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Do Americans Want Companies to Get Involved in Social Movements?
No full textSocial justice movements have occurred in the U.S. as methods for social groups to bring awareness to and address inequities in the country. Psychological research has spent a lot of time understanding how social justice movements impact society and its members. In the US, the Black Lives Matter movement focuses on racial injustice and forces Americans to consider how they view and approach prejudice toward racial minorities. Industrial and Organizational Psychology has also examined how identities outside of a company (e.g., race, gender) impact people\u27s behaviors towards and within a company. Little research has specifically focused on how people respond to companies when they respond to social justice movements or current events. The goal of this research is to assess factors that impact perceptions of diversity statements from companies and how these perceptions may impact people’s engagement with the companies and social movements themselves. We predict that people will view companies differently based on their own opinions and social groups. Specifically, people who are already active in social justice and who have friends and family who engage in social justice will like companies that support social justice more than people who are not active in social justice. The effect will also be present when participants are asked how comfortable they are with interacting with said company. Overall, the current research will help researchers understand the role companies have in social justice movements
An Analysis of Factors that Affect Work Zone Crash Severity
No full textRoadway work zones pose a significant threat to the lives of both motorists and construction workers, by changing the route of a roadway and having workers operate close to moving vehicles. With driving culture varying from state to state in the US, analyzing crash data from a particular region is the most effective way to determine what causes severe work zone crashes. This study investigates five factors that may contribute to the injury severity of work zone crashes in the state of Georgia: Speed limit, time of day, average annual daily traffic (AADT), number of lanes, and manner of collision. Using Georgia work zone crash data from 2019-2023, this study cross-analyzes each factor with KABCO injury severity. Using a chi-squared test, it was found that all factors are significantly correlated to the severity of work zone crashes. The manner of collision had the highest chi-squared value, indicating that it is the most significant out of the factors considered in regard to influencing the crash severity. Based on the results, it is recommended to implement median break-away barriers in work zones to reduce head on collisions with oncoming traffic and to force motorists to slow down to navigate the constricted roadway. In addition, using reflective cones and speed monitoring displays may help drivers navigate and slow down on roadways in darker conditions when the chance for fatal crashes is heightened
Intracellular Spatial Dynamics of Metal Transcription Factor 1
No full textMetal Transcription Factor 1 (MTF-1) is a cytoplasmic transcription factor protein involved in cellular response to metal ions and stress. During cellular stress or heavy metal exposure, MTF-1 proteins translocate to the nucleus and bind DNA metal response elements (MRE), initiating the transcription of genes associated with intracellular metal regulation (e.g., zinc transporter (ZnTs), Zrt-/Irt-like protein (ZIP), metallothioneins). MTF-1 is positioned as a key sensor of cellular processes that trigger the need for bio-metals such as zinc. Therefore, monitoring its spatial distribution in cells can provide insight into what cellular conditions cause its intracellular movement. To visualize MTF-1 eukaryotic cellular location, chemically competent E. Coli (strain: DH5-α) cells were transformed with an MTF-1 plasmid containing Green Fluorescent Protein (GFP) and ampicillin (amp) resistance inserts. Transformed cells were selected using amp+ agar plates. Visible colonies were harvested then grown in amp+ Lennox Broth (LB) broth for amplification followed by plasmid purification. Purified endotoxin free plasmids were transfected into human embryonic kidney (HEK) 293T cells and imaged using fluorescent microscopy techniques. Control data demonstrated plasmid transformation, high yield purification, and efficient transfection. We aim to use this instrument to study intracellular MTF-1 trafficking during wound and regeneration and to determine if its nuclear translocation is regulated by reactive oxygen species
Computational study of the proton transfer in the H7O3+ cluster
Get PDFProton transfer (PT) from one molecule to another is among the most studied phenomena in chemistry. PT requires the bond cleavage and the formation of a new one, AH+ + B -\u3e A+ BH+. In protonated water clusters, such a process consists of the interconversion of hydrogen bonds. Experimentally, such a process can be observed as a significant increase of a dipole moment. However, other vibrational transitions often occur with small changes in the dipole moment while large changes in polarizability. In this work, we study the PT process in a protonated water cluster, H7O3+ using computational methods. We run geometry optimization and compare data of various methods, such as density functional theory (DFT) methods and highly accurate CCSD(T) level of theory, with available experimental data. Thermodynamic data of H7O3+ and its dissociation fragments, H5O2+, H3O+, and H2O are collected, and dissociation energies are calculated. Also, harmonic vibrational infrared (IR) and Raman spectra of H7O3+are calculated using normal mode analysis and compared to anharmonic spectra obtained from molecular dynamics simulations. Raman spectra of H7O3+ have yet to be recorded in the experiment. The second-order Møller–Plesset perturbation theory (MP2), Becke 3-Parameter Lee-Yang-Parr functional (B3LYP), Perdew-Burke-Ernzerhof (PBE) functional, and the Coupled Cluster theory are used in conjugation with AVDZ and AVTZ basis sets. IR and Raman spectroscopies are used to identify vibrational modes of a complex that cause changes in dipole moment and polarizability, respectively. Collected data on H7O3+ will aid in the determination of the polarizability tensor surface. H7O3+ and H5O2+ dissociation energies and their corresponding zero-point corrected values will be compared to the experimental values of Dalleska et. al. Dissociation energies provide insight into the strength of bonds in a molecular complex and reveal the accuracy of the given computational approach. Identifying anharmonic shifts and new vibrational modes in the vibrational spectra can aid in the understanding of the structure and interactions of the clusters. The shifts in spectra are due to the interactions between the clusters and their surroundings, as well as the symmetry of the molecules. The study of this small, protonated water cluster, H7O3+ is integral to the study of proton motion in biological and synthetic systems
