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Cultural Competency in Nursing Education: Assessing Knowledge Among Nurse Educators in Northwest Georgia\u27s Nursing School
No full textCultural Competency in Nursing Education: Assessing Knowledge Among Nurse Educators in Northwest Georgia\u27s Nursing School
Background: Nurses encounter diverse cultures and ethnicities throughout their careers. Cultural competence, defined as a necessary component of quality care, encompasses the attitudes, knowledge, and skills of providers (California Endowment, 2003). Ensuring an appropriate level of cultural competency among nurse educators can positively influence educational settings, helping students thrive both in class and in the field (Armour, 2004).
Aim: This study aims to explore the level of cultural competency knowledge among nurse educators at a nursing school in northwest Georgia.
Method: A descriptive exploratory study was conducted with 22 nurse educators from a nursing school in northwest Georgia, who completed an online anonymous survey. The survey included demographic factors and utilized the Cultural Competency Self-Assessment Checklist to assess knowledge levels. Descriptive analysis of percentages and frequencies was used to describe the study sample and their cultural competence knowledge.
Results: A total of 22 participants completed the survey, aged between 47-57 years. The majority held a master\u27s degree, and 52.4% were doctorally prepared. More than half (61.9%) were white, and 71% had graduated more than six years ago. All participants had experience working with patients or students of minority origin. Half (52.4%) considered themselves minorities based on religion, origin, or color. Knowledge scores ranged from 8-28 out of a maximum of 130, with most scores in the middle range.
Conclusion: This study highlights a lack of cultural competency knowledge among nurse educators despite the recent advances in nursing education and workplace settings, indicating a need for workshop training programs to increase their knowledge levels. Limited cultural knowledge among educators can result in lower student success and retention rates, as well as a decrease in the quality of care provided by the nursing workforce. Future studies should explore cultural competency training programs to enhance knowledge among a broader scope of nursing professionals and examine the long-term effects on student performance, retention rates, success, and healthcare disparities
Re-Entry of a Space Capsule in a Martian Atmosphere
No full textThe aerodynamic performance of space reentry capsules plays a critical role in ensuring safe and efficient atmospheric descent. This study focuses on the computational fluid dynamics (CFD) simulation of airflow around a blunt-body reentry capsule designed for descent into the Martian atmosphere. The objective is to analyze aerodynamic properties such as drag, heat transfer, and flow separation under Martian atmospheric conditions. The investigation will be conducted using ANSYS Fluent, leveraging turbulence models and heat transfer equations to capture key flow characteristics specific to Mars\u27 thin atmosphere
Study on AsRiPPs, arsenic-containing ribosomally synthesized and post-translationally modified peptides
No full textArsenic (As), the king of poisons, has been a potential agent in medicine, particularly in antibiotic production. Notably, some bacteria utilize As to produce unique antibiotics, as represented by Arsinothricin (AST), the first known As-containing antibiotic. AST effectively controls various pathogens while sparing human cells, demonstrating the potential of As-containing antibiotics as a new pipeline for our shrinking antibiotic arsenal. To discover further novel As-containing antibiotics, we mined bacterial genome database using the AST Biosynthetic Gene Cluster (BGC) and found prospective BGCs for novel As-containing antibiotics in two Actinomyces: Microbispora rosea and Amycolatopsis tolypomycina. Gene analyses suggest that the BGCs code for As-containing RiPPs (Ribosomally Synthesized and Post-translationally modified Peptides), which we named AsRiPPs, where one gene encodes a precursor peptide with the remaining genes involved in post-translational modifications. From the M. rosea AsRiPP BGC, we selected four genes (one precursor peptide gene and three modifier genes), which we hypothesize are the minimum required gene set to produce an As-containing precursor of the encoded AsRiPP. The precursor peptide gene was solely expressed or co-expressed with the modifier genes in Escherichia coli in the presence of As and the AsRiPP production was analyzed. So far, we confirmed that the precursor peptide gene was expressed when solely expressed in E. coli and successfully purified the peptide by affinity chromatography. We are currently examining the strain that co-expresses the precursor peptide gene and modifier genes. As an alternate approach, we cultured A. tolypomycina with As and examined the production of the AsRIPP. As a result, we found that the strain produced an organic As species with antibiotic activity, suggesting that the strain produces an As-containing antibiotic, presumably an AsRiPP. These results demonstrate that further As-containing antibiotics exist in nature, offering a new avenue for the discovery of antibiotics
The Role of Artificial Intelligence in Mental Health: Opportunities, Challenges, and Ethical Considerations
