15133 research outputs found
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Effects of Dietary PFOA on Male Zebrafish Reproductive Behavior and Success
No full textPer- and polyfluoroalkyl substances (PFAS) are emerging contaminants of concern due to associated adverse health effects and their persistence. Perfluorooctanoic acid (PFOA) is one of the most common types of this global pollutant and has been shown to impact behavior and the reproductive system. PFOA exposure is associated with changes in aggression, altered brain signaling, abnormal sperm, and testicular and prostate cancer. Zebrafish are commonly used to study toxicity of PFAS. Previous PFOA studies have typically exposed zebrafish through aqueous solutions, however, dietary PFOA is a significant exposure pathway that has been understudied. The purpose of this study is to examine how dietary PFOA exposure impacts adult male reproductive behaviors, and subsequently reproductive success. Male zebrafish were chronically exposed to either 100 ng or 1 μg of dietary PFOA over 4 weeks and assessed for morphometrics, mating behaviors, and egg fertilization at 1, 2, and 4 weeks. Results found PFOA impacted mass, body length and velocity. Males exposed to 100 ng showed the most change and had increased mass, body length, and velocity. Effects on mass, length and velocity were dependent on the dose in a non-monotonous relationship. Effects on behavior occurred at week 2, while length was impacted by week 4. Fertilization of eggs was not impacted. This study shows PFOA is still a threat to the adult life stage and dietary exposure can lead to different results than aqueous exposure
The Art of Being a Peafowl: Light in the Darkness of Gothic Literature
No full textThe Gothic genre aims at evoking terror within its audiences causing imagination to supersede rationality. Each author working in the genre has a particular way of achieving this task, but Southern and New England Gothic writers Flannery O’Connor and Shirley Jackson share the unique approach of including aspects of brightness within otherwise dark pieces of literature. Stylistically the two share similarities in how they employ these flashes of color atypical of Gothic works; however, the literary purpose for their implementation varies between the two women. O’Connor’s vivid imagery bolstered by rich colors, specifically in the short story “A Good Man is Hard to Find,” serves primarily to create an atmospheric contrast between the serene environment and horrific violence of the plot, therefore enhancing the shock and fear one feels at the violent ending by providing a standard of goodness for comparison. Jackson, especially in her novel The Haunting of Hill House, uses these bright colors to a similar effect, but it is their figurative capacity as symbols to explore the internality of her complex characters alongside their evolving relationships that takes precedence over their ability to contrast. This thesis utilizes theory on the Gothic genre, the distinctive regional subgenres of Southern and New England Gothic, and extensive biographical information as a guide to further understand the presence of brightness within these dark works
Enhancement of Offshore Wind Farms Using Geospatial Wind Data and Machine Learning in the Northeastern United States
No full textThis study investigates using satellite-based wind data and machine learning models to support offshore wind energy planning and prediction. Sentinel-1 Level 2 data was utilized to analyze wind patterns. K-means clustering reveals that 64.6% of the wind originates from the southwest, while higher speeds are more frequently recorded from the northwest during winter. Principal Component Analysis (PCA) was employed to reduce dimensionality and interpret key patterns in wind speed and power output at the Jersey-Atlantic onshore wind farm. Artificial Neural Networks (ANN), a temporal ANN, and a Convolutional Neural Network (CNN) were developed to forecast turbine power output. The CNN, which captured spatial dependencies across turbines, achieved the best overall performance, with R2 scores exceeding 0.93. Results indicate that model performance is influenced by turbine location and wind direction, reflecting the role of wake effects. This research illustrates how spatial data and machine learning can enhance wind energy forecasting and inform more effective wind farm design
Impact of urbanization on water quality and toxins in the Passaic River, New Jersey
No full textThe Passaic River is a significant water source in New Jersey which has experienced urbanization in its surrounding areas. Many citizens and scientists have grown concerns about the deteriorating water quality and increase in contamination. This research project will investigate the impact of urbanization on water quality, specifically focusing on the presence of toxins such as heavy metals and harmful algae. The research aims to determine if urbanization correlates with higher toxin concentrations in the river and to what extent these pollutants may affect the ecosystem and human health. The methodology includes researching heavy metal concentrations, nutrient levels, and algal bloom reports. Additionally, GIS mapping will be used to analyze land use change over time to draw a correlation between urbanization and pollution levels. Urbanization factors will include population density, land use change, and deforestation. Sources for urbanization data will be obtained from satellite imagery, census data, and historical land use maps. I anticipate the results to have a positive correlation between urbanized areas and higher concentration of toxins. These findings could provide valuable data to inform environmental management and urban planning decisions. This will hopefully promote cleaner water while having better public health policies in increasingly urbanized areas