Finite Element Analysis of Seismic Response in Structural Models with and without Fluid Viscous Dampers, Using a New Viscoelastic Model, Phase II
No full textThis research uses finite element analysis (FEA) to explore the dynamic response of composite buildings under seismic loading, focusing on optimizing damper configurations to enhance energy dissipation and reduce structural damage. The study examines various structural configurations, analyzing how fluid viscous dampers (FVDs) mitigate stress, displacement, and vibrations during dynamic events. Proper damper placement, including direction and location, is tailored to address specific structural vulnerabilities, significantly reducing inter-story drifts, improving force distribution, and ensuring safety.
Strategic damper placement, considering building height and inter-story behavior, maximizes performance, with systems like Toggle-Brace-Damper, Eccentric Lever-Arm, and Viscous Wall Dampers offering targeted solutions for efficient energy dissipation. The addition of FVDs results in a significant reduction in vibrations, enhancing resilience and minimizing structural fatigue.
In the configuration selected in this work, dampers are placed horizontally and connected to a near-rigid chevron frame. This approach maximizes energy dissipation by injecting the full movement into the damper\u27s horizontal orientation, though some motion may be lost due to the frame\u27s stiffness constraints.
The findings bridge the gap between theoretical modeling and practical application, providing insights for designing real-world experimental models to test vibration control strategies. The outcomes offer innovative solutions for improving the safety and stability of structures in seismically active regions, advancing both structural and mechanical engineering
Assessing a Solution for GA Work Zone Safety Through Cross Classification
No full textWork zone safety is a health risk for drivers and construction workers. In Georgia, work zone crashes have decreased over the past 5 years, but the number of fatalities has still been over 1,000 each of those years. Studies have proven solutions such as lowering the speed limit or relying on current traffic control devices to be ineffective. The risks associated with these crashes must be recognized to improve upon previous solutions or innovate new ones from the results. The objective of this study is to utilize cross classification to identify factors that contribute to work zone crash deaths and severe injuries in the state of Georgia. The following factors found within the Georgia Department of Transportation were cross classified with the KABCO severity scores: manner of collision, urban & rural, segment annual average daily traffic, work zone type, and posted speed limit. GDOT data dating from the years of 2019-2023 was gathered and placed in contingency tables using each factor versus crash severity. The expected values were then calculated from the gathered data (or observed values) and placed in new tables for each factor. Then, the observed and expected values were used to calculate the chi-square value of each factor. The results showed that all listed factors are indeed risk factors that influence crash severity. Work zone type had the smallest chi-square value and manner of collision had the highest. Therefore, the manner of collision is the most significant regarding the severity of work zone crashes. In conclusion, energy absorption median stoppers could be built on Georgia’s highways to reduce the amount of collision type crashes. Additionally, improved traffic control devices may help lessen the flow of traffic and strategically placed radar-based feedback systems may help drivers become more aware of their high speeds within work zones
AI-Driven Predictive Modeling of Alzheimer’s Disease Progression Using Deep Learning and Clinical Data
No full textAlzheimer\u27s disease is one of the most important public health problems of our time, affecting millions of individuals worldwide. As a chronic neurodegenerative disorder, Alzheimer\u27s leads to cognitive decline, memory loss, and, ultimately, loss of autonomy. Our research aims to employ artificial intelligence, through a Dense Neural Network (DNN) model, to analyze the progression of Alzheimer\u27s based on an individual\u27s exercise, diet, lifestyle, and current condition. Our data was obtained from WashU Medicine’s Open Access Series of Imaging Studies (OASIS) database of cross-sectional MRI scans from patients that ranged in age from young to older adulthood. The two datasets that were used focused on showing the progression of Alzheimer’s (cognitively normal, uncertain dementia, and AD dementia) over time in a variety of patients. They were first merged via their SessionIDs to ensure the model’s ability to track a patient’s cognitive progression in case their OASISID had multiple SessionIDs attached to them. The data was then preprocessed to ensure data integrity through scaling, encoding, and handling NaN (null) data values. A Dense Neural Network model with two hidden layers was implemented using TensorFlow and Keras, optimizing for both accuracy and generalizability. The model was trained with a categorical cross-entropy loss function, adaptive learning rate optimization via the Adam Optimizer, and class weight balancing to mitigate bias against important, yet underrepresented classes, for the sake of generalization. The model achieved a classification accuracy of 96% ± 2% after 50 epochs, demonstrating its potential for accurate predictive analytics in biomedical applications. By identifying patterns and correlating disease progression, we aim to generate predictive insight that can be used to support early intervention and customized treatment methods
The Association between Gestational Cortisol & Maternal Metabolic Health
No full textBackground: Cortisol is a stress hormone produced by the adrenal gland. Excess cortisol is associated with poor metabolic health, including insulin resistance and abdominal adiposity. Maternal cortisol levels increase three-fold to support fetal growth and development, however excess cortisol production is linked with adverse offspring outcomes.
