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:

"Artificial intelligence is transforming our way of life. Able to spot patterns invisible to the human eye, algorithms are learning how to make our lives easier, safer, and more fun. That power is not lost on materials researchers. During the next decade, artificial intelligence or AI-driven research could fundamentally transform how new and better materials are developed. What’s more, it might even revamp how materials research itself is carried out, enabling promising new materials and processes to be developed more quickly. Machine learning methods come in a variety of flavors, with some requiring more guidance, or “supervision,” from researchers. But, generally, a machine-learning algorithm designed to discover and understand the behavior of materials looks for patterns connecting the composition, structure, and properties of known materials..."

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

Grade level: graduate students, advanced undergrads, persons with analyzed research results

Course length: 1 semester, 4-6 months

Objective: This course empowers scientists to engage with their own data, each other, and the public through art. Through collective brainstorming, prototyping, and feedback from professional artists, students will create a project that expresses their own research through any artistic medium of their choice. The course typically culminates in a public art exhibition where students interact with a general audience to discuss their research, art, and what it means to be a scientist.

SYNOPSIS: In this lesson, students investigate the effectiveness of visual art in addressing climate change.

SCIENTIST NOTES: Simply put, not everyone is swayed by a scientific expert. Often it takes other means to convey a message to someone. That is why is an integral part of climate change communication. Art, scientifically, has a different impact on our thoughts and decision-making than hearing a lecture from an expert. This lesson explores different climate change art projects and shows their potential to reach audiences. This lesson has passed the scientific review process.

POSITIVES:
-Students learn that art can be used to address issues that are usually just discussed in scientific terms.
-Students learn about a variety of artists whose work deals with climate change.
-Students can begin to visualize ways that they might make art about climate change, which can serve as a subsequent lesson.
-This lesson is interactive and simulates a real-world situation in the art world, requiring a variety of skills.

ADDITIONAL PREREQUISITES:
-This lesson can be paired with or follow a more in-depth discussion of climate change science.
-Students should know how to use Google Slides or a similar type of presentation format.
-Students should have a basic familiarity with rubrics.

DIFFERENTIATION:
-Teachers can provide instruction multimodally.
-Teachers can preview vocabulary with ESL students.
-Teachers can follow up with questions to ensure comprehension.
-Teachers can pair students with helpful peers.
-It can be beneficial for developing students’ interpersonal skills if groups were randomized.

"The Art of the Probable" addresses the history of scientific ideas, in particular the emergence and development of mathematical probability. But it is neither meant to be a history of the exact sciences per se nor an annex to, say, the Course 6 curriculum in probability and statistics. Rather, our objective is to focus on the formal, thematic, and rhetorical features that imaginative literature shares with texts in the history of probability. These shared issues include (but are not limited to): the attempt to quantify or otherwise explain the presence of chance, risk, and contingency in everyday life; the deduction of causes for phenomena that are knowable only in their effects; and, above all, the question of what it means to think and act rationally in an uncertain world.
Our course therefore aims to broaden students' appreciation for and understanding of how literature interacts with – both reflecting upon and contributing to – the scientific understanding of the world. We are just as centrally committed to encouraging students to regard imaginative literature as a unique contribution to knowledge in its own right, and to see literary works of art as objects that demand and richly repay close critical analysis. It is our hope that the course will serve students well if they elect to pursue further work in Literature or other discipline in SHASS, and also enrich or complement their understanding of probability and statistics in other scientific and engineering subjects they elect to take.

The ability to ask and answer questions while reading is essential to comprehension. This article discusses instructional strategies used to teach questioning and provides many online resources. The article appears in the free, online magazine Beyond Weather and the Water Cycle, which explores the seven essential principles of the climate sciences for teachers in k-grade 5 classrooms.

This activity introduces students to an actual data set that explores the impacts of ocean acidification on tropical coral reef ecosystems. Students are first given a scenario for a field site in the Caribbean and are asked to design an experiment that answers the question: How will a decline in surface ocean pH by the 21st century impact tropical coral growth? Students then gather actual data (from coral images collected from the field site) to calculate calcification rates of different coral samples. Finally, students use the provided saturation state values to predict the extent to which coral calcification is expected to decline by the 21st century.

