The Impact of Sleep Apnea on Conventional Doppler Indices

AbstractObjectiveTo prospectively explore the impact of obstructive sleep apnea (OSA) on conventional Doppler indices and to identify possible negative prognostic factors for left ventricular diastolic dysfunction. Materials and Methods: All included subjects had overnight polysomnog-raphy. All subjects underwent a comprehensive echocardiography examination to evaluate systolic and diastolic function of the left ventricle. A multiple logistic regression model was created to identify potential negative prognostic factors for left ventricular dysfunction.ResultsA significant decrease in the ratio of early and atrial mitral flow velocity (E/A ratio) in OSA patients was found. Patients with moderate-to-severe OSA had a significant increase in the odds ratio for development of an abnormal E/A ratio (p=0.014, multivariate logistic regression). There was a significant negative correlation between E/A ratio and apnea-hypopnea index (p = 0.01). Non-obese OSA patients and obese-OSA patients carried significantly increased odds ratios for the development of a reduced E/A ratio (p = 0.02 and 0.038, respectively).ConclusionSubjects with OSA had reduced mitral E/A ratios, which implies possible impaired diastolic heart function. Further study to reverse impaired diastolic function via lifestyle modifications and treatment with nasal continuous positive airway pressure or surgery is warranted

Maximizing Friend-Making Likelihood for Social Activity Organization

The social presence theory in social psychology suggests that computer-mediated online interactions are inferior to face-to-face, in-person interactions. In this paper, we consider the scenarios of organizing in person friend-making social activities via online social networks (OSNs) and formulate a new research problem, namely, Hop-bounded Maximum Group Friending (HMGF), by modeling both existing friendships and the likelihood of new friend making. To find a set of attendees for socialization activities, HMGF is unique and challenging due to the interplay of the group size, the constraint on existing friendships and the objective function on the likelihood of friend making. We prove that HMGF is NP-Hard, and no approximation algorithm exists unless P = NP. We then propose an error-bounded approximation algorithm to efficiently obtain the solutions very close to the optimal solutions. We conduct a user study to validate our problem formulation and per- form extensive experiments on real datasets to demonstrate the efficiency and effectiveness of our proposed algorithm

Teaching Business Intelligent with an Executive Dashboard

Data visualization has been an important tool for company executives to obtain timely information for decision making purposes. This tutorial session use a state-of-art executive dashboard system to showcase how data visualization can be presented in a classroom environment. Sample cases and datasets are available for participants to take home for their own teaching purposes

Sharing is the Key to Create a Community of Learning in Higher Education

Web 2.0 technologies have been wildly used in pedagogical design. It is eminent to adopt a new way of teaching and learning in the higher education environment. This paper advocate that “Sharing” is the essence of this new paradigm shift. We borrow from the Community of Learning theory and try to argue that content sharing within the faculty members, between faculty members and students, and among students are one important element to deliver high quality education. We also use our experience of designing an undergraduate MIS course to share a few techniques of using Web 2.0 technology in the classroom, virtual or on the ground

How Employee Use of Generative Artificial Intelligence Affects Self-Evaluation: Investigating Implications for Job Insecurity and Career Commitment

This research delves into the transformative influence of Generative Artificial Intelligence (GenAI) on the self-evaluation processes of employees within contemporary organizations. In an era marked by rapid technological advancements, the integration of AI into various facets of the workplace is reshaping traditional paradigms. We use Self-Evaluation Maintenance (SEM) Model, which is our theoretical lens, and combining with the concept of Core Self-Evaluation (CSE) to conduct our research model. This study seeks to elucidate whether the usage of GenAI, specifically in the context of performance compares to GenAI, and then the impact on CSE, which we plan to use in this research, has discernible effects on how employees perceive and evaluate their own contributions. In addition, we adapt various reliable scales to assess the constructs in our research model. This research employs surveys and content analysis of questionnaire data to investigate the perceptions of employees in organizations that have introduced GenAI-driven tools for performance appraisal. The objective is to determine whether these tools, by providing real-time feedback, personalized recommendations, and novel evaluation metrics, result in changed self-perceptions and attitudes towards one\u27s work