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  1. Free, publicly-accessible full text available April 1, 2025
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  6. The Academy of Engineering Success (AcES), a summer bridge program for incoming first-time freshmen (FTF) engineering students at West Virginia University (WVU), faced challenges in recruiting underserved students for years. To address this issue, research was conducted via a collaboration among faculty in engineering and business, with support from an undergraduate researcher and faculty in the Center for Excellence in STEM Education. A mixed methods study using surveys and interviews was designed to assess recruitment communication channels and student awareness of AcES and another university-level trip-based summer program to explore any misalignment and propose suggestions to improve future recruitment of diverse students. Results from 91 survey responses and 2 interviews are discussed. This paper also describes how cross-disciplinary non-tenure track faculty collaborated on engineering education research. 
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    Free, publicly-accessible full text available July 30, 2024
  7. Abstract

    There exist linear relations among tensor entries of low rank tensors. These linear relations can be expressed by multi-linear polynomials, which are called generating polynomials. We use generating polynomials to compute tensor rank decompositions and low rank tensor approximations. We prove that this gives a quasi-optimal low rank tensor approximation if the given tensor is sufficiently close to a low rank one.

     
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  8. In addition to scientific questions, clinical trialists often explore or require other design features, such as increasing the power while controlling the type I error rate, minimizing unnecessary exposure to inferior treatments, and comparing multiple treatments in one clinical trial. We propose implementing adaptive seamless design (ASD) with response adaptive randomization (RAR) to satisfy various clinical trials’ design objectives. However, the combination of ASD and RAR poses a challenge in controlling the type I error rate. In this paper, we investigated how to utilize the advantages of the two adaptive methods and control the type I error rate. We offered the theoretical foundation for this procedure. Numerical studies demonstrated that our methods could achieve efficient and ethical objectives while controlling the type I error rate. 
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