Publications

Permanent URI for this collection

Browse

Search Collection

Now showing 1 - 5 of 62030
  • Article
    Courting the Sharks: The Influence of CEO Narcissistic Admiration and Rivalry on New Venture Funding
    (INFORMS, 2025-05-12) Sanchez-Ruiz, Paul ; Blake, Andrew ; Petrenko, Oleg ; Maldonado-Bautista, Ileana ; Collewaert, Veroniek ; Artz, Kendall ; Management and Entrepreneurship
    We draw from the social psychology literature to introduce an alternative conceptualization of executive narcissism—narcissistic admiration and rivalry. In the context of chief executive officers (CEOs) pitching to investors, we theorize how narcissistic CEOs may use distinct behavioral strategies to pursue status, thereby shaping investor sentiment and ultimately affecting investors’ funding decisions. Using Shark Tank data, we find evidence that narcissistic admiration and rivalry are associated with opposing patterns in new venture funding, as shaped by investor sentiment. Specifically, CEO narcissistic admiration is positively associated with new venture funding by increasing investor sentiment, whereas CEO narcissistic rivalry is negatively associated with new venture funding by decreasing investor sentiment. These results highlight the need to separate narcissistic admiration and rivalry in executive narcissism research and illustrate the underlying mechanisms through which executive narcissism shapes organizational outcomes. Overall, this study provides new insights into two pathways of executive narcissism and offers evidence consistent with the idea that executive narcissism matters in entrepreneurial contexts.
  • Article
    Relative Pose Estimation of an Uncooperative Target with Camera Marker Detection
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-10) Candan, Batu ; Servadio, Simone ; Department of Aerospace Engineering
    Accurate and robust relative pose estimation is the first step in ensuring the success of an active debris removal mission. This paper introduces a novel method to detect structural markers on the European Space Agency’s Environmental Satellite (ENVISAT) for safe de-orbiting using image processing and Convolutional Neural Networks (CNNs). Advanced image preprocessing techniques, including noise addition and blurring, are employed to improve marker detection accuracy and robustness from a chaser spacecraft. Additionally, we address the challenges posed by eclipse periods, during which the satellite’s corners are not visible, preventing measurement updates in the Unscented Kalman Filter (UKF). To maintain estimation quality in these periods of data loss, we propose a covariance-inflating approach in which the process noise covariance matrix is adjusted, reflecting the increased uncertainty in state predictions during the eclipse. This adaptation ensures more accurate state estimation and system stability in the absence of measurements. The initial results show promising potential for autonomous removal of space debris, supporting proactive strategies for space sustainability. The effectiveness of our approach suggests that our estimation method, combined with robust noise adaptation, could significantly enhance the safety and efficiency of debris removal operations by implementing more resilient and autonomous systems in actual space missions.
  • Article
    High-velocity nasal insufflation in dogs with left-sided congestive heart failure unresponsive to traditional oxygen therapy: a retrospective case series
    (Frontiers, 2025-05-09) Lane, Bailey ; Walton, Rebecca A. ; Blong, April E. ; Hoen, Meredith ‘t ; Tropf, Melissa A. ; Ward, Jessica ; Masters, Allison K. ; Veterinary Clinical Sciences
    Objective: To describe high–velocity nasal insufflation (HVNI) for managing dogs with left–sided congestive heart failure (L–CHF) failing traditional oxygen therapy (TOT). To secondarily evaluate complications based on retrospective evaluation of the record of HVNI and survival to discharge. Design: Retrospective case series from a university teaching hospital between August 2019 and October 2021. Animals: Twelve dogs diagnosed with L-CHF and managed with HVNI. Measurements and main results: Medical records were retrospectively reviewed for signalment, point-of-care diagnostics, and HVNI information. Nine dogs were diagnosed with myxomatous mitral valve disease, and three dogs were diagnosed with dilated cardiomyopathy. All dogs in this study required HVNI after failing TOT. Dogs were treated with HVNI for a median of 14 h (range 2–22 h). HVNI was successfully discontinued in 10 dogs (83%), all of which survived to discharge. Two dogs on HVNI were humanely euthanized, both of which were diagnosed with Stage D refractory CHF. No major complications of HVNI were noted in any dogs. Conclusion: HVNI is a potential method of escalating oxygen support for dogs in L-CHF who fail TOT. In this case series, all dogs in which HVNI was successfully discontinued survived to discharge.
  • Article
    Analytical and Data-Driven Koopman Operator for the Perturbed Kepler and Circular Restricted Three-Body Problems
    (Elsevier, 2025-05-09) Hofmann, Christian ; Lavezzi, Giovanni ; Wu, Di ; Servadio, Simone ; Linares, Richard ; Department of Aerospace Engineering
    A modified version of the Extended Dynamic Mode Decomposition (EDMD) approach for the Koopman operator theory is presented, utilizing sparse-grid quadrature nodes and weights to generate the training data. Compared to standard random sampling, this method emphasizes certain regions of the state space and improves the accuracy and convergence rate of the Koopman operator while reducing the amount of required data. Additionally, we propose a QR decomposition and Koopman modes reduction to reduce the computational effort for analytical propagation. Applications in astrodynamics are considered, where atmospheric drag is included as an additional perturbation in a recently developed set of regularized orbital elements. An extensive comparison of the analytical Galerkin method and the data-driven standard and quadrature-based EDMD approaches is provided. Numerical examples for the analytical prediction of perturbed Keplerian motion and periodic orbits in the circular restricted three-body problem, and a comparison with an analytic propagator demonstrate the efficiency of the developed methods.
  • Article
    Legacy Nutrient Transport by Overland Sheet Flow
    (ASCE, 2025-05-07) Gilley, John E. ; McGehee, Ryan ; Wacha, Kenneth M. ; Department of Agricultural and Biosystems Engineering (CALS)
    The transport of phosphorus (P) and nitrogen (N) from sites containing varying quantities of legacy nutrients was evaluated in this investigation. The data that were examined were collected during four previously reported field hydrologic studies performed in eastern Nebraska. Additional flow was introduced to the top of the rainfall simulation plots to replicate runoff conditions occurring along a hillslope. It was observed that both P and N delivery were influenced by runoff rate on sites where beef cattle manure or inorganic fertilizer had been applied. Legacy nutrient delivery appeared to have been influenced by the quantity of nutrients released at a particular runoff rate and the amount of overland sheet flow available to transport the nutrients. Two hypotheses were formulated based on experimental observations. Hypothesis 1: P transport rates can be estimated from measurements of soil P content. Hypothesis 2: Linear regression equations can be used to relate total N delivery to runoff rate. Each hypothesis was affirmed using the student’s 𝑡-test. Additional assessment of the proposed nutrient transport equations is needed at other locations maintained under different management conditions.