In this lesson students create a laboratory simulation of the water cycle. Indicating the change in states of matter and the flow of energy. Students also compare and contrast the cycle of matter with the flow of energy. This lesson was created as part of the 2016 NASA STEM Standards of Practice Project, a collaboration between the Alabama State Department of Education and NASA Marshall Space Flight Center.

In this feature, adapted from Interactive NOVA: "Earth," students explore the relationship between oxygen concentration and the well-being of various organisms by simulating a change in oxygen levels and observing what happens.

This image depicts a representative subset of the atmospheric processes related to aerosol lifecycles, cloud lifecycles, and aerosol-cloud-precipitation interactions that must be understood to improve future climate predictions.

Atmospheric methyl chloroform concentration is modeled as an extension of the generic water tank structure. Simulated and observed concentrations are used to estimate the global atmospheric lifetime of methyl chloroform and its 1989 to 2009 emission history.

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This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure approaches, molecular dynamics, and Monte Carlo.
This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5107 (Atomistic Computer Modeling of Materials).
Acknowledgements
Support for this course has come from the National Science Foundation's Division of Materials Research (grant DMR-0304019) and from the Singapore-MIT Alliance.

In this activity, students will explore how the Law of Conservation of Energy (the First Law of Thermodynamics) applies to atoms, as well as the implications of heating or cooling a system. This activity focuses on potential energy and kinetic energy as well as energy conservation. The goal is to apply what is learned to both our human scale world and the world of atoms and molecules.

In this simulation of a doctor's office, students play the roles of physician, nurse, patients, and time-keeper, with the objective to improve the patient waiting time. They collect and graph data as part of their analysis. This serves as a hands-on example of using engineering principles and engineering design approaches (such as models and simulations) to research, analyze, test and improve processes.

More attractive people elicit more positive first impressions. This effect is called the attractiveness halo, and it is shown when judging those with more attractive faces, bodies, or voices. Moreover, it yields significant social outcomes, including advantages to attractive people in domains as far-reaching as romance, friendships, family relations, education, work, and criminal justice. Physical qualities that increase attractiveness include youthfulness, symmetry, averageness, masculinity in men, and femininity in women. Positive expressions and behaviors also raise evaluations of a person’s attractiveness. Cultural, cognitive, evolutionary, and overgeneralization explanations have been offered to explain why we find certain people attractive. Whereas the evolutionary explanation predicts that the impressions associated with the halo effect will be accurate, the other explanations do not. Although the research evidence does show some accuracy, it is too weak to satisfactorily account for the positive responses shown to more attractive people.

The simulation illustrates an Atwood's machine, which is simply two blocks connected by a string passing over a pulley. In this version of the simulation, the mass of the pulley is negligible - that leads to the tension being the same everywhere in the string.

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:

"Accurate identification of medical alarm sounds can be life-saving, but current standard alarms are difficult to learn. One issue is that these alarms, despite having different melodies, possess highly similar tonal qualities. This makes it hard to distinguish, for example, an alarm indicating an abnormal heart rate from one denoting abnormal oxygen saturation. To ease interpretation, researchers have developed new auditory icon alarms. These real-world sounds are associated with the processes they represent, such as the sound made by pills rattling in a bottle to indicate a drug administration issue or the sound of assisted breathing to denote abnormal ventilation parameters. The intuitive reaction to such sounds should make the icon alarms easier to identify than standard alarms, creating new possibilities to improve patient safety. The team tested the usability of the icons in a simulated intensive care unit..."