Exploring the predictive utility of emotion regulation strategies on behaviorally expressed emotion dysregulation
No full textEmotion dysregulation (ED) is the inability to manage emotions presented at inadequate levels or times (Gross, 2008). Emotional challenges can increase social and behavioral difficulties (Conner et al., 2020), particularly in autistic youth, who experience higher ED rates (McDonald et al., 2024). Emotion regulation strategies (ERS) include cognitive reappraisal (CR: reframing situations to regulate emotional impact), and emotion suppression (ES: inhibiting emotion-expressive behaviors) (Brockman, 2016). However, which approach most effectively mitigates ED remains unclear, particularly for autistic youth (Cai et al., 2018). We examined differences in ERS and internalized and externalized dysregulation (i.e., dysphoria and reactivity) in neurodiverse youth. Twenty neurodiverse youth (35% autistic, Mage=12.95, SDage=1.67; 45% male; 70% White) and their parents participated in this study. Parents completed the Emotion Dysregulation Inventory, examining reactivity and dysphoria(Mazefsky et al., 2018). Youth reported use of CR and ES (Emotion Regulation Questionnaire; Gross & John, 2003). CR, but not ES, negatively correlated to reactivity and dysphoria (both b\u3c-.673, p\u3c.05). Independent t-test showed significantly more CR in neurotypical youth than autistic youth (t=3.023, p\u3c.05). Paired t-tests showed more CR than ES (t=5.778, p\u3c.001) in neurotypical youth, but no significant differences in autistic youth. Overall, children reporting more CR exhibit less reactivity and dysphoria, but autistic youth apply CR less than neurotypical children. Findings suggest that emphasis on cognitive reappraisal when addressing emotion regulation challenges through CBT may be beneficial, especially for autistic youth, who use CR less than neurotypical youth
Correlation between results of SCQ, D-KEFs and brief questionnaires as a measure of executive functioning in ASD diagnosed children
No full textAutism spectrum disorder (ASD) is associated with executive functioning (EF) difficulties (see Demetriou et al., 2018, for a recent meta-analysis). EF relates to skills including impulse control, working memory, focus, and cognitive flexibility (Diamond, 2013). As EF is a complex, multifaceted construct, it is important to use multi-method assessment that incorporates task-based measures to assess EF skills and informant surveys to assess everyday EF behaviors. Examining the association of autistic traits with multiple measures of EF in autistic youth can capture the nuanced and heterogeneous nature of cognitive profiles in autism, which can inform more tailored and effective interventions. Parents of 78 youth (Mage=11.742, SDage=2.872, 42.3% female, 53.8% male, 3.8% transgender/non-binary) reported child’s ASD symptoms (SCQ; Rutter et al., 2013) and daily EF behaviors (BRIEF-2; Gioia et al., 2018, Flexibility Scale; Strang et al., 2017). Youth were administered a task-based EF measure (DKEFS; Delis et al., 2001). SCQ scores were positively correlated with EF challenges measured by BRIEF and FS (rs\u3e.450, ps\u3c.001). Additionally, there was a strong negative correlation between SCQ scores and specific DKEFS subtests of inhibitory control, set-shifting, and cognitive flexibility (rs\u3c-.247, ps\u3c 0.033). These findings highlight how autism-related differences in social communication are closely linked to both parent-report and performance-based EF challenges. Findings underscore SCQ as a useful indicator of both autistic traits and EF challenges, capturing distinct but complementary aspects. As EF difficulties can worsen ASD symptoms, detecting these challenges early could inform more targeted assessment and intervention (Lupi et al., 2023; Skogli et al., 2020)
Composting food waste at Montclair State University: A sustainable approach to waste management
No full textThe implementation of composting food waste from residence halls at Montclair State University would be an eco-friendly and impactful system. Universities increasingly face pressure to address environmental issues and managing food waste has become a major focus for reducing campus carbon footprints. I believe that if MSU introduced a composting program aimed at diverting food waste from landfills and turning it into nutrient-rich compost for use in campus landscaping and local community gardens that the university would benefit greatly. The program would operate through compost bins located in dining halls, residence halls and common areas, with educational outreach to students and staff on the importance of reducing food waste and the positive effect of composting on the environment. My research looks into the logistics of implementing an accessible composting program, including implementing compost bins in residence halls, while also evaluating its environmental, and economic benefits; with the purpose of providing environmental education to Montclair State students. MSU would successfully reduce food waste by a significant amount, lower landfill contributions which would show economic benefit, and produce valuable compost that benefits local soil health and can be used for MSU’s community garden. Additionally, the program would increase awareness of sustainability on campus, promoting a culture of environmental responsibility. This study also addresses challenges like contamination and participation rates and offers recommendations for ongoing improvements to better the hypothetical program based on research conducted at other universities. Overall, MSU’s composting initiative could serve as a model for other universities looking to implement sustainable waste management practices and contribute to environmental health benefits and environmental preservation
