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A Fleet-Level Condition-Based Robust Optimization Framework For Manufacturing & Energy Systems
No full textThis study introduces a new generation of optimization models that inherently capture degradation dynamics and dependencies in multi-asset systems. In both industrial and power system applications, effective operations and maintenance (O&M) decisions require the integration of economic and degradation dependencies, which significantly impact system performance and asset lifetime. We propose robust optimization frameworks that embed sensor-driven degradation models into optimization models, allowing us to monitor and control degradation processes within the optimization model. These models seamlessly integrate predictive degradation models with optimization models, offering a comprehensive approach to optimizing O&M strategies across complex systems. In the first part, we focus on multi-asset industrial systems, where degradation interactions between assets and operational stress affect the lifespan of assets. Our framework models these dependencies, leveraging sensor data to optimize production, maintenance schedules, and failure risk management. We extend this work to power systems, where the integration of renewable energy and distributed generation introduces operational variability, leading to frequent start/stop cycling that accelerates asset degradation. Our extended model incorporates start/stop cycling as a key factor in degradation rates, optimizing unit commitment and maintenance schedules in dynamic power grid environments. Real-world computational experiments validate the advantages of this framework, highlighting its ability to balance lifetime utilization, failure risks, and operational efficiency in both power system applications
Informing The Police About Gait: A Simulation Study Of Driving While Under The Influence (dui).
No full textAlcohol intoxication impairs gait and balance, increasing the risk of accidents. While traditional field sobriety tests (FSTs) can be useful in road-side assessment, their subjectivity lacks the precision require to provide detailed insights into spatio-temporal gait parameters. This study aimed to evaluate the effects of simulated intoxication—using Drunk Busters Goggles—on spatio-temporal gait parameters in healthy adults across multiple walking conditions. Additionally, the study explored the relationship between self-reported cognitive failures and balance confidence with objective gait performance.
A total of 40 healthy participants completed walking tasks on the GAITRiteTM Walkway System both with and without the goggles. Gait parameters analyzed included distance, ambulation time, velocity, step count, cadence, step and stride length, stride velocity, and single- and double-support times. The Cognitive Failures Questionnaire (CFQ) and the Activities-specific Balance Confidence (ABC) Scale were administered.
Results showed significant main effects of simulated intoxication and walking condition on all gait parameters. Wearing the goggles led to increased distance, ambulation time, step count, and single-and double-support time, and decreased velocity, cadence, step length, and stride length and velocity, indicating a conservative gait strategy under impairment. No significant interaction between intoxication and walking condition was observed, suggesting gait alterations were consistent regardless of task complexity. Furthermore, no significant correlations were found between subjective measures and objective gait metrics.
These findings may support the application of Drunk Busters Goggles in simulating alcohol-related gait impairments and highlight the potential utility of quantitative gait analysis to supplement traditional FSTs. The consistent gait changes across single- and dual-task conditions may underscore the widespread and pronounced effect of intoxication on gait. The absence of significant correlations between subjective and objective measures may be partly attributed to the use of a healthy, non-clinical sample. Additionally, the CFQ and ABC Scale are general measures of everyday cognitive mistakes and balance confidence, which may not reflect participants’ perceptions during or immediately after the gait tasks. Future research should extend to older and clinical populations, and controlled alcohol administration to replicate the physiological and cognitive effects of intoxication and explore real-world applications of objective gait assessment
A Virtual Reality-Driven Approach For Collaborative Human-Robot Interaction
