24067 research outputs found
Sort by
Pathways to Possibilities
Get PDFPathways to Possibilities explores the importance of establishing a Montessori Pre-K through 8th grade school for a large population of children, highlighting the unique challenges they face in accessing an education that meets their fundamental needs. By incorporating Montessori design principles and learning theories, the proposed school aims to create an inclusive, supporting environment that fosters self-directed learning, creativity, and social engagement. It advocates expanding the Montessori model to a larger school that fosters an inclusive environment that supports diverse students’ need
Optimized Purification and Activity Analysis of Endothelial Nitric Oxide Synthase (eNOS, NOS3)
No full textEndothelial nitric oxide synthase (NOS3, also known as eNOS) plays a crucial role in vascular health by synthesizing nitric oxide (NO), which regulates vascular tone, blood pressure, and endothelial function. Despite its significance, producing active NOS3 for biochemical studies remains challenging. We developed an optimized protocol to yield full-length NOS3 in a highly purified and active state, validated by SDS-PAGE and spectrophotometric analysis. NOS3 is as a substrate of p38 alpha, we tested the ability of wild p38 alpha and two binding site variants to phosphorylate NOS3. Differential phosphorylation patterns enable us to predict the areas on p38 alpha that are likely to be physiologically relevant to the intracellular binding of NOS3 and p38. The successful purification of active NOS3 opens new avenues for investigating its structure-function relationships, regulatory mechanisms, and potential therapeutic applications in cardiovascular diseases. This optimized protocol provides a reliable means of obtaining recombinant NOS3 suitable for detailed biochemical and functional studies. Purified protein will facilitate future studies on NOS3 regulation and its role in endothelial health and vascular homeostasis. Our future research aims to elucidate the relationship between NOS3 and Sirtuin 6 (SIRT6), an NAD+-dependent deacetylase, to understand how SIRT6 modulates NOS3 function and its implications for endothelial health
Modeling potential effects of ocean acidification on shell formation in Pacific oyster (Crassostrea gigas)
No full textAs the climate changes and oceans become warmer, ocean waters are becoming increasingly acidified from their historical pH near 8, with a low of 7.8 expected by 2100. This phenomenon of ocean acidification is caused by atmospheric CO2 dissolving into ocean water, with which it reacts to form carbonic acid. Increasing acidity interferes with the ability of many marine fauna to construct shells and exoskeletons from CaCO3. Because of this, ocean acidification poses a serious threat to many shell-forming marine species and understanding that threat will be vital to conservation efforts. Predictive models for how ocean acidification will affect marine species, such as coral reefs and mussels, currently exist and are crucial areas of research. One such species is the Pacific oyster Crassostrea gigas, the most cultivated oyster in the world, which supports a $7.5 billion per year industry worldwide. We investigated how ocean acidification may impact oyster harvests under different climate change scenarios. We hypothesized that the projected ocean pH changes would impact oyster harvests because of the detrimental effects of reduced pH on shell formation and maintenance. To test this hypothesis, we constructed dynamic energy budget (DEB) models of mussel growth and maintenance and parameterized them for C. gigas. We then ran these models under different ocean pH scenarios defined by data from the Ocean Carbon and Acidification Data System, built by the National Centers for Environmental Information (NCEI). These pH scenarios are derived from two different climate scenarios, the Shared Socioeconomic Pathways (SSP) 245 “middle of the road” scenario with some mitigation and the more severe SSP585 “fossil fueled development” scenario. Our findings have the potential to inform the sustainability of these ecologically and economically important marine animals
Breaking the System: Tricking Generative AI/LLMs
No full textBreaking the System: Tricking Generative AI/LLMs This research examines various ways to “trick” generative artificial intelligence (AI) and large language models (LLMs) into revealing that they are AI/LLMs rather than humans responding. The goal is to develop methods for detecting AI-generated content in human-requested tasks and interactions with webpage elements through techniques known as “red teaming” and “adversarial prompting.” Red teaming is defined as “a way of interactively testing AI models to protect against...toxic, biased, or factually inaccurate generation. Adversarial prompting is defined as inputting prompts to “exploit weaknesses in LLMs, leading them to produce harmful, misleading, or unintended outputs,” (Martineau 2025; Kumar, 2024). Across multiple LLMs such as ChatGPT, Grok, LLaMA, Claude, and Microsoft Copilot, we tested this by presenting identical prompts to analyze similarities and differences in response patterns. To do so, we familiarized ourselves with the various platforms to determine successful methods. We piloted prompts with various languages such as Pig Latin, Telugu, and German. We then experimented with different fonts and punctuation such as Wingding\u27s, Morse Code, and Ascii Code. Emojis placed within a string of randomized characters were used to test response times of the LLMs in identifying the specified emoji given in the prompt. Minor adjustments made to an image resulted in incorrect categorization of the cropped or inverted image in ChatGPT, LLaMA and Microsoft Copilot. We found that when prompted with indefinite text prompts, every model produced different amounts of string repetitions. Findings suggest that red teaming and adversarial prompting can generate differences in AI/LLM responses that may lead to successful detection. However, due to rapid advancements of this technology, these approaches will need to continuously be refined and tested. Through further research, we plan to explore additional specific and targetable prompting methods that could potentially elicit LLM responses and patterns