Get PDFMental health issues are becoming more common worldwide, especially after the COVID-19 pandemic and the ongoing shortage of mental health professionals. AI has the potential to help bridge this gap by offering scalable, affordable, and accessible mental health support. This research examines how AI-driven tools like chatbots and natural language processing systems are being used in mental health care and evaluates their effectiveness and limitations. Case studies like Wysa and HAILEY demonstrate that AI can be useful for people with mild to moderate anxiety and depression. This study analyzes case studies and existing literature to assess how AI supports mental health care while identifying potential risks and ethical concerns. However, AI tools have major limitations, including a lack of human empathy, privacy concerns, and potential biases in their models. While AI is valuable for diagnostic support, therapist training, and crisis intervention, it cannot replace human clinicians—especially for individuals dealing with severe mental health conditions. Findings suggest that AI should complement, rather than replace, human professionals to maximize effectiveness. This paper also highlights the ethical concerns and policies needed to make AI integration safe and effective. Future research should focus on enhancing AI’s emotional intelligence, reducing bias, and ensuring responsible use in mental health car
Exploring the Environmental Factors that Affect Color Change in the Green Anole
No full textExploring the environmental factors that affect color change in the green anole
The green anole (Anolis carolinensis) is the only native anole in the United States and one of the most common reptiles throughout its range. These anoles are rather slender and small, ranging from five to eight inches in length as adults and are found throughout the southeastern United States, living in a wide variety of habitats such as swamps, forests, parks, and even residential areas. Individual green anoles are capable of changing their color—fluctuating between various shades of green and brown. But why? Previous studies have tested alternative hypotheses of camouflage (or background matching), thermoregulation, and social interactions. Here, we provide an independent test of the role of thermoregulation and background matching using 1,175 records of anoles from Atlanta, Georgia from a citizen science database. From each observation, we recorded the type of background the anole was found on, the color of background, and the color of the anole. Using R, we extracted local air temperature and weather data. We then built a series of models to identify the relationships between anole color and air temperature, background type, and background color. Here, we present preliminary results discussing the strengths and weaknesses of the citizen science data to answer our preliminary hypotheses
Design and Development of Bat-Inspired Unmanned Aerial System for Mapping and Navigation
No full textThe goal of this project is to develop a sonar-based Unmanned Aerial System (UAS) that mimics bat behavior using ultrasonic waves and reflections to form a spatial map to navigate and avoid obstacles. While using a quadcopter design, two overlapping carbon fiber plates make up the center frame, and four booms extend from its corners to hold the propulsion system. The foremost compartment resembles the head of a Grey Long-Eared Bat, which houses a 400EP125-NBWN speaker in the mouth to emit ultrasonic pulses, which are reflected and detected by two SO.2 Ultrasonic Omni Lapel Lav Microphones placed inside the bat ears, to facilitate the mapping and navigating. The microphones connect to a microcontroller for signal processing through an ADC if needed, and the speaker is controlled with PWM and an amplifier. Custom 3D-printed components, printed using a Stratasys F170 FDM printer, include ESC housings, a modular battery box, a sliding door mechanism, and the bat-shaped head and ears. These components were designed in SolidWorks and ensure compatibility with the UAS while utilizing modularity, reducing weight, and minimizing drag. Finite Element Analysis (FEA) was performed to simulate stress distribution and strength of 3D-printed components under operational loads. After integrating flight-critical electronics, the UAS successfully flew a hover test at five feet, performing controlled roll, pitch, and yaw movements, successfully executing 90-degree and 180-degree turns, forward-backward, and side-to-side transitions. The UAS experienced minimal drift, smooth response times, and a controlled landing. The total flight was approximately one minute, but further testing is needed to ensure that the UAs complies with every design requirement
Search for Novel Arsenic-Containing Antibiotics
No full textArsenic is one of the most potent environmental toxins. On one hand, therefore, many bacteria have evolved arsenic-detoxifying mechanisms to counteract such a powerful substance. On the other hand, surprisingly, some bacteria utilize arsenic in metabolism, as an electron acceptor/donor, osmosis, or other functions. Another way to employ arsenic is in antibiotics. Some bacteria weaponize environmental arsenic to combat other bacteria, producing compounds with potential medical uses, as represented by arsinothricin (AST), the first known arsenic-containing antibiotic that controls various pathogens. These insights open new pathways in the pharmaceutical field to innovate in novel, arsenic-containing antibiotics that can help combat modern, high-priority diseases like tuberculosis and malaria. The goal of this project is to identify novel arsenic-containing antibiotics, which we hope can be utilized long-term to shed light on our shrinking antibiotic arsenal and help combat drug-resistant bacteria. The gene set (so-called biosynthetic gene cluster, or BGC) required for AST biosynthesis was used to search bacterial genome databases, which led to the discovery of several prospective BGCs for novel arsenic-containing antibiotics. In this project, four bacterial strains with the prospective BGCs were selected and cultured with arsenic under various conditions, testing their ability to produce novel arsenic-containing antibiotics. After several days of culture, bacterial cells were removed by centrifuge, and the resulting supernatant (i.e., liquid medium) were collected, and arsenic species in the media was analyzed by liquid chromatography coupled with inductively-coupled plasma mass spectrometry (LC-ICP-MS). As expected, unknown arsenic species were detected from some of the cultures, suggesting that the prospective BGCs are for novel arsenic-containing antibiotics. We are currently repeating the experiments to confirm the obtained results. Our study will provide insight into the arsenic biogeochemical cycles of various bacterium and their potential uses in the drug industry and medical field
