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Aims and Objectives: The aim of this study was to explore the association between transition shocks and professional identity and the mediating roles of self‐efficacy and resilience among Chinese novice nurses. Background: Novice nurses experience transition shock when they start their careers, which might lead to decreased professional identity and ultimately turnover. By contrast, self‐efficacy and resilience are excellent psychological resources that may be associated with higher professional identity. It is unclear how transition shock affects professional identity by influencing these two internal resources. Design: A cross‐sectional survey. Methods: The STROBE guidelines were followed to report this study. Convenience sampling was used to recruit participants, and 252 novice nurses completed the Transition Shock of Novice Nurses Scale, the Professional Identity Assessment Scale, the General Self‐Efficacy Scale and the Connor‐Davidson Resilience Scale between April 2022 and May 2022. Influencing factors were primarily identified using independent‐sample t‐tests and a one‐way ANOVA. Structural equation modelling was used to detect the mediating effects of self‐efficacy and resilience. Results: Differences in novice nurses' levels of professional identity were found across age groups, hospitals and departments. Transition shock was negatively related to professional identity. Self‐efficacy and resilience mediated the complete chain relationship between transition shock and professional identity. Conclusion: To our knowledge, this study is the first to explore the mediating effect of self‐efficacy and resilience on transition shock and professional identity. Higher transition shock may lead to lower professional identity by reducing self‐efficacy and resilience. Relevance to Clinical Practice: Nursing managers ought to emphasise the significant role of psychological resources in the work adaptation process of novice nurses. It may be more effective to improve professional identity and maintain the stability of the health care system. Patient or Public Contribution: Nursing administrators working at seven preselected hospitals actively assisted us in the process of collecting self‐report questionnaires from novice nurses, such as by booking appointments and providing access for questionnaire administration. In addition, the participants were actively involved in the data collection process. [ABSTRACT FROM AUTHOR]

The goal of color superresolution reconstruction and demosaicing is to get an enhanced resolution image from raw single-chip data of Bayer color filter array. Two parts of regularization method, fidelity and regularization terms, are discussed in detail to solve the problem. Elastic net is successfully applied to variable-selection method; we utilize it as a novel fidelity term to improve performance and make the reconstructed image more suitable for human visual system. Piecewise linear framelet operators are recently adopted to image denoising, which are utilized to detect multiorientation variation of the signal in color correlation space. [K.sub.R] as green (G) minus red and [K.sub.B] as G minus blue are a color correlation space of low-pass signal, and luminance component contains most of the information of a full-color image. Thus, [K.sub.R]/[K.sub.B] plus luminance component is considered as a color correlation space for regularization. Experimental results show that our algorithm is efficient in removing visual artifact, preserving the edges of image with high-peak signal-to-noise ratio, and satisfying visual effect. Index Terms--Color correlation space, color superresolution (SR), demosaicing, elastic net (EN), framelet, regularization.

Motivation: The identification of repetitive elements is important in genome assembly and phylogenetic analyses. The existing de novo repeat identification methods exploiting the use of short reads are impotent in identifying long repeats. Since long reads are more likely to cover repeat regions completely, using long reads is more favorable for recognizing long repeats. Results: In this study, we propose a novel de novo repeat elements identification method namely RepLong based on PacBio long reads. Given that the reads mapped to the repeat regions are highly overlapped with each other, the identification of repeat elements is equivalent to the discovery of consensus overlaps between reads, which can be further cast into a community detection problem in the network of read overlaps. In RepLong, we first construct a network of read overlaps based on pair-wise alignment of the reads, where each vertex indicates a read and an edge indicates a substantial overlap between the corresponding two reads. Secondly, the communities whose intra connectivity is greater than the inter connectivity are extracted based on network modularity optimization. Finally, representative reads in each community are extracted to form the repeat library. Comparison studies on Drosophila melanogaster and human long read sequencing data with genome-based and short-read-based methods demonstrate the efficiency of RepLong in identifying long repeats. RepLong can handle lower coverage data and serve as a complementary solution to the existing methods to promote the repeat identification performance on long-read sequencing data. [ABSTRACT FROM AUTHOR]