Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Force Classification

Force Classification

Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

LINC01116 promotes tumor proliferation and neutrophil recruitment via DDX5-mediated regulation of IL-1β in glioma cell.

Cell death & disease·2020

Same author

Metal-Organic Framework Membrane Nanopores as Biomimetic Photoresponsive Ion Channels and Photodriven Ion Pumps.

Angewandte Chemie (International ed. in English)·2020

Same author

Graphdiyne oxide: a new carbon nanozyme.

Chemical communications (Cambridge, England)·2020

Same author

Egg and egg-sourced cholesterol consumption in relation to mortality: Findings from population-based nationwide cohort.

Clinical nutrition (Edinburgh, Scotland)·2020

Same author

A blood-based 22-gene expression signature for hepatocellular carcinoma identification.

Annals of translational medicine·2020

Same author

Identification of Four Pathological Stage-Relevant Genes in Association with Progression and Prognosis in Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis.

BioMed research international·2020

Search research articles

Related Experiment Video

Updated: Sep 24, 2025

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

English Text Recognition Deep Learning Framework to Automatically Identify Fake News.

Fei Wu¹, Xiaoyu Luo²

¹Hunan Institute of Engineering, 411104 Xiangtan, Hunan, China.

Computational Intelligence and Neuroscience

|May 9, 2022

Summary

This study introduces a novel deep temporal convolutional network (DTCN) method to combat fake news by analyzing user friendships. The advanced technique achieves highly reliable fake news detection, protecting readers from misinformation.

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Sep 24, 2025

Deep Neural Networks for Image-Based Dietary Assessment

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Area of Science:

Computer Science
Social Media Analysis
Information Science

Background:

The rapid spread of fake news globally is a significant modern technological challenge.
Increased social media use and declining trust in traditional media exacerbate fake news dissemination.
The vast volume and speed of online information contribute to the fake news problem.

Purpose of the Study:

To highlight the importance of detecting fake news.
To develop automated methods for identifying false information.
To protect readers from online misinformation.

Main Methods:

Utilized user friendship information for fake news detection.
Employed a deep temporal convolutional network (DTCN) scheme.
Integrated tensor factorization with a non-negative RESCAL method and class-aware rate tables.

Main Results:

Achieved highly reliable fake news detection.
Produced more accurate representations through advanced factorization techniques.
Demonstrated the effectiveness of the DTCN and RESCAL integration.

Conclusions:

Automated fake news detection is crucial for combating misinformation.
Analyzing user social networks offers valuable insights for detection.
The proposed DTCN-based method provides a robust solution for identifying fake news.