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

Accumulating evidence indicates high risk of bias in preclinical animal research, questioning the scientific validity and reproducibility of published research findings. Systematic reviews found low rates of reporting of measures against risks of bias in the published literature (e.g., randomization, blinding, sample size calculation) and a correlation between low reporting rates and inflated treatment effects. That most animal research undergoes peer review or ethical review would offer the possibility to detect risks of bias at an earlier stage, before the research has been conducted. For example, in Switzerland, animal experiments are licensed based on a detailed description of the study protocol and a harm–benefit analysis. We therefore screened applications for animal experiments submitted to Swiss authorities (n = 1,277) for the rates at which the use of seven basic measures against bias (allocation concealment, blinding, randomization, sample size calculation, inclusion/exclusion criteria, primary outcome variable, and statistical analysis plan) were described and compared them with the reporting rates of the same measures in a representative sub-sample of publications (n = 50) resulting from studies described in these applications. Measures against bias were described at very low rates, ranging on average from 2.4% for statistical analysis plan to 19% for primary outcome variable in applications for animal experiments, and from 0.0% for sample size calculation to 34% for statistical analysis plan in publications from these experiments. Calculating an internal validity score (IVS) based on the proportion of the seven measures against bias, we found a weak positive correlation between the IVS of applications and that of publications (Spearman’s rho = 0.34, p = 0.014), indicating that the rates of description of these measures in applications partly predict their rates of reporting in publications. These results indicate that the authorities licensing animal experiments are lacking important information about experimental conduct that determines the scientific validity of the findings, which may be critical for the weight attributed to the benefit of the research in the harm–benefit analysis. Similar to manuscripts getting accepted for publication despite poor reporting of measures against bias, applications for animal experiments may often be approved based on implicit confidence rather than explicit evidence of scientific rigor. Our findings shed serious doubt on the current authorization procedure for animal experiments, as well as the peer-review process for scientific publications, which in the long run may undermine the credibility of research. Developing existing authorization procedures that are already in place in many countries towards a preregistration system for animal research is one promising way to reform the system. This would not only benefit the scientific validity of findings from animal experiments but also help to avoid unnecessary harm to animals for inconclusive research.

UniProt is a high quality, comprehensive protein resource in which the core activity is the expert review and annotation of proteins where the function has been experimentally investigated. At the same time the UniProt database contains large numbers of proteins which are predicted to exist from gene models, but which do not have associated experimental evidence indicating their function. UniProt commits significant resources to developing computational methods for functional annotation of these predicted proteins based on the data in entries that have gone through the expert review process.

We will describe the two main automated annotation systems currently in use. First, UniRule, which is an established UniProt system in which curators manually develop rules for annotation. Second ARBA (Association-Rule-Based Annotator), which has recently been introduced as a significant improvement in fully automated functional annotation. ARBA is a multiclass learning system which uses rule mining techniques to generate concise annotation models. ARBA employs a data exclusion set that censors data not suitable for computational annotation, and generates human-readable rules for each UniProt release.

We will also briefly touch on the mechanism UniProt has set up to enable researchers to run these automated annotation systems on their own protein datasets.

Who is this course for?
This webinar is for scientists and bioinformaticians with an interest in functional annotation of protein sequences.

Outcomes
By the end of the webinar you will be able to:

Recall the role of UniProt's two main automated annotation systems
Describe how UniRule and ARBA work
Get started using these automated annotation systems

Students learn more about assistive devices, specifically biomedical engineering applied to computer engineering concepts, with an engineering challenge to create an automatic floor cleaner computer program. Following the steps of the design process, they design computer programs and test them by programming a simulated robot vacuum cleaner (a LEGO® robot) to move in designated patterns. Successful programs meet all the design requirements.

Second course in a two-course sequence. Introduces and applies technical skills around beginning and managing a small business, including spreadsheets and the use of charts and graphs. Includes reflection and discussion of the application of concepts to a real-world example. Requires teamwork and collaboration to be exercised in completing a group project. Covers application of financial, legal, and administrative procedures in running a business.
Upon successful completion of this course, students will be able to:
Represent business models in spreadsheets including preparation of charts and graphs. Apply key business activities and the primary concepts and terms associated with these activities. Manage a business interacting with the external environment (through a simulation) and describe how this interaction impacts both business and the external environment. Implement the financial, legal, and administrative procedures involved in starting new business ventures. Identify ethical issues facing businesses. Effectively collaborate with team members and communicate professionally.