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Study of collective self-esteem and academic motivation examining perceptions of academic statistics of black traditional undergraduate students attending a PWI
Get PDFCollege enrollment for black traditional college-age students has been on the rise. Matriculation experienced a seven percent increase from 2000 to 2018 (NCES, 2020). However, Cokley et al. (2013) found that black students exhibit the highest minority stress among college students. Researchers also found that students may feel pressured to break stereotypes and perform well academically (Smith & Hope, 2020; Brooms, 2019; Mary et al., 2018). As more black students enroll in colleges nationwide, there is more than reasonable cause to continue examining how the matriculation of black students into predominantly white institutions impacts black students and their perceptions of themselves, their surroundings, and their likelihood of success. The present study explored how traditional undergraduate black students\u27 perceptions of academic statistics (on-time and delayed graduation rates, honors college matriculation) while attending a predominately white institution (PWIs) relate to their intrinsic and extrinsic academic motivations and collective self-esteem
Theoretical studies of benzoquinone reactivity in acidic and basic environments
Get PDFQuinones are a class of organic compounds containing a six-membered unsaturated ring with two carbonyl groups. They are biologically relevant mostly due to their ability to participate in redox reactions. Prior experiments in our lab showed that quinones can induce protein modifications that are pH dependent. In an acidic environment the modifications were less significant than in a basic environment. Previous computational studies have also been carried out to model, in neutral solutions, the reaction between various quinones and various amines. Various amine groups are used as a model for the amino group of lysine to represent protein modification. The theoretical study presented here will extend previous work by looking at the reaction between benzoquinone and methylamine in both acidic and basic media. All theoretical calculations were performed using a hybrid density functional theory method, MPW1K, in conjunction with the 6-31+G(d,p) basis set
Recent Advances of Electrochemical Impedance Spectroscopy in Biological Lipid Bilayer Membranes
Get PDFLipid Bilayer Membranes (LBMs) form the cellular boundaries that biologically and chemically separate the intracellular from the extracellular environment for biological cells. They also encapsulate many cellular organelles such as the Golgi Apparatus, mitochondria, and endoplasmic reticulum. With remarkably high flexibility, they form very complex and robust conformations such as in the Golgi apparatus; consequently, the mechanical dynamics and electrical characteristics of LBMs are the subjects of active research. Electrochemical Impedance Spectroscopy (EIS) is an efficient and widely used method for characterizing the dielectric properties of biological systems. Unlike dielectrophoresis, EIS is non-invasive and does not need labeling to measure the dielectric properties. In addition to that, it is based on an electrical impedance model, which can be much more accurately described, when compared to the fluid mosaic model, and the classical bilayer mechanics theory, and other models that attempted to describe the dynamics of LBMs. In this work, we investigate the recent advances in electrochemical impedance spectroscopy of biological lipid bilayer membranes, and compare the results of different works reported in literature on biological phospholipid bilayer membranes. Values of electrical resistivity\u27s of phospholipid bilayer membranes that are reported in literature vary by as much as six orders of magnitude
Gender and Perception of Music Genre in College Students
Get PDFSixty-nine college students listed five songs that they enjoy, then classified each song into one of 15 music genre options. Each of the listed songs were assessed for vocalist gender, which was compared to their music genre classifications and the listeners’ gender. Male vocalists were dominant in every genre tested, outnumbering female vocalists 3.7 to 1. Pop was the notably more equitable exception with a ratio of 1.15:1. However, female vocalists were constricted to the pop genre, as 49% of the listed songs with female vocalists were considered to be pop. Additionally, the study found male and female vocalists have demographically different audiences. It also found some gendered music genres and significant gender differences in the listeners\u27 music genre perception
The role of A-layer in polyunsaturated fatty acid (PUFA)-mediated effects on Aeromonas salmonicida subsp. salmonicida
