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Creators/Authors contains: "Li, Wei"

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  1. Free, publicly-accessible full text available June 1, 2026
  2. Abstract For efficient roll-to-roll (R2R) production of flexible electronic components, a precise R2R transfer peeling process is essential, requiring accurate modeling and control. This paper introduces a novel approach to confining the dynamics of a nonlinear R2R mechanical peeling system within a convex set known as a norm-bounded linear differential inclusion (NLDI). This method utilizes constraints on uncertain system variables to create a tighter NLDI representation compared to other convexification techniques. Moreover, it offers drastically reduced computational cost compared to previous methods applied to convexify the R2R peeling system. The NLDI is employed to generate an H∞-optimal controller for the R2R peeling system, and both simulations and experiments demonstrate better dynamic performance compared to other controllers for R2R transfer. 
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    Free, publicly-accessible full text available May 1, 2026
  3. Abstract Roll-to-roll (R2R) manufacturing is a highly efficient industrial method for continuously processing flexible webs through a series of rollers. With advancements in technology, R2R manufacturing has emerged as one of the most economical production methods for advanced products, such as flexible electronics, renewable energy devices, and 2D materials. However, the development of cost-effective and efficient manufacturing processes for these products presents new challenges, including higher precision requirements, the need for improved in-line quality control, and the integration of material processing dynamics into the traditional web handling system. This paper reviews the state of the art in advanced R2R manufacturing, focusing on modeling and control, and highlights research areas that need further development. 
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    Free, publicly-accessible full text available April 1, 2026
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  7. Heterogeneities among tumor cells significantly contribute towards cancer progression and therapeutic inefficiency. Herein, we discuss recent microfluidic platforms for sorting and profiling of tumor cells for prognostics and personalized therapies. 
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    Free, publicly-accessible full text available February 25, 2026
  8. Abstract Spatially resolved transcriptomics technologies have opened new avenues for understanding gene expression heterogeneity in spatial contexts. However, existing methods for identifying spatially variable genes often focus solely on statistical significance, limiting their ability to capture continuous expression patterns and integrate spot-level covariates. To address these challenges, we introduce spVC, a statistical method based on a generalized Poisson model. spVC seamlessly integrates constant and spatially varying effects of covariates, facilitating comprehensive exploration of gene expression variability and enhancing interpretability. Simulation and real data applications confirm spVC’s accuracy in these tasks, highlighting its versatility in spatial transcriptomics analysis. 
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    Free, publicly-accessible full text available December 1, 2025
  9. Free, publicly-accessible full text available December 9, 2025
  10. Abstract Two correspondences raised concerns or comments about our analyses regarding exaggerated false positives found by differential expression (DE) methods. Here, we discuss the points they raise and explain why we agree or disagree with these points. We add new analysis to confirm that the Wilcoxon rank-sum test remains the most robust method compared to the other five DE methods (DESeq2, edgeR, limma-voom, dearseq, and NOISeq) in two-condition DE analyses after considering normalization and winsorization, the data preprocessing steps discussed in the two correspondences. 
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    Free, publicly-accessible full text available December 1, 2025