Examining novel bacteriophage against Staphylococcus species
No full textViruses are infectious microbes containing DNA or RNA within a protein coat. They are nonliving and require a host to replicate. Bacteriophages are viruses that utilize bacteria as a host organism. Bacteriophages are highly selective and do not infect human cells; they only target disease-causing bacteria and do not disrupt the body’s normal microbiome. Antimicrobial resistance jeopardizes the ability to treat bacterial infections. As such, it is necessary to explore new treatment options, such as phage therapy. Currently, bacteriophages are only used to treat disease in situations where all other options have been exhausted. More information is needed for phage therapy to become more widespread and available for use in healthcare settings. KSU alumnus Ross Wood processed samples from opossum intestines and isolated a bacteriophage, which he named MRSAΦOPP. He hypothesized that through interactions with humans and human waste, opossums may encounter pathogens and phages that could be relevant to modern medicine. His preliminary findings show that the phage shows some lytic activity in S. aureus and Enterococcus species. This project aims to expand on Ross’ research with MRSAΦOPP and examine its ability to infect and lyse an array of Staphylococcus species (S. aureus, methicillin-resistant S. aureus, S. intermedius, and S. saprophyticus). A spotting assay will be used to determine the effect of the phage on a host. The host species is mixed with molten top agar and poured onto LB plates to grow a bacterial lawn. The bacteriophage is serially diluted and spotted directly onto the lawn. If the phage successfully infects and kills the host, plaques, areas of dead bacteria, will form. Findings thus far indicate that the phage MRSAΦOPP effectively lyses MRSA and S. aureus. Further research to characterize and type phage MRSAΦOPP will be conducted in the upcoming weeks
Investigation of the Flexural Strength Capacity of Concrete Made with Steel Fiber, Glass Powder and Fly Ash as Partial Replacement of Cement
No full textSteel Fiber Reinforcement is used to improve durability and toughness in concrete. Using steel fiber in production of concrete could eliminate the need for steel reinforcing and has potential to reduce CO2, which is important for producing environmentally friendly concrete. Cracking and fracturing under dynamic load could be prevented with enhancing the durability of concrete. Flexural Strength Capacity of Concrete depends on different variables, such as concrete mixture, compressive strength, cracking… Traditional concrete has flexural strength of 400-700psi (2.76 MPa-4.83 MPa) determined using a 3-point bending test, simulating the loading of the vehicle on the slab. The goal of this project is to produce high quality concrete mixture which could be resistant to dynamic loads. This work presents current progress toward developing concrete mixture design resistant to dynamic loads, which is important for pavement design. A 3-point bending test will be utilized at Kennesaw State University in order to determine the difference between the flexural strength capacity of reinforced concrete and flexural strength capacity of concrete fabricated using Fiber Glass Rebars. Concrete beams with square cross section 6in x 6in and 5ft (15cm x 15cm x 1.67m) length will be cast at Kennesaw State University using the same concrete mixture design and different type of rebars. Deflection of the beams will be measured using dial indicator
Developing Glycine-rich Peptide Therapeutics Targeting Alpha-Synuclein Aggregation in Parkinson Disease
No full textVarious neurodegenerative conditions like dementia, Alzheimer’s disease (AD), and Parkinson’s disease (PD) cannot be easily treated using current medical technology. Currently, over 55 million individuals suffer from dementia worldwide, with more than 10 million new cases diagnosed every year. The impact of dementia extends far beyond the individual, affecting also the lives of their families, friends, and caregivers by causing memory loss, behavioral changes, and social reclusion, which progressively get worse over time. In recent studies, scientists have uncovered a link between alpha-synuclein (α-syn) and Parkinson’s disease. The misfolding and aggregation of alpha-synuclein, often called Lewy Bodies (LB), is extremely hard to exterminate, which suggests for a new therapeutic strategy. As a result of their high target specificity and potency, peptide therapeutics are designed to bind specifically to certain proteins or receptors, leading to enhanced efficacy, a disadvantage of small molecules. Furthermore, their amino-acid-based structure minimizes the risk of eliciting an immune response. This study aims to design glycine-rich peptide analogs to inhibit alpha-synuclein aggregation. By utilizing alpha-fold, 3D models of the ten peptide analogs were created. Subsequently using the molecular docking, the binding affinity of each of these analogs was determined. Among these analogs, one analog was synthesized using the solid phase synthesis protocol. In this protocol, high swelling rink amide resin with a loading capacity of 0.6 mmol/g and 100-200 mesh size was used. The peptide-resin complexes were cleaved, filtered and precipitated. Then, the precipitate dissolved with 10% acetic acid and lyophilized overnight to form peptide powders. The peptide was characterized by mass spectrometry. One intense peak was noticed at m/z 503.3 which corresponds to [M+2H]2+, change states which exactly agreed with the theoretical masses. For further studies, biological assay using LCMS and FRET will be employed to measure the inhibition efficiency of these peptides