No full textAeromonas salmonicida subsp. salmonicida is a Gram-negative bacterium that infects salmonids and non-salmonids worldwide leading to an infection known as furunculosis, which is characterized by skin lesions and hemorrhages of the fish epidermis. This infection is carried out by a A+ (virulent strain) of A. salmonicida containing an important virulent factor known as the A-layer, which is a 2D paracrystalline structure that binds to the basement membrane and functions to promote adherence to host membranes and resistance to host defense. The purpose of this study was to examine the ability of the A+ A. salmonicida to incorporate exogenous fatty acids into its lipid membrane and explore the phenotypic outcomes. A. salmonicida A+ and A- strains were differentiated using the Congo Red plating method. The A+ A. salmonicida cultures were grown in CM9 supplemented with the presence or absence of 300µM exogenous polyunsaturated fatty acids (PUFAs). Lipids were extracted and analyzed for membrane assimilation by thin-layer chromatography and ultra performance liquid chromatography mass spectrometry and showed the ability of A. salmonicida to incorporate exogenous fatty acids into its lipid profile. The phenotypic outcomes were examined using a series of assays for membrane permeability, antimicrobial peptide susceptibility, and biofilm formation. The fatty acid 20:5 significantly (p \u3c 0.001) decreased biofilm formation consistently across the temperatures tested. A general decrease in biofilm formation was seen at a higher temperature of 28ºC. The PUFAs (18:3γ 20:3, 20:4, 20:5, 22:6) significantly (p \u3c 0.001) permeabilized the membrane by 40% when compared to the control tested in the crystal violet uptake. In addition, the PUFAs (18:3γ, 20:3) provided significant (p \u3c 0.001) protection against the antimicrobial peptide polymyxin B (PMB). The A+ strain when compared to the A- displayed similar phenotypic effects as a fish pathogen. In fact, both A+ and A- strains preferred the fatty acid 22:6 which may indicate a role omega-3 fatty acids play in A. salmonicida being a fish pathogen
Investigating the Public Service Loan Forgiveness Program\u27s Impact on Public Service Employees
Get PDFThe Public Service Loan Forgiveness (PSLF) program has garnered attention in the media in recent months, primarily in reaction to recent program reforms. Public service employees have struggled to navigate the PSLF program since its formation in 2007, which is complex, tedious, and time consuming. While some relief has been granted, many more face uncertainty as to whether or when their loans will be forgiven. Coupled with the fact that many individuals feel shame and stigma for having loans in the first place and for seeking loan forgiveness, the PSLF process can take a negative toll on individuals and in turn, negatively impact a wide variety of personal, social, and work outcomes. For this study, we surveyed individuals pursuing PSLF and assessed a variety of emotional responses to the loan forgiveness process and a variety of well-being outcomes. We hypothesize that individuals who are enrolled in the PSLF program will have more negative emotional responses to the loan forgiveness program than positive emotional responses. We hypothesize negative emotions about the PSLF process will be positively correlated with a) levels of depression and b) feeling like a burden on their family. Additionally, we will explore the size of the loan to be forgiven and number of years spent pursuing loan forgiveness in these relationships. This study is a beginning phase of our research agenda, wherein our goal is to explore and understand how enrollment in the PSLF program conflicts with one’s time, contributes to personal strain, lack of autonomy, and coping attempts to handle the program alongside their life demands. Participants were recruited to complete an online survey from social media pages associated with PSLF and data collection is still ongoing, with 116 participants to date. Data are being analyzed using correlation and regression analyses in SPSS. Implications of this study include gaining a greater understanding of the emotional impacts of the PSLF program on public service employees. Further, this work aims to spark a call to action for the PSLF program, as it is in dire need of further reform to decrease the enrolled individuals’ negative outcomes, in both the personal and work spheres. Policy implications would also include devising tactics and establishing resources for public servants to mitigate their depressive symptoms and improve their overall mental health. Such improvements would not only help the public service employees, but also their communities that they are serving
The relationship between leadership engagement and workplace incidents
Get PDFOrganizations with strong safety cultures tend to have fewer injuries, which is likely attributed to an increased engagement in safe work behaviors (Dejoy, 2005; DeJoy et al., 1995; Zou, 2011). Furthermore, Hahn and Murphy suggest that engagement behaviors in safety management systems also contribute to a strong safety culture (2008). Engagement behaviors in safety management systems include reporting near misses and minor injuries as well as engaging in safety policies and practices that are perceived as important to the organization and its leaders. In this study, we will be examining how leadership engagement in safety practices is related to near misses and workplace incidents at a large chemical manufacturing company in the United States. The company recently implemented a leadership engagement tool called the ZIM Tracker (Zero-Incident Mindset), which is designed to encourage leaders to engage in and track safety practices in hopes that it will ultimately lead to a decrease in workplace incidents. The ZIM Tracker presents individuals and groups with monthly safety goals, which include over 20 different safety practices, such as Pre-Job Hazard Assessment or Emergency Drill Participation, identified by the company. We suggest that if leaders are more engaged in safety practices and tracking those practices, then the number of reported near misses will increase and the number of workplace incidents will decrease. The number of reported near misses will increase because the leaders’ engagement will signal to the employees that it is important to report near misses, which will allow for the situations leading to a near miss to be addressed. By addressing these near misses, we expect a subsequent decrease in workplace incidents. Because the ZIM Tracker is a relatively new tool, it is important to evaluate its validity over its three years of implementation. We expect that if the ZIM Tracker is encouraging leaders to engage in and report safety practices then there will be an increase in safety practices reported and conducted because leaders will be motivated to achieve their safety goals within the ZIM Tracker. We also expect that this increase will subsequently lead to an increase in reported near misses and a decrease in workplace incidents. To test this hypothesis, we will examine safety outcome data over the three years prior to the implementation of the ZIM Tracker compared to three years after implementation