Objectives: This study tests the associations between cortisol, abdominal fat, and insulin resistance in pregnancy.
Methods: Twenty-three participants (BMI = 30.85 ± 7.4, age = 27 ± 5) visited the KSU Exercise Science Physiology laboratory in early pregnancy (V1, 12-15 weeks) and late pregnancy (V2, 24-28 weeks). Blood samples were collected during each trimester, and body-fat percentage was assessed using bioelectrical impedance analysis. HOMA-IR was used for insulin resistance. Intra-abdominal-adipose-tissue (IAAT) and subcutaneous1 (SAT1) thicknesses were collected by ultrasound 1cm above the umbilicus. Preperitoneal-adipose (PPAT) and subcutaneous2 (SAT2) were collected immediately below the xiphoid process. Correlations were used to determine differences in SPSS, and body fat was controlled.
Results: HOMA-IR in early pregnancy was strongly and positively associated with SAT1 and SAT2 in visit one (p\u3c0.05). Cortisol on visit three is strongly and negatively associated with HOMA in early pregnancy (p\u3c0.05).
Conclusion: As expected, HOMA-IR and SAT1 and SAT2 were strongly and positively associated; contradistinctly, late pregnancy cortisol was negatively associated with early pregnancy HOMA-IR
Observing and Measuring The Links Between Morals, Deviant Behavior, and The 4F’s Trauma Response Structure
No full textIn 1915, American Physiologist Walter Bradford Cannon introduced “The 4F responses,” a theory that essentially suggests that trauma responses (i.e., fight, flight, freeze, and fawn) can disrupt moral reasoning, potentially increasing the likelihood of participating in or accepting deviant behavior by altering how individuals assess right and wrong in both high-stress and ordinary situations. This project takes an interdisciplinary approach and uses the Moral Foundations Theory to explore how an individual’s moral intuitions impact their trauma responses and behavioral outcomes. The current study uses a survey method to present participants with hypothetical scenarios, allowing for the measurement of decision-making outcomes and processes (e.g., reaction times, difficulty experience, confidence, etc.). Based on previous research and preliminary findings, we would expect to find that trauma responses would vary as a function of people’s moral intuitions. Overall, the projection of the findings and results collected are to ultimately prove the links, relationships, and effects of these natural trauma responses towards moral decision-making
Adoptonomics
No full textThis research presents an analysis aimed at understanding the financial aspects of the adoption process. Our goal was to investigate how families prepare financially for adoption, focusing on the various financial requirements and contributions across different adoption methods, and to explore the sociocultural connection between adopting individuals\u27 attitudes and preferences towards various adoption funding methods.A sample of 125 U.S. families participated in this investigation. Parental participants averaged 45.94 years (s = 8.651). Most parents identified as female (91.43, Caucasian (88.57%), held a bachelor’s or graduate degree (62.85%), and identified either as Christian (28.57%) and agnostic (14.29). Most families spent money on agency fees, home study expenses, and paperwork/dossier expenses. Two types of fundraising were presented to families: 1) receiving money from others in exchange for giving goods in return, and 2) receiving money from others without offering goods in return. Most participants did not fundraise to pay for their adoption. Families who cashed in their 401k felt more comfortable with fundraising, X² (6, N = 11) = 15.01, p = 0.02. Those who endorsed fundraising without offering something in exchange were more likely to take and accepted state and federal subsidies to fund their adoption, X² (24, N = 35) = 45.87, p = 0.005. People who did not endorse fundraising were more likely to receive subsidies (free money) from outside sources, X² (80, N = 31) = 103.70, p = 0.039. The presented data utilized a sociocultural perspective; we investigated which families were more or less likely to utilize various adoption and funding methods and how comfortable they felt with the process, acknowledging that their choices may have been influenced by their motivations or attitudes towards seeking additional assistance (Tybejee, 2003)