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   https://doi.org/10.1016/j.actamat.2021.117077  

   Zhong, Wei; Zhang, Qiaofu; Zhao, Ji-Cheng (August 2021, Acta Materialia)

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2. A Dual‐Purpose Model for Binary Data: Estimating Ability and Misconceptions

   https://doi.org/10.1111/jedm.12383  

   Ma, Wenchao; Sorrel, Miguel A.; Zhai, Xiaoming; Ge, Yuan (January 2024, Journal of Educational Measurement)

   Abstract Most existing diagnostic models are developed to detect whether students have mastered a set of skills of interest, but few have focused on identifying what scientific misconceptions students possess. This article developed a general dual‐purpose model for simultaneously estimating students' overall ability and the presence and absence of misconceptions. The expectation‐maximization algorithm was developed to estimate the model parameters. A simulation study was conducted to evaluate to what extent the parameters can be accurately recovered under varied conditions. A set of real data in science education was also analyzed to examine the viability of the proposed model in practice. 

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3. A Phase-Field Model for In-Space Manufacturing of Binary Alloys

   https://doi.org/10.3390/ma16010383  

   Ghosh, Manoj; Hendy, Muhannad; Raush, Jonathan; Momeni, Kasra (January 2023, Materials)

   The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface. 

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4. Measurement errors in the binary instrumental variable model

   https://doi.org/10.1093/biomet/asz060  

   Jiang, Zhichao; Ding, Peng (November 2019, Biometrika)

   Summary Instrumental variable methods can identify causal effects even when the treatment and outcome are confounded. We study the problem of imperfect measurements of the binary instrumental variable, treatment and outcome. We first consider nondifferential measurement errors, that is, the mismeasured variable does not depend on other variables given its true value. We show that the measurement error of the instrumental variable does not bias the estimate, that the measurement error of the treatment biases the estimate away from zero, and that the measurement error of the outcome biases the estimate toward zero. Moreover, we derive sharp bounds on the causal effects without additional assumptions. These bounds are informative because they exclude zero. We then consider differential measurement errors, and focus on sensitivity analyses in those settings. 

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5. Optimal Parallel Algorithms in the Binary-Forking Model

   https://doi.org/10.1145/3350755.3400227  

   Blelloch, Guy E.; Fineman, Jeremy T.; Gu, Yan; Sun, Yihan (July 2020, ACM Symposium on Parallelism in Algorithms and Architectures)