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CC BY-NC-SA
Introduction to Chemistry
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Conditional Remix & Share Permitted
CC BY-NC-SA
This intermediate organic chemistry course focuses on the methods used to identify the structure of organic molecules, advanced principles of organic stereochemistry, organic reaction mechanisms, and methods used for the synthesis of organic compounds. Additional special topics include illustrating the role of organic chemistry in biology, medicine, and industry.
- Subject:
- Chemistry
- Physical Science
- Material Type:
- Full Course
- Provider Set:
- MIT OpenCourseWare
- Author:
- Jamison, Timothy
- Tabacco, Sarah
- Date Added:
- 09/01/2003
Conditional Remix & Share Permitted
CC BY-NC-SA
This intermediate organic chemistry course focuses on the methods used to identify the structure of organic molecules, advanced principles of organic stereochemistry, organic reaction mechanisms, and methods used for the synthesis of organic compounds. Additional special topics include illustrating the role of organic chemistry in biology, medicine, and industry.
- Subject:
- Chemistry
- Physical Science
- Material Type:
- Full Course
- Provider Set:
- MIT OpenCourseWare
- Author:
- Berkowski, Kimberly
- Jamison, Timothy
- Date Added:
- 09/01/2006
Only Sharing Permitted
CC BY-NC-ND
Learn about organic chemistry through engaging, bitesize animated videos. They are organised into these chapters: crude oil, functional groups, alkanes and alkenes, alcohols, carboxylic acids and esters, polymers, proteins, carbohydrates, organic chemistry in everyday life and nanoscience.
- Subject:
- Physical Science
- Material Type:
- Lecture
- Date Added:
- 01/12/2016
Unrestricted Use
CC BY
This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:
"Background: Activated sludge (AS) of wastewater treatment plants (WWTP) is one of the world’s largest artificial microbial ecosystems and the microbial community of the AS system is closely related to WWTP performance. However, how to predict its community structure is still unclear. Results: Here, we used artificial neural networks (ANN) to predict the microbial compositions of AS systems collected from WWTPs located worldwide. The predictive accuracy R21:1 of Shannon-Wiener index reached 60.42%, and the average R21:1 of amplicon sequence variants (ASVs) appearing in at least 10% of samples and core taxa were 35.09% and 42.99%, respectively. We also found that the predictability of ASVs was significantly positively correlated with their relative abundance and occurrence frequency, but significantly negatively correlated with potential migration rate..."
The rest of the transcript, along with a link to the research itself, is available on the resource itself.
- Subject:
- Biology
- Career and Technical Education
- Environmental Studies
- Life Science
- Material Type:
- Diagram/Illustration
- Reading
- Provider:
- Research Square
- Provider Set:
- Video Bytes
- Date Added:
- 06/20/2023