No full textThis dissertation addresses the critical challenge of enabling robots to effectively understand and anticipate human behavior in shared workspaces, a cornerstone of Industry 5.0\u27s human-centric manufacturing. The research developed and evaluated a Virtual Reality (VR)-driven framework for collecting high-fidelity human movement data and applying advanced neural network models for human intention recognition and trajectory prediction.The study pursued three main objectives. First, an immersive VR platform was developed for capturing detailed human movements in simulated manufacturing tasks. An unsupervised classification framework (Dynamic Time Warping and k-means clustering) demonstrated the platform\u27s utility for initial intention analysis, achieving an average accuracy of 85%. Second, supervised deep learning models were investigated for robust human intention recognition. Using VR-collected data, Convolutional Neural Networks (CNNs), hybrid CNN-Long Short-Term Memory (CNN-LSTM) networks, and CNN-Transformer models were trained. The CNN-Transformer model significantly outperformed others, achieving near-perfect F1-scores (0.998) for classifying seven manufacturing-related activities, affirming the potential for high-accuracy intention recognition. Third, a framework for indoor human trajectory prediction was devised. Neural network models trained on diverse walking patterns were evaluated using Average Displacement Error (ADE) and Final Displacement Error (FDE). The CNN-LSTM and CNN-Transformer models demonstrated promising accuracy in forecasting future human positions, crucial for proactive robot navigation. Key contributions include: (1) a validated VR-driven platform for HRI research; (2) novel unsupervised and supervised learning frameworks for intention recognition, with exceptional performance from the CNN-Transformer model; (3) an effective neural network-based framework for human trajectory prediction; and (4) rich datasets and methodological insights for VR-based HRI studies. This work advances collaborative robot capabilities, fostering safer, more intuitive, and efficient human-robot partnerships. Future work will target real-world deployment, model generalization, and richer contextual understanding
A Randomized Controlled Trial Of A Novel Instagram Intervention Targeting Alcohol Use And Binge Drinking
No full textHeavy alcohol use is associated with serious mental and physical healthconsequences that result in billions of dollars in health care expenditures each year. Heavy alcohol use is particularly common among young adults, 40% of whom report past-month binge drinking and 15% of whom meet criteria for an alcohol use disorder (Schulenberg et al, 2021; SAMHSA, 2024). However, despite these high prevalence rates and the significant consequences associated with problem drinking, the vast majority of young adults never seek treatment; many citing barriers such as cost, time constraints, stigma, and the belief that treatment is unnecessary (SAMHSA, 2024). Social media is widely and frequently used by young adults and may therefore provide an ideal platform for alcohol interventions. To date, however, very few empirical studies have tested the effects of social media-based alcohol interventions, and those that have, have used Facebook, a platform with diminishing popularity among young adults.
The current study tested an Instagram-based binge drinking intervention amongyoung adults by building on pilot work and using a community-based, young adult sample, a randomized controlled design, and a 10-week follow-up assessment. Results show support for small-to-moderate intervention effect on past-month drinking, including total number of drinks, drinking days, and binge drinking days, as well as readiness to change. The intervention was also associated with decreases in frequency of use of protective behavioral strategies. There is no evidence of effect on positive/negative affect, alcohol related consequences, or mindfulness practices. Limitations and future directions are discussed
Mitochondrial Genome Analysis of the Late Bronze Age Andronovo Population in Central Tianshan, Xinjiang
Get PDFThe Andronovo Culture, which originated from the Sintashta Culture, played a significant role in the migration of populations across the Eurasian steppe. The Tianshan Mountains, situated at the eastern end of Eurasian steppe, became the main distribution area of Andronovo culture in Xinjiang during the Late Bronze Age (LBA). To investigate the genetic structure, genetic diversity, and possible migration routes of the Late Bronze Age Andronovo population, we conducted mitochondrial genomes analysis on 12 individuals excavated from the Shihuyao cemetery in the Central Tianshan of Xinjiang. The results revealed that Shihuyao population exhibited high genetic diversity, and a close genetic affinity with Western Steppe cultural populations, particularly the Sintashta cultural population. Meanwhile, the presence of the South Asian lineage M2c, as well as the Eastern Eurasian lineages C1e and Z1, indicated genetic linkages among the Bactria–Margiana Archaeological Complex (BMAC) populations, the Northern Eurasian populations/indigenous populations, and the Andronovo culture populations. Our findings enhance the understanding of the Andronovo culture’s spread in Central Tianshan and its impact on the genetic structure of local populations
Celebrating the 70th Anniversary of Merrill-Palmer Quarterly
No full textThe 2024–2025 academic year is the 70th anniversary of Merrill-Palmer Quarterly: Journal of Developmental Psychology. This significant milestone presents an opportunity to honor the journal’s history, scholarly contributions, and mission to share scientific discoveries. The purpose of this article is to announce this milestone; provide a review of the journal’s history, including the key events and individuals involved in its establishment and ongoing success; and give an overview of the journal’s publication record. Additionally, a brief summary of the contents of the 70th anniversary issue is included