Beyond Memorization: A Cognitive Psychology-Based Framework for AI Intelligence Assessment
No full textTraditional AI evaluation methods often fail to measure true intelligence due to their reliance on datasets easily incorporated into training regimes. As a result, many AI systems achieve inflated scores not by demonstrating genuine understanding but by recognizing patterns in previously encountered data. Recent research, including Apple’s study introducing GSM-Symbolic, underscores this issue and highlights the need for more robust testing frameworks. This project proposes a novel AI assessment methodology based on cognitive psychology, designed to evaluate intelligence beyond memorization and pattern recognition. Instead of relying on static datasets, our framework will present AI systems with dynamic, open-ended problems that test critical thinking, creativity, and ingenuity. These tests will incorporate principles from human intelligence research, such as problem-solving under novel conditions, generating original ideas, and adapting strategies when faced with unexpected challenges. Unlike existing benchmarks, which often evaluate AI on deterministic tasks with predefined solutions, our approach will focus on qualitative and emergent problem-solving abilities. Key research objectives include designing test scenarios that effectively differentiate between statistical inference and genuine reasoning, developing metrics for evaluating AI performance on open-ended tasks and validating the framework across various AI models. The results of this study could provide a standardized methodology for assessing machine intelligence in a way that is resistant to data contamination and memorization-based inflation. By shifting the focus from recall-driven benchmarks to adaptive reasoning and creativity, this framework aims to establish a more accurate measure of artificial intelligence, contributing to both theoretical and practical advancements in AI evaluation
Alanine-based Temporin L Peptide Analogs to Inhibit Viral Replication in SARS-CoV-2
No full textThroughout the past several years, Covid-19 has taken a heavy toll on people’s health. Although small molecule drugs and vaccines have made an impact to improve patients’ immunity and have served preventative measures, relatively new peptide therapeutics is gaining popularity. Small molecule drugs often lack having specific target functions, cause unwanted complications, and drug resistance. However, peptide therapeutics are gaining in popularity due to their impeccable specificity, high potency, and fast approval process. The goal of this research project is to develop effect and potent analogs of Temporin L (TL) peptide to block the catalytic sites including Cys145 and His41 of the main protease of SARS-CoV-2. Utilizing computer aided design, 12 analogs were modelled incorporating alanine sequentially in the 12 positions of TL peptide. All analogs underwent molecular docking using HDOCK program to evaluate the binding energies against the main protease. The best three analogs (analog 3, 4, and 9) were evaluated by molecular dynamic modeling using YASARA software. The results were analyzed that reveal the radius of gyration, RMSD, solvent accessible surface area, and RMSF for each of the three analogs to compare their effectiveness. The best analog 3 was synthesized using the solid phase synthesis protocol using a rink-amide resin. Once the peptide synthesis is completed, the resin was removed by adding a high percentage of trifluoracetic acid (TFA). Subsequently, peptide solution was filtered and TFA was removed by blowing nitrogen and precipitated by adding iced-cold diether ether. Through a freeze-drying process, the peptide powder was created. Mass spectrometry was employed to confirm the mass of the synthesized peptides which showed two intense peaks at m/z 542.67 and 813.50 corresponding to [M+3H]3+ and [M+2H]2+, charge states, respectively. The inhibiting efficiency of this analog will be tested using FRET and LCMS based protease assays
Empathy Through Play: Exploring the Prosocial Potential of Video Games
No full textAs video games continue to evolve, so too do discussions about their psychological impact on players. While much attention has been given to the debate over whether video games incite violent tendencies, far less research has explored the opposite possibility: that games can foster empathy. The Game Narrative Lab seeks to address this gap by designing and studying games that promote prosocial behavior.
Our work centers on creating innovative, narrative-driven games that inspire empathy and kindness in players. This process involves collaboration across disciplines, with writers, artists, developers, and researchers crafting experiences that challenge dominant narratives about games and their societal effects. The art, narrative, and development teams are currently working on a game project called Alley Cat, where players play as a cat who has to help other animals in unfortunate situations. To inform our designs, we are conducting a study using Corporation Incorporated, a game developed in our lab and published by the KSU Game Studio, that explores the challenges faced by an immigrant adjusting to life in America.
Our research challenges persistent misconceptions about video games by demonstrating their potential as tools for empathy-building rather than sources of aggression. Through this work, we aim to recontextualize games as an interactive medium capable of fostering meaningful social change—one that not only entertains but also deepens players’ understanding of others