattice. At 917 °C, α-Fe transforms into the fcc lattice, and this allotrope is termed as γ-iron (γ-Fe) (austenite) with diamagnetic properties. According to the iron-carbon phase diagram, γ-Fe can incorporate up to 2.03% carbon. Lowering the temperature below 917 °C, carbon atoms diffuse out of the structure, and γ-Fe turns back to α-Fe. Up to now, γ-Fe could not be stabilized without such impurities as Mn, Cr, Ni at room temperature. We have obtained of iron nanoparticles with the face-centered cubic structure with diameters of up to 200 nm without impurities on the substrate of graphene oxide by thermal annealing in an inert gas. In our work we show that phases formation of iron depends on the temperature of annealing. At the annealing temperature from 300 ºC through 600 ºC only iron oxides are formed. We established the unexpected formation of the γ-phase already at 700°C by X-Ray diffraction and Mössbauer spectroscopy. These methods clearly identify the stability of the γ-phase at room temperature. The rather low transition temperature of α-Fe to γ-Fe already starting at 700 °C suggests that the mechanism for the transformation is different from that observed for bulk iron. The maximum γ-iron nanoparticles content on the substrate of graphene oxide was fixed at an annealing temperature of 950 °C.

Habituation occurs when responding to a stimulus decreases with repeated exposure. This decrease can be seen in an array of behaviors, including wheel running. In this experiment, rats ran in four different contexts (i.e., running wheels with different backgrounds/scents) for 30 minutes every day. One group ran in the same context daily while the other alternated between contexts. Rats running in different contexts should habituate less and run more consistently and at a higher rate. By increasing our understanding of the influence of habituation on exercise, results will have important implications for those wanting to maintain interest in an exercise routine.

Abstract SRS: Effects of Cross-Situational Generalization on Memory and Attitude Polarization Toward Social Groups

Serena Avitia, Akua Jonah, & Kaleigh Decker

When people generalize about others, they go beyond the information they are given and infer a level of cross-situational consistency that may polarize their attitudes. The current study investigates how cross-situational generalizations about a group’s traits can affect subsequent attitudes and memory. We predicted that participants who generalized about a fictitious groups behavior across various settings will rate the likelihood of cross-situational trait consistency as significantly higher than the scale mid-point, and report more negative attitudes toward the group than participants who reviewed the initial information they were given. Generalizers will also write paragraphs that more depict group members as displaying the original traits in general rather than only in the given situations, mistakenly recall and recognize some of the situations they rated as part of the initial information, and mistakenly report that their reported attitudes (after they generalized) were the same as their impressions immediately after reading the initial information. The predicted results will increase our understanding of the processes by which attitudes toward an entire group can polarize without any additional information.