Historical and Contextual Variations in the Association Between Gender Role Adherence and Well-Being: Revisiting an Early Essay From the Merrill-Palmer Quarterly
No full textIdeas discussed in R. E. Hartley’s essay published in the Merrill-Palmer Quarterly in 1960 were reconsidered in a study of the associations between measures of gender role identity and self-perceptions of well-being in two samples (Ns = 710 and 325) of older school-age participants from lower middle-class and upper middle-class neighborhoods in Montreal, Canada, and Barranquilla, Colombia. One sample was collected in 2002; the other, in 2017. The central concern of Hartley’s essay was the consequence of historical changes in adherence to traditional gender role prescriptions. The current study participants rated items adapted from the Bem Sex Role Inventory to measure sensitivity/femininity and assertiveness/masculinity and completed a measure of self-perceived social competence and general self-worth. Two critical findings were observed. First, there was a time-related increase in sensitivity/femininity for upper middle-class participants from Montreal and a time-related decrease in assertiveness/masculinity for lower middle-class participants. Second, in both samples, the mean scores on the two measures of well-being were higher for children who were identified as androgynous than for children who were sex-typed. These findings replicate previous results and confirm Hartley’s observations described in the Merrill-Palmer Quarterly seven decades ago
Sexual and Reproductive Healthcare Perceptions Among Arab-American Women: Implications for Gynecological Health Outcomes
Get PDFThis literature review analyzes the sexual and reproductive healthcare perceptions of Arab-American (AA) women living in the United States and how this impacts the prevalence of gynecological diseases. Sexual health is viewed promiscuously within the AA population and is generally reduced to the physical act of intercourse. It is considered either an agent of sexual desire or a means to reproduce. This dichotomy overlooks aspects of gynecological health within a broader framework. This attitude is evident in the minimal utilization of preventative screenings and increased rates of sexually transmitted infections (STIs) and gynecological cancers. Consequently, this narrow view of sexual health perpetuates a cycle of neglect, leaving critical aspects of women’s health unaddressed and contributing to adverse long-term outcomes.
Arabs in Michigan generally face poorer health outcomes than the broader population, particularly in women’s health and prevention. Studies show lower rates of STI testing and general understanding of gynecological health. Furthermore, screening rates for breast cancer and gynecological cancers are low. Contributing factors include limited education, religious fatalism, lack of spousal support, and cultural stigma. Additionally, because AA women are often grouped under a broad demographic category, specific health statistics are largely unknown, preventing recognition of their unique experiences.
The sexual and reproductive healthcare perceptions of AA women result in lower utilization of screenings, higher rates of gynecological diseases, and a limited understanding of sexual health. Addressing these issues requires a culturally competent approach that considers the unique experiences of AA women
Cracking the Code: Enhancing SDOH Documentation with ICD-10-CM Z codes
Get PDFIntroduction: Social determinants of health (SDOH) have a large impact on health outcomes with the World Health Organization (WHO) estimating that SDOH accounts for nearly 30-55% of patient health outcomes. Addressing SDOH especially in primary care clinics can lead to reduced barriers to care and improvement in health outcomes. At WSUSOM, there is curricular emphasis on gaining knowledge of SDOH, but this does not always translate to clinical practice. Currently, ICD-10-CM Z Codes are being used to report SDOH and other factors influencing patients’ health status. We would like to investigate how SDOH is currently being documented and create an intervention to improve documentation practices and the usage of ICD-10-CM Z codes. Methods: A retrospective chart review will be conducted at the GMAP clinic at University Health Center to establish baseline frequency of SDOH documentation and Z Code usage. The review will analyze components of social history, resources provided, common diagnoses associated with Z codes, relevant demographics, etc. An intervention will be created for resident physicians, including a training session and educational material to improve understanding and utilization of Z codes. Patient charts will be reviewed from clinic appointments after the intervention to assess changes in documentation practices. Results: Researchers hypothesize that the intervention will improve SDOH documentation practices and increase the use of ICD-10 CM Z codes at the GMAP clinic. Conclusion: This study will ultimately address how to better mitigate barriers to care due to effects of SDOH by improving documentation practices in the primary care setting