Modular 3D-Printed Translational Spring System for Engineering Education
No full textThe high cost and limited availability of laboratory equipment restrict hands-on learning opportunities for engineering students. The research question being addressed here is: Can a fully 3D-printed, modular translational spring system provide an accessible and cost-effective tool for teaching vibrations and dynamics? This project focuses on designing and prototyping a device that demonstrates translational forces using an interchangeable, pegboard-mounted system. The modular design features magnetic connections between springs, carts, and stoppers, allowing for easy assembly, disassembly, and customization of different spring lengths. By integrating these adaptable components, the system aims to provide a flexible learning tool that can be adjusted to suit different experimental needs. The design process involved iterative sketching, SolidWorks modeling, and 3D printing to refine tolerances and determine suitable materials. The expected outcome is a functional, scalable educational tool that enables universities to teach core engineering concepts without significant financial investment. This system has the potential to enhance visual and hands-on learning, making complex concepts more accessible to students. Future work includes finalizing the build setup with defined tolerances for pegboard integration and optimizing the spring and rail system for better performance and ease of use
Predator Species Across Different Kingdoms: A Bacterial Agar Art Exhibition
No full textPredators are essential across all domains of life, regulating populations, shaping ecosystems, and driving nutrient cycles. This agar art exhibit showcases a range of predatory species across different kingdoms, highlighting their roles in sustaining biodiversity. In 1995, gray wolves (Canis lupus) were reintroduced to Yellowstone National Park, triggering a trophic cascade that regulated elk populations, restored vegetation, and increased beaver numbers. This shift improved river ecosystems and enhanced biodiversity, demonstrating the landscape-shaping power of apex predators. Owls serve as both aerial predators and bioindicators. By controlling rodent populations, they prevent agricultural damage and disease spread, while their presence—or absence—reflects ecosystem health. A decline in owl populations often signals habitat loss or pollution, emphasizing their ecological importance. In the plant kingdom, the waterwheel plant (Aldrovanda vesiculosa) is a free-floating aquatic carnivore that preys on small invertebrates like water fleas and mosquito larvae. By regulating insect populations, it potentially reduces disease vectors, showcasing plant-based predation. At the microbial level, predatory bacteria like Myxococcus xanthus and Pseudomonas aeruginosa play vital ecological roles. M. xanthus, a soil-dwelling bacterium, preys on other bacteria by swarming and secreting digestive enzymes, controlling microbial populations, and suppressing plant pathogens. P. aeruginosa, acting as a biocontrol agent, produces antimicrobial compounds that inhibit fungal pathogens and contribute to bioremediation by degrading organic pollutants. This artistic representation of predation across kingdoms emphasizes the interconnectedness of ecosystems and the unseen influence of predators. Through bacterial agar art, we contribute to STEAM and explore nature’s complexity
Privacy-Preserving Multimodal Sentiment Analysis
No full textWith the world\u27s future changing and the use of technology constantly increasing, cybersecurity professionals need to understand that it is not just the passwords or cards of their clients that are at stake anymore. With AI becoming a mainstay in the tech scene, the security risk it could pose to regular people through acts like deepfakes, or more advanced voice copying technology, is immeasurable. This is what our lab aims to fix. The Privacy Preserving Model Lab plans to use an AI model, created and trained, to encrypt picture, video, and voice sample data to increase the security of both companies and the average citizen. Today, a cybercriminal can steal your pictures and voice and use them to become you, taking full control over your online life and accounts. We focus on training our AI model to become quicker in the encryption of the data, as well as more secure. As even though the use of these sophisticated models has proven to be effective, if something slips, data we gather could unintentionally reveal personal information such as someone’s identity or location Thanks to the use of technology like the Raspberry Pi and the AI Hat+ attachment, we’d be able to test our model more rigorously, allowing for more data and stress to go into it and allowing us to see and share our progress more effectively. In today\u27s day and age, people gain access to their devices through technology like facial recognition, and people use vocal passwords for their bank. We believe that it’s better to stay ahead of any possible threat that could arise in the future, preferably making adjustments to our model when needed, than to fear not being prepared when these new types of cyber attacks eventually come