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Google Scholar: the ultimate guide

How to use Google scholar: the ultimate guide

What is Google Scholar?

Why is google scholar better than google for finding research papers, the google scholar search results page, the first two lines: core bibliographic information, quick full text-access options, "cited by" count and other useful links, tips for searching google scholar, 1. google scholar searches are not case sensitive, 2. use keywords instead of full sentences, 3. use quotes to search for an exact match, 3. add the year to the search phrase to get articles published in a particular year, 4. use the side bar controls to adjust your search result, 5. use boolean operator to better control your searches, google scholar advanced search interface, customizing search preferences and options, using the "my library" feature in google scholar, the scope and limitations of google scholar, alternatives to google scholar, country-specific google scholar sites, frequently asked questions about google scholar, related articles.

Google Scholar (GS) is a free academic search engine that can be thought of as the academic version of Google. Rather than searching all of the indexed information on the web, it searches repositories of:

  • universities
  • scholarly websites

This is generally a smaller subset of the pool that Google searches. It's all done automatically, but most of the search results tend to be reliable scholarly sources.

However, Google is typically less careful about what it includes in search results than more curated, subscription-based academic databases like Scopus and Web of Science . As a result, it is important to take some time to assess the credibility of the resources linked through Google Scholar.

➡️ Take a look at our guide on the best academic databases .

Google Scholar home page

One advantage of using Google Scholar is that the interface is comforting and familiar to anyone who uses Google. This lowers the learning curve of finding scholarly information .

There are a number of useful differences from a regular Google search. Google Scholar allows you to:

  • copy a formatted citation in different styles including MLA and APA
  • export bibliographic data (BibTeX, RIS) to use with reference management software
  • explore other works have cited the listed work
  • easily find full text versions of the article

Although it is free to search in Google Scholar, most of the content is not freely available. Google does its best to find copies of restricted articles in public repositories. If you are at an academic or research institution, you can also set up a library connection that allows you to see items that are available through your institution.

The Google Scholar results page differs from the Google results page in a few key ways. The search result page is, however, different and it is worth being familiar with the different pieces of information that are shown. Let's have a look at the results for the search term "machine learning.”

Google Scholar search results page

  • The first line of each result provides the title of the document (e.g. of an article, book, chapter, or report).
  • The second line provides the bibliographic information about the document, in order: the author(s), the journal or book it appears in, the year of publication, and the publisher.

Clicking on the title link will bring you to the publisher’s page where you may be able to access more information about the document. This includes the abstract and options to download the PDF.

Google Scholar quick link to PDF

To the far right of the entry are more direct options for obtaining the full text of the document. In this example, Google has also located a publicly available PDF of the document hosted at umich.edu . Note, that it's not guaranteed that it is the version of the article that was finally published in the journal.

Google Scholar: more action links

Below the text snippet/abstract you can find a number of useful links.

  • Cited by : the cited by link will show other articles that have cited this resource. That is a super useful feature that can help you in many ways. First, it is a good way to track the more recent research that has referenced this article, and second the fact that other researches cited this document lends greater credibility to it. But be aware that there is a lag in publication type. Therefore, an article published in 2017 will not have an extensive number of cited by results. It takes a minimum of 6 months for most articles to get published, so even if an article was using the source, the more recent article has not been published yet.
  • Versions : this link will display other versions of the article or other databases where the article may be found, some of which may offer free access to the article.
  • Quotation mark icon : this will display a popup with commonly used citation formats such as MLA, APA, Chicago, Harvard, and Vancouver that may be copied and pasted. Note, however, that the Google Scholar citation data is sometimes incomplete and so it is often a good idea to check this data at the source. The "cite" popup also includes links for exporting the citation data as BibTeX or RIS files that any major reference manager can import.

Google Scholar citation panel

Pro tip: Use a reference manager like Paperpile to keep track of all your sources. Paperpile integrates with Google Scholar and many popular academic research engines and databases, so you can save references and PDFs directly to your library using the Paperpile buttons and later cite them in thousands of citation styles:

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Although Google Scholar limits each search to a maximum of 1,000 results , it's still too much to explore, and you need an effective way of locating the relevant articles. Here’s a list of pro tips that will help you save time and search more effectively.

You don’t need to worry about case sensitivity when you’re using Google scholar. In other words, a search for "Machine Learning" will produce the same results as a search for "machine learning.”

Let's say your research topic is about self driving cars. For a regular Google search we might enter something like " what is the current state of the technology used for self driving cars ". In Google Scholar, you will see less than ideal results for this query .

The trick is to build a list of keywords and perform searches for them like self-driving cars, autonomous vehicles, or driverless cars. Google Scholar will assist you on that: if you start typing in the search field you will see related queries suggested by Scholar!

If you put your search phrase into quotes you can search for exact matches of that phrase in the title and the body text of the document. Without quotes, Google Scholar will treat each word separately.

This means that if you search national parks , the words will not necessarily appear together. Grouped words and exact phrases should be enclosed in quotation marks.

A search using “self-driving cars 2015,” for example, will return articles or books published in 2015.

Using the options in the left hand panel you can further restrict the search results by limiting the years covered by the search, the inclusion or exclude of patents, and you can sort the results by relevance or by date.

Searches are not case sensitive, however, there are a number of Boolean operators you can use to control the search and these must be capitalized.

