Domestic Violence On Paula Hawkins’ Novel The Girl On The Train (2015): A Sociological Approach

Astrie Ayu Nilasari/A320140001. DOMESTIC VIOLENCE ON PAULA HAWKINS’ NOVEL THE GIRL ON THE TRAIN (2015): SOCIOLOGICAL APPROACH. Research paper. School of Teacher Training and English end Education, Muhammadiyah University of Surakarta. June, 2020. Domestic violence can happen in marriage life. WHO in 2018 showed there are 71% physic and sexual violence, 62% among them were domestic violence. In this study, the researcher focused on domestic violence that happened in The Girl On The Train novel. The objectives of this study were to identify the causes of domestic violence, to describe how domestic violence is depicted in the novel, and to reveal the reason why the author represents domestic violence in the novel. To collect the data results researcher used editing, organizing, and conducting the finding of the result based on the analysis. The results of the study showed first, there are four causes of domestic violence such as economic problems, man’s bad habit violence, jealous woman/man, and disloyalty woman/man. Second, the depiction of domestic violence in this novel divided into characters, plot/events, setting, and style. Third, the reason Paula Hawkins addressed domestic violence in her novel is she was interested in domestic violence phenomena and she wanted women/men aware of domestic violence. In conclusion, this research showed domestic violence occurs for some reasons such as economic problems, man’s bad habit violence, jealous woman/man, and disloyalty woman/man. Domestic violence in this novel is represented to characters, plot/events, setting, and style The Girl On The Train novel

Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken

Background: The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues. Results: Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development. Conclusion: Expression profiles obtained from public RNA-seq datasets - despite being generated by different laboratories using different methodologies - can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species