Robert Morris University (RMU) is a private university in Moon Township, Pennsylvania. It was founded in 1921 and is named after Robert Morris, known as the "financier of the [American] revolution." It enrolls nearly 5,000 students and offers 60 bachelor's degree programs and 35 master's and doctoral programs. Most students are from the Pittsburgh area, while 16 percent of freshmen in 2018 were from outside Pennsylvania.
This research focuses on laser through transmission welding of thermoplastic materials, experimentation of thermoplastics through transmission laser welding, and a comparison with finite element (FE) modeling of the laser welding process. Thermoplastic through transmission laser welding is increasingly used in industry and manufacturing due to the precise weld location, speed of process, and quality of weld. However, thermoplastic welding parameters are often unknown or thermoplastic welding standards are undeveloped. The comprehensive objective of the experimentation and FE modeling performed in this work is to develop a relationship between melt temperature and laser energy absorption used in thermal welding of PA6 and PA66. Surface exposure experiments are performed on PA6 and PA66 samples to measure thermal profiles. FE simulations of the surface exposure testing and through transmission are completed in Abaqus to simulate the moving heat source of the laser. This work develops a novel experimental testing procedure for studying the thermal properties of PA6 and PA66 thermoplastic materials under surface exposure loading from laser energy. The significant results of this work include experimental development of surface exposure testing for PA6 and PA66 as well as a comparison between maximum temperature measurements in experimentation, simulation, and literature values for PA6 and PA66.
Succession planning (SP) has been presented as an essential practice for nonprofit organizations (NPOs) to ensure a future supply of leaders, organizational stability, and mission continuity. Despite SP's anticipated benefits, many NPOs do not implement this practice, and few studies have examined why. This study aimed to provide a more detailed qualitative exploration of NPOs' reasons for implementing or not implementing SP. Twenty senior NPO managers were interviewed about their organization's current SP practices, reasons for adoption or non-adoption, and challenges experienced or anticipated with implementing SP or developing their current SP programs. The findings demonstrate the varied approaches NPOs take to implementing SP and clarify the barriers they perceive to SP. Most organizations recognized SP's importance but also identified barriers to its application in their organization. For NPOs that did not implement SP, many preferred other options for finding leaders or did not consider SP to be their highest priority. Ten inductively identified barriers emerged that explain why NPOs do not implement SP. In practice, this study's findings may aid consultants, human resource practitioners, leaders, benefactors, and policymakers in finding ways to overcome barriers to SP or in strategically reflecting on alternative approaches to leadership succession that match with the organizations' culture, resources, or priorities.
PurposeSaudi Arabia has faced widespread gender gaps, discrimination and inequality; however, with Vision 2030, government reforms and changes in the laws, there has been improvement in women's rights. Saudi women today are better educated, more informed and have greater workforce participation. Despite these advances, women have limited opportunities to hold leadership positions. The purpose of this study, therefore, is understand how women who have attained leadership positions achieve and succeed.Design/methodology/approachIn this paper, the researchers describe Saudi women's leadership experiences as expressed in semi-structured interviews with eight women working in leadership positions. Analysis of transcripts aims to identify the challenges and supports these leaders experienced.FindingsSeveral themes emerged from the analysis: sociocultural factors, impact of societal change and supports for career development. Sociocultural factors such as the impact of religion, education, women's roles and modesty and gender mingling play a significant role in determining the success of women leaders. In addition, supports for career development such as competency for the job, role models, management support and continued professional development were identified as important to the success of these women leaders.Practical implicationsResults of this study have practical implications for educational institutions including teaching women to navigate change in the country and to self-advocate. Implications for organizations include corporate diversity and equity training and policies.Social implicationsTo implement the reforms within Vision 2030, government policies and society needed to change. This challenges traditional conservative religious ideologies. Being aware of this, the government initiated public awareness campaigns to create a supportive environment for change. These changes have impacted society, including women's roles.Originality/valueThis paper provides analysis of original data from women leaders during a time of government reform and societal change in Saudi Arabia. It discusses the significance of Islamic feminism and Vision 2030 in shaping the opportunities available to women leaders.
BACKGROUND:There is no published evidence to support the efficacy of any digital vaping cessation program for young adults (YAs) at differing levels of readiness to quit. In this pilot randomized controlled trial, we evaluated the preliminary acceptability and efficacy of a program for vaping cessation based on acceptance and commitment therapy (ACT on Vaping), delivered via a smartphone app and text messaging. METHODS:YAs aged 18-30 (n = 61) were randomized 1:1 to ACT on Vaping (n = 31) or incentivized text message control (n = 30). Outcome data were collected at 3 months post-randomization. Results were compared against a priori benchmarks for acceptability (satisfaction of ≥3.5 on 5-point scale) and efficacy relative to control (meeting at least one of three): ≥1-point difference in Contemplation Ladder change scores; ≥5 percentage difference in 24-hour quit attempts, ≥5 percentage difference in cotinine-confirmed 30-day point prevalence abstinence (PPA) from all non-therapeutic nicotine/tobacco. RESULTS:Satisfaction with ACT on Vaping averaged 3.8, exceeding the acceptability benchmark. A higher proportion of participants in the ACT on Vaping arm reported a 24-hour quit attempt (87.5% vs. 75.9%), exceeding the efficacy benchmark. Both changes in quit readiness (+0.96 in ACT on Vaping vs. +0.72 in control) and cotinine-confirmed 30-day PPA (4.2% in ACT on Vaping vs. 0% in control) were descriptively higher for ACT on Vaping but did not reach the benchmark level for efficacy. CONCLUSIONS:ACT on Vaping had promising acceptability and preliminary efficacy. A fully powered trial of ACT on Vaping is warranted to evaluate its efficacy. IMPLICATIONS:Digital interventions are a promising yet under-researched approach for reaching and supporting YAs to quit vaping. This proof-of-concept pilot randomized controlled trial evaluated a novel mobile health application and associated text messaging program (ACT on Vaping) for young adult vaping cessation and found preliminary evidence for acceptability and efficacy relative to an incentivized text message control arm, warranting evaluation in a fully powered trial as a next step. TRIAL REGISTRATION:NCT05897242.
Portfolio optimization remains a central theme in financial research, with recent advances in machine learning (ML) and computational power enabling more sophisticated forecasting models. Cryptocurrencies, characterized by extreme volatility and rapidly changing dynamics, pose particular challenges for portfolio allocation. This study proposes a novel Double Deep Transformer Q-Learning (DDTQL) framework for optimizing a portfolio of 15 leading cryptocurrencies. To the best of our knowledge, this is the first work to apply a Double Transformer-based reinforcement learning model specifically to cryptocurrency portfolio optimization, moving beyond prior studies that have combined Transformers and RL in unrelated domains. The framework leverages Reinforcement Learning (RL) within a Markov Decision Process (MDP) to derive optimal allocation strategies from historical price data, including periods of economic crisis. Empirical findings show that DDTQL consistently outperforms Long Short-Term Memory (LSTM), Multi-Output Artificial Neural Network (ANN) models, Proximal policy optimization (PPO), Markowitz portfolio optimization and a market benchmark in terms of the Sharpe Ratio. The Transformer’s attention mechanism and encoder-decoder design enable the effective modeling of long-term dependencies without requiring a recurrent structure, leading to superior predictive and decision-making performance. These results highlight the effectiveness of integrating Transformers within an RL framework for financial decision-making and portfolio allocation in cryptocurrency markets. Future research could refine Transformer architectures and incorporate additional financial and macroeconomic signals to further strengthen predictive robustness and practical applicability.