Exploring connections between student engagement, social interactions, and mathematical modeling
No full textMathematical modeling is the act of employing mathematics to represent a real-world situation and using this representation to solve a problem or set of problems (Cirillo et al., 2016; Kaiser, 2017). Despite the general consensus within the mathematics education community on the importance of mathematical modeling (CCSSI, 2010; Garfunkel et al., 2019), teachers often face challenges in its enactment (Phillips, 2016; Teague et al., 2016). This poster shares an account of our experience preparing for and facilitating the enactment of a mathematical modeling activity with preservice elementary teachers. Participants were tasked with comparing relative sizes using everyday objects, a familiar context intended to enhance understanding and engagement. Following the task, we analyzed the group dynamics and communication strategies that influenced student participation and potential products of the task. Our findings indicate that effective communication and collaborative strategies significantly enhanced the modeling process, allowing for the sharing of ideas and valuing diverse perspectives. Conversely, ineffective communication hindered participation, particularly when dominant voices stifled group dynamics. The iterative nature of mathematical modeling was evident as participants revisited decisions and clarified understandings throughout the task. Our reflections underscore the critical role of social interactions in fostering a productive learning environment. This study contributes to insights regarding the facilitation of mathematical modeling activities and highlights key areas for future research, including the implications of technology in group settings and the dynamics of student interaction in mathematical problem solving
Expression and purification of dihydrofolate reductase from Wuchereria bancrofti as a potential antifolate drug target
No full textElephantiasis, also known as lymphatic filariasis, affects around a billion people in 54 countries and remains a significant worldwide health concern. Wuchereria bancrofti (Wb), the parasitic worm responsible for filariasis, depends on Dihydrofolate reductase (DHFR), the enzyme that catalyzes the conversion of dihydrofolate to tetrahydrofolate for DNA replication and cell division. DHFR is an important drug target in the treatment of cancer and bacterial infections. Due to DHFR’s central role in folate-mediated metabolism and necessity for DNA synthesis, it is a major focus in this study for the identification of potential inhibitors that could disrupt the survival and replication of Wb. An N-terminal His6-tagged construct was used to produce the enzyme in E. coli, and isopropyl β-D-thiogalactopyranoside (IPTG) was used to induce the production of the Wb DHFR enzyme. Methotrexate -agarose resin and nickel-nitriloacetic acid (Ni-NTA) were used in a two-step affinity chromatography method to purify the enzyme. To test for the presence and concentration of the purified protein, a Nanodrop at 280 nm was used to measure the protein yield. We will analyze the isolated enzyme\u27s Michaelis-Menten kinetic parameters, KM (μM) as a substrate affinity measure and kcat (s⁻¹) as the catalytic turnover rate, to gain a better understanding of the Wb DHFR active site. This research lays the foundation for targeted inhibitor screening by identifying selective antifolate compounds that could lead to effective treatments for lymphatic filariasis, potentially improving the lives of millions affected by this neglected tropical disease
Utilizing AI to revolutionize perception training for children with residual speech sound disorder
No full textWhen a speech sound disorder (SSD) extends past 8 years of age, these errors can be classified as a residual speech sound disorder (RSSD). Research has shown that production training alone may not be sufficient in resolving children’s residual speech errors and the addition of perceptual training may be necessary to build accurate representations of errored sounds. To date, perception research study outcomes have not readily translated to clinical application because of methodological challenges in creating accurate, natural-sounding, speaker-specific stimuli for children with RSSD who are unable to produce correct versions of errored phonemes. In this pilot study, 160 correct fricative productions were artificially generated from a single 10-year-old male participant with an /s/ distortion using an AI speech software program. Altered productions were combined with 213 naturally-produced /s/ stimuli from the same participant, included in a listening task for source differentiation (AI vs. natural) and accuracy ratings using blinded listeners. The project investigates the use of AI stimuli to create speaker-specific, personalized stimuli for perceptual training modules to enhance intervention outcomes. Preliminary ratings reveal an \u3e80% correct rating match for AI stimuli based on group average. Average rater accuracy for sound source identification of AI stimuli was slightly greater than chance at 56%. Listeners’ inability to definitively discriminate AI stimuli from natural speaker specific stimuli provides preliminary justification for investigating the use of AI generated stimuli for auditory training as a clinical tool for improving perceptual accuracy of fricatives in children with RSSD