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:

"The Materials Research Society is proud to announce the 2020 MRS Communications Lecture honorees, Drs. Chun-Teh Chen and Grace Gu from the University of California, Berkeley. The honor recognizes excellence in the field of materials research through work published in MRS Communications. Drs. Chen and Gu are recognized this year for their prospective paper on how researchers are harnessing artificial intelligence to accelerate the design and discovery of composite materials. Their work is featured in volume nine, issue two of MRS Communications. Composites are combinations of two or more base materials, whose collective properties exceed those possessed by either material alone. Composites are widely used as structural materials in the automotive and aerospace industries and can also be easily found in nature. Limitations in manufacturing methods have generally restricted the architecture these materials take on in real-world applications. Most commonly, they’re processed into multilayer sheets..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general.

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:

"Antibiotic resistance is a growing problem worldwide—and in outer space. Spaceflight can promote biofilm formation and antimicrobial resistance development, and astronauts are especially vulnerable to infection due to the unique demands of spaceflight. To support future space travel, it is critical to understand exactly how spaceflight affects microbial diversity and virulence. To learn more, researchers recently used a machine learning algorithm to analyze sequencing data from the Microbial Tracking (MT)-1 mission, which sampled microbes at eight locations on the International Space Station during three flights. The model predicted the presence of hundreds of antibiotic resistance genes (ARGs) in the 226 bacterial strains isolated from the flights, including strains of the potentially very pathogenic bacterium Enterobacter bugandensis and the food poisoning-related bacterium Bacillus cereus..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This is the GitHub repository for course CMP 414/765: Artificial Intelligence taught at The City University of New York, Lehman College, in Fall 2022

9. Brave New World - AI/ML

The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, city governments worldwide are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more accessible with technology and more connected.

This video presentation was created by Ella Rechtenbach to provide instruction and insight into artificial intelligence and machine learning.

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:

"_Clostridioides difficile_ infection (CDI), the most common hospital-acquired infection in the U.S., can cause severe diarrhea and even death, and more than 15% of infected individuals experience recurrent infection within 8 weeks. CDI is related to gut microbiome imbalance, but the factors that influence recurrence are not well understood. To identify potential predictors of recurrence, researchers sequenced and metabolically profiled the gut microbiomes of 53 patients with CDI over time. Compared to patients with no recurrence, patients with recurrent CDI had slower recovery of gut microbial diversity, and depletion of important anaerobic microbes, such as certain _Clostridium_ species. The patients with recurrent CDI also had delayed recovery of microbial metabolites in the gut, which was likely associated with dysfunction of the microbiome or of the host tissue..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

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:

"A new study suggests that early ACL reconstruction surgery delays secondary injury to the knee meniscus compared with delayed surgery or nonsurgical treatment. The findings are published in _The_ _American Journal of Sports Medicine_. The anterior cruciate ligament, or ACL, is an important stabilizing structure in the knee. Injury to the ACL places additional stress on neighboring knee structures, such as the meniscus, increasing the risk of secondary injury. However, it’s unclear whether the type and timing of ACL reconstruction affect the risk of subsequent meniscal injury. To find out, researchers recently used machine learning to compare the risk and timing of secondary meniscal injury among patients whose ACL injuries were treated nonsurgically, with early reconstruction surgery, or with delayed reconstruction surgery. There was no significant difference in the overall occurrence of secondary meniscal injury in the patients who were treated with versus without surgery..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

13. Brave New World - Emerging Threats: Cybersecurity

The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities in particular are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, governments are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more accessible with technology and more connected.

This research resource suggests you some best sites of dataset collection which some of you might have known earlier. In the research field of machine learning, it is always tough to find the related dataset and if found it is always hard to filter some. Now that technologies have imporved, this article suggests some well known resources to collect your dataset related to your research. 

15. Brave New World: Ethical Considerations and Risks

The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities in particular are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, governments are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more accessible with technology and more connected.