Food deserts, crime, and neighborhood context: an examination of the impact of food insecurity on violent crime in Little Rock
Get PDFThis thesis seeks to explore the indirect and direct relationships between food insecurity, concentrated disadvantage, and distribution of violent offenders through the lens of social disorganization. Data gathered by the Little Rock Police Department, American Community Survey, and city business license records are used to test neighborhood-level relationships across Little Rock, Arkansas’ 155 Census block groups. Pearson’s Correlation is used at the bivariate level and negative binomial regression tests multivariate relationships. The results suggest a null relationship between food insecurity and distribution of violent offenders across Little Rock block groups. However, several findings are consistent with prior research and theory– the most salient of which is the impact of concentrated structural disadvantage on the distribution of violent offenders. This thesis contributes original research to the study of food deserts and crime that may be used as a foundation for future studies
Analysis of the factors influencing multiple uses of crime guns: an exploratory study
Get PDFA broad body of literature has been built around the topic of gun violence in the United States. The characteristics of communities, victims, and offenders have each been used to explain variation in the likelihood and frequency of gun crime. Less attention has been given to the factors associated with multiple uses of crime guns. The current study applies binary logistic regression to crime logs maintained by the police department of a mid-size city in the Southeastern U.S. to examine how neighborhood and initial incident characteristics influence the likelihood that a crime gun will be used in multiple incidents. Gang involvement and time in circulation are found to be positively related to the odds of a crime gun being used in more than one offense, while street culture exerts an inverse influence. Further, street culture was found to condition the impact of offense severity on repeat use
Improving IoT security through the use of deep learning at the physical layer
Get PDFThe Internet of Things (IoT) is a heterogeneous network interconnection connecting electronic and electro-mechanical devices to the Internet. The total number of IoT devices is estimated to reach 26.66 billion and is expected to reach 75.4 billion by 2025. Currently, only 30% of the IoT devices employ encryption, which puts the majority of the IoT devices and their underlying infrastructure under risk of attacks by: 1) devices that are wrongly authenticated to access the network specially when digital credentials are transmitted without encryption, and 2) devices that can detect, intercept, and exploit communications between IoT devices. Therefore, more advanced security mechanism are required to secure IoT devices, their corresponding networks, and infrastructure. The Open Systems Interconnect (OSI) stack provides a layered model that governs IoT networks. Based on the OSI stack, the physical (PHY) layer–of each IoT device and associated network–is the first layer exposed to attacks. Traditionally, IoT security techniques are implemented in higher OSI layers, thus these techniques ignore the PHY layer and any potential security advantages it possesses. Due to the demonstrated success of Deep Learning (DL) within the fields of computer vision and image processing, as well as prior research that suggests DL as a viable solution to addressing communications system challenges; this work investigates DL-driven PHY layer security techniques that surpass traditional approaches. The presented work investigates PHY layer security at the encoding and waveform levels. Encoding-based PHY layer security is achieved through an adversarial training and shared-code scheme that leverages DL to redesign a Direct Sequence Spread Spectrum (DSSS) communications system such that it inherently, deliberately, and adaptively prevents an adversary from detecting and reconstructing captured messages. Waveform based PHY layer security is improved through a Radio Frequency-Distinct Native Attributes (RF-DNA) fingerprint process capable of exploiting Specific Emitter Identification (SEI) features that are extracted from waveforms that transverse a Rayleigh fading channel prior to collection. This is achieved through the integration of channel correction prior to DL-based radio identification. The investigated channel correction approaches include traditional and semi supervised learning. The results show that: 1) the DL-based redesign of DSSS encoding achieves featureless signaling that prevents the adversary from reconstructing detected messages, and 2) unsupervised learning based channel correction improves RF-DNA fingerprinting performance by 25% over that of traditional machine learning approaches