Browse Articles

Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning

Chong et al. | May 01, 2023

Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
Image credit: Pixabay

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.

Read More...

Firearm-purchase laws that limit the number of guns on the market reduce gun homicides in the South Side of Chicago

Krishnan et al. | Jan 24, 2022

Firearm-purchase laws that limit the number of guns on the market reduce gun homicides in the South Side of Chicago

Gun violence has been a serious issue in the South Side of Chicago for a long time. To intervene, regulators have passed legislation they hoped to curb -if not completely eradicate- the issue. However, there is little analysis done on how effective the various laws have been at reducing gun violence. Here the authors explore the association between firearm purchase laws passed between 1993-2018 and the incidence of gun homicide in Chicago's South Side. Their analysis suggests that some laws have been more effective than others, while some might have exacerbated the issue. However, they do not consider other contributing factors, which makes it difficult to prove causation without further investigation.

Read More...

The novel function of PMS2 mutation on ovarian cancer proliferation

Cho et al. | Dec 18, 2022

The novel function of <em>PMS2</em> mutation on ovarian cancer proliferation

With disruption of DNA repair pathways pertinent to the timeline of cancer, thorough evaluation of mutations relevant to DNA repair proteins is crucial within cancer research. One such mutation includes S815L PMS2 - a mutation that results in significant decrease of DNA repair function by PMS2 protein. While mutation of PMS2 is associated with significantly increased colorectal and endometrial cancer risk, much work is left to do to establish the functional effects of the S815L PMS2 mutation in ovarian cancer progression. In this article, researchers contribute to this essential area of research by uncovering the tumor-progressive effects of the S815L PMS2 mutation in the context of ovarian cancer cell lines.

Read More...

Investigation of unknown causes of uveal melanoma uncovers seven recurrent genetic mutations

Nanda et al. | Aug 25, 2022

Investigation of unknown causes of uveal melanoma uncovers seven recurrent genetic mutations

Uveal melanoma (UM) is a rare subtype of melanoma but the most frequent primary cancer of the eye in adults. The goal of this study was to research the genetic causes of UM through a comprehensive frequency analysis of base-pair mismatches in patient genomes. Results showed a total of 130 genetic mutations, including seven recurrent mutations, with most mutations occurring in chromosomes 3 and X. Recurrent mutations varied from 8.7% to 17.39% occurrence in the UM patient sample, with all mutations identified as missense. These findings suggest that UM is a recessive heterogeneous disease with selective homozygous mutations. Notably, this study has potential wider significance because the seven genes targeted by recurrent mutations are also involved in other cancers.

Read More...

Collaboration beats heterogeneity: Improving federated learning-based waste classification

Chong et al. | Jul 18, 2023

Collaboration beats heterogeneity: Improving federated learning-based waste classification

Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.

Read More...

Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy

Takemaru et al. | Feb 24, 2020

Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy

Acquired immunodeficiency syndrome (AIDS) is a life-threatening condition caused by the human immunodeficiency virus (HIV). In this work, Takemaru et al explored the role of Coiled-Coil Domain-Containing 11 (CCDC11) in HIV-1 budding. Their results suggest that CCDC11 is critical for efficient HIV-1 budding, potentially indicating CCDC11 a viable target for antiviral therapeutics without major side effects.

Read More...

Search Articles

Search articles by title, author name, or tags

Clear all filters

Popular Tags

Browse by school level