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

Ideal Solutions

Ideal Solutions

According to Raoult’s law, the partial vapor pressure of a solvent in a solution is equal or identical to the vapor pressure of the pure solvent multiplied by its mole fraction in the solution. However, Raoult's Law is only valid for ideal solutions. For a solution to be ideal, the solvent-solute interaction must be just as strong as a solvent-solvent or solute-solute interaction. This suggests that both the solute and the solvent would use the same amount of energy to escape to the...

General Properties of Solutions

General Properties of Solutions

Many common substances around us exist as a solution, such as ocean water, air, and gasoline. All solutions are mixtures of substances that are composed of varying amounts of two or more types of atoms or molecules. A mixture with a non-uniform composition is a heterogeneous mixture, whereas a mixture with a uniform composition is a homogeneous mixture. The components that make the homogeneous mixture are evenly spread out and thoroughly mixed.

Solution Formation

Solution Formation

There is no one solvent that can dissolve every type of solute. Some substances that readily dissolve in a certain solvent might be insoluble in a different solvent. A simple way to predict which substances dissolve in which solvent is the phrase "like dissolves like". This means that polar substances, such as salt and sugar, dissolve in a polar substance like water. In contrast, non-polar substances are more soluble in non-polar solvents such as carbon tetrachloride.
This selective...

Enthalpy of Solution

Enthalpy of Solution

There are two criteria that favor, but do not guarantee, the spontaneous formation of a solution:

Standard Solutions

Standard Solutions

Standard solutions refer to solutions with a precisely known concentration or composition. A primary standard is a highly pure, high molar mass, stable substance that is entirely soluble in water, the most commonly used solvent in analytical chemistry. The primary standard solution can be used to standardize secondary standards, which are substances with known concentrations but are less pure and stable. Standard solutions are essential for achieving accurate and reliable results in analytical...

Blank Solutions

Blank Solutions

A blank solution is a solution that does not contain the analyte, or the substance of interest being tested or measured. It is typically prepared using the same reagents and procedure as the sample solution but without adding the analyte. The primary purpose of preparing a blank solution is to account for any background interference or contamination that may affect the accuracy and reliability of the analytical method.
In some experimental cases, the reagents, solvents, or lab equipment used in...

You might also read

Related Articles

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

Sort by

Same author

Race and Ethnicity in Cardiovascular Disease Risk Prediction for Multiethnic Populations: Insights From Global Guidelines.

JACC. Asia·2026

Same author

Epicardial adipose tissue signatures in Asian coronary artery disease: Insights from cardiac CT.

American journal of preventive cardiology·2026

Same author

A Retrospective Analysis of Concomitant Spinal Injuries in the Setting of Polytrauma at a Tertiary Hospital in Singapore.

Cureus·2026

Same author

Voice features and deep learning models for identifying acute decompensated heart failure.

Digital health·2026

Same author

Discrimination Against Asian Americans and its Impact on Lifestyle Risk Factors for Cardiovascular Disease: A Scoping Review.

Journal of racial and ethnic health disparities·2026

Same author

Efficacy and safety of aspirin for primary prevention in adults with elevated lipoprotein(a) or genetic susceptibility via LPA gene variants: a systematic review and meta-analysis.

European journal of preventive cardiology·2026

Same journal

Modeling and analysis of forward and inverse kinematics for a flexible Stewart platform.

PloS one·2026

Same journal

Barriers and facilitators to healthcare utilization amongst people living with sickle cell disease in the United States: A scoping review.

PloS one·2026

Same journal

Enhancing data completeness in time series: Imputation strategies for missing data using significant periodically correlated components.

PloS one·2026

Same journal

Key targets and mechanisms by which gut microbiota-derived metabolites regulate Alzheimer's disease through the immune - inflammatory pathway: Based on network pharmacology and molecular docking.

PloS one·2026

Same journal

Grid-tied Transformer-less Boost Switched Capacitor Topology (TLBSCT) for PV applications.

PloS one·2026

Same journal

The load-velocity profiles and exercise-specific velocity zones for seven commonly used weightlifting exercises.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 20, 2026

Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication

Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication

Published on: January 26, 2024

Hate speech detection: Challenges and solutions.

Sean MacAvaney¹, Hao-Ren Yao¹, Eugene Yang¹

¹Information Retrieval Laboratory, Georgetown University, Washington, DC, United States of America.

|August 21, 2019

Summary

This summary is machine-generated.

This study addresses challenges in automatic hate speech detection, proposing a multi-view Support Vector Machine (SVM) approach for improved interpretability and performance in identifying harmful online content.

More Related Videos

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Published on: January 3, 2017

Organotypic Cerebellar Cultures: Apoptotic Challenges and Detection

Organotypic Cerebellar Cultures: Apoptotic Challenges and Detection

Published on: May 17, 2011

Related Experiment Videos

Last Updated: Jan 20, 2026

Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication

Author Spotlight: Deciphering the Cognitive and Neural Mechanisms of Gesture in Communication

Published on: January 26, 2024

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors

Published on: January 3, 2017

Organotypic Cerebellar Cultures: Apoptotic Challenges and Detection

Organotypic Cerebellar Cultures: Apoptotic Challenges and Detection

Published on: May 17, 2011

Area of Science:

Natural Language Processing
Computational Linguistics
Artificial Intelligence

Background:

The proliferation of online content has led to an increase in hate speech.
Automatic detection of hate speech faces challenges including linguistic nuances, varying definitions, and data limitations.
Current deep learning models often lack interpretability, making it difficult to understand their decision-making processes.

Purpose of the Study:

To identify and examine the challenges in automatic hate speech detection.
To propose a more interpretable and effective approach for hate speech detection.
To discuss remaining technical and practical challenges in the field.

Main Methods:

Utilized a multi-view Support Vector Machine (SVM) approach.
Compared the proposed method against existing state-of-the-art techniques.
Focused on improving model interpretability alongside performance.

Main Results:

The multi-view SVM approach achieved near state-of-the-art performance.
The proposed method demonstrated greater simplicity and interpretability compared to neural networks.
Effectively addressed some limitations of current hate speech detection systems.

Conclusions:

The multi-view SVM offers a promising direction for interpretable hate speech detection.
Further research is needed to overcome remaining technical and practical hurdles.
Improved interpretability is crucial for trustworthy AI in content moderation.