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:

"Diarrhea is common among calves and causes huge losses to the global cattle industry. Fecal microbiota transplantation (FMT) is one promising approach to prevent and treat calf diarrhea. However, achieving success with FMT is difficult because of farm management differences, a lack of good donors, and the difficulty of recipient selection. To guide more effective FMT, a recent study investigated factors related to FMT success or failure in 20 donor–recipient pairs. The overall success rate for diarrhea improvement was 70%. Selenomonas bacteria were found in both donors and recipients when FMT was successful, suggesting that Selenomonas may be a biomarker of donor–recipient compatibility, and Sporobacter was identified as a potential biomarker for good donor selection. Pairs of correlations between specific microbial taxa and metabolites were also linked to success, and low levels of pre-FMT glycerol 3-phosphate, dihydroxyacetone phosphate, and isoamylamine were predicted to facilitate good results..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

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:

"A new, fully automated approach could help spot faulty electric motors before they leave the production floor. Based on a popular machine-learning algorithm known as an autoencoder, this technique could prove invaluable to the numerous industries that produce electric motors, as well as those that rely on them. An autoencoder is an algorithm that distills, or encodes, input data down to a few key elements. It then decodes that information to reproduce the original data as closely as possible. At first glance, it might look like a simple cut-and-paste operation. But there’s more than meets the eye. The algorithm actually learns to pick out patterns that are fundamental to the structure of the original data set. For that reason, the tool is incredibly useful for cleaning up noisy data. Trained on a sufficiently large data set, an autoencoder can look at a muddled image and output a fair restoration. That ability, it turns out, is also valuable for telling a good electric motor from a bad one..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

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:

"Environment-derived gut microbes can contribute to host health. In soil invertebrates, the gut microbiome is gradually assembled from the specific soil microecological region that the host inhabits. However, the effects of environmental stress on soil invertebrate microbiomes remain unknown. To learn more, a new study sought to characterize the gut bacterial taxa of the soil invertebrate Folsomia candida in the presence or absence of environmental concentrations of soil pollutants. Sequencing revealed that exposure to the fungicide azoxystrobin (AO), the antibiotic oxytetracycline (OTC), or their mixture (AO) increased Gammaproteobacteria abundance. The Gammaproteobacteria response was closely associated with F. candida physiological and functional indicators, such as the locomotion (HAA) index and oxidative stress..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

A module for the course: CS 59974: Special Topics in Artificial Intelligence - "Machine Learning in Action". Delivered at the City College of New York in Spring 2020 by Hunter McNichols as part of the Tech-in-Residence Corps program.

A module for the course: CS 59974: Special Topics in Artificial Intelligence - "Setting up Jupyter Notebooks". Delivered at the City College of New York in Spring 2020 by Hunter McNichols as part of the Tech-in-Residence Corps program.

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:

"Most current knowledge about gut microbiomes has been obtained from studies on mammals, while the microbiomes of fish, the most diverse group of vertebrates (~33,000 species), are less well understood. Specifically, the major influencing factors and unique features of fish gut microbiomes remain unclear. To bridge this knowledge gap, a recent study analyzed the gut contents of 227 fish representing 85 different freshwater fish (FWF) and saltwater fish (SWF) species. rRNA sequencing revealed that Proteobacteria and Firmicutes were the two most abundant phyla, indicating a different composition from the typical vertebrate microbiome, which is composed mainly of Firmicutes and Bacteroidetes. Habitat (freshwater versus saltwater) more strongly influenced the host microbiome than host taxonomy or trophic level and the microbiome taxonomic and functional profiles were better indicators of a fish’s habitat than of its taxonomy..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

In this lab, students will train three simple neural networks using the AP Gridworld software and a perceptron neural network. The lab culminates when students have trained an autonomous car to drive around simple cars without crashing.

These are materials that may be used in a CS0 course as a light introduction to machine learning.

The materials are mostly Jupyter notebooks which contain a combination of labwork and lecture notes. There are notebooks on Classification, An Introduction to Numpy, and An Introduction to Pandas.

There are also two assessments that could be assigned to students. One is an essay assignment in which students are asked to read and respond to an article on machine bias. The other is a lab-like exercise in which students use pandas and numpy to extract useful information about subway ridership in NYC. This assignment uses public data provided by NYC concerning entrances and exits at MTA stations.

This OER material was produced as a result of the CS04ALL CUNY OER project

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:

"The human gut is home to a diverse community of microbes. Variations in the makeup of this community between individuals have been linked to diseases such as inflammatory bowel disease, diabetes, and cancer. Efforts to understand these differences have revealed three community types, or enterotypes, in humans, each representing the dominance of a single microbe. But because microbes co-mingle with many partners, studying the gut microbiome solely in terms of enterotypes misses on the highly nuanced nature of microbial interactions. Researchers recently addressed that shortcoming using a machine learning technique called latent Dirichlet allocation, or LDA. Their goal was to determine whether and how recurring microbial partnerships, or assemblages, are linked to the three enterotypes. Using gut metagenomic data gathered from 861 healthy adults across 12 countries LDA revealed three assemblages corresponding to each enterotype as well as a fourth wild-card assemblage that could be found in any gut..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.