  • AND requires both of the words or phrases on either side to be somewhere in the record.
  • NOT can be placed in front of a word or phrases to exclude results which include them.
  • OR will give equal weight to results which match just one of the words or phrases on either side.

➡️ Read more about how to efficiently search online databases for academic research .

In case you got overwhelmed by the above options, here’s some illustrative examples:

Example queriesWhen to use and what will it do?

"alternative medicine"

Multiword concepts like are best searched as an exact phrase match. Otherwise, Google Scholar will display results that contain and/or .

"The wisdom of the hive: the social physiology of honey bee colonies"

If you are looking for a particular article and know the title, it is best to put it into quotes to look for an exact match.

author:"Jane Goodall"

A query for a particular author, e.g., Jane Goodall. "J Goodall" or "Goodall" will also work, but will be less restrictive.

"self-driving cars" AND "autonomous vehicles"

Only results will be shown that contain both the phrases "self-driving cars" and "autonomous vehicles"

dinosaur 2014

Limits search results about dinosaurs to articles that were published in 2014

Tip: Use the advanced search features in Google Scholar to narrow down your search results.

You can gain even more fine-grained control over your search by using the advanced search feature. This feature is available by clicking on the hamburger menu in the upper left and selecting the "Advanced search" menu item.

Google Scholar advanced search

Adjusting the Google Scholar settings is not necessary for getting good results, but offers some additional customization, including the ability to enable the above-mentioned library integrations.

The settings menu is found in the hamburger menu located in the top left of the Google Scholar page. The settings are divided into five sections:

  • Collections to search: by default Google scholar searches articles and includes patents, but this default can be changed if you are not interested in patents or if you wish to search case law instead.
  • Bibliographic manager: you can export relevant citation data via the “Bibliography manager” subsection.
  • Languages: if you wish for results to return only articles written in a specific subset of languages, you can define that here.
  • Library links: as noted, Google Scholar allows you to get the Full Text of articles through your institution’s subscriptions, where available. Search for, and add, your institution here to have the relevant link included in your search results.
  • Button: the Scholar Button is a Chrome extension which adds a dropdown search box to your toolbar. This allows you to search Google Scholar from any website. Moreover, if you have any text selected on the page and then click the button it will display results from a search on those words when clicked.

When signed in, Google Scholar adds some simple tools for keeping track of and organizing the articles you find. These can be useful if you are not using a full academic reference manager.

All the search results include a “save” button at the end of the bottom row of links, clicking this will add it to your "My Library".

To help you provide some structure, you can create and apply labels to the items in your library. Appended labels will appear at the end of the article titles. For example, the following article has been assigned a “RNA” label:

Google Scholar  my library entry with label

Within your Google Scholar library, you can also edit the metadata associated with titles. This will often be necessary as Google Scholar citation data is often faulty.

There is no official statement about how big the Scholar search index is, but unofficial estimates are in the range of about 160 million , and it is supposed to continue to grow by several million each year.

Yet, Google Scholar does not return all resources that you may get in search at you local library catalog. For example, a library database could return podcasts, videos, articles, statistics, or special collections. For now, Google Scholar has only the following publication types:

  • Journal articles : articles published in journals. It's a mixture of articles from peer reviewed journals, predatory journals and pre-print archives.
  • Books : links to the Google limited version of the text, when possible.
  • Book chapters : chapters within a book, sometimes they are also electronically available.
  • Book reviews : reviews of books, but it is not always apparent that it is a review from the search result.
  • Conference proceedings : papers written as part of a conference, typically used as part of presentation at the conference.
  • Court opinions .
  • Patents : Google Scholar only searches patents if the option is selected in the search settings described above.

The information in Google Scholar is not cataloged by professionals. The quality of the metadata will depend heavily on the source that Google Scholar is pulling the information from. This is a much different process to how information is collected and indexed in scholarly databases such as Scopus or Web of Science .

➡️ Visit our list of the best academic databases .

Google Scholar is by far the most frequently used academic search engine , but it is not the only one. Other academic search engines include:

  • Science.gov
  • Semantic Scholar
  • scholar.google.fr : Sur les épaules d'un géant
  • scholar.google.es (Google Académico): A hombros de gigantes
  • scholar.google.pt (Google Académico): Sobre os ombros de gigantes
  • scholar.google.de : Auf den Schultern von Riesen

➡️ Once you’ve found some research, it’s time to read it. Take a look at our guide on how to read a scientific paper .

No. Google Scholar is a bibliographic search engine rather than a bibliographic database. In order to qualify as a database Google Scholar would need to have stable identifiers for its records.

No. Google Scholar is an academic search engine, but the records found in Google Scholar are scholarly sources.

No. Google Scholar collects research papers from all over the web, including grey literature and non-peer reviewed papers and reports.

Google Scholar does not provide any full text content itself, but links to the full text article on the publisher page, which can either be open access or paywalled content. Google Scholar tries to provide links to free versions, when possible.

The easiest way to access Google scholar is by using The Google Scholar Button. This is a browser extension that allows you easily access Google Scholar from any web page. You can install it from the Chrome Webstore .

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Research: When Bonuses Backfire

  • Dirk Sliwka
  • Timo Vogelsang

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How to rethink your incentive strategy and reward employees in ways that actually motivate them.

Why do bonuses sometimes backfire? It’s because each incentive design choice both signals information about your own beliefs and intentions as an employer and shapes the signaling value of employee behavior within the organization. If you don’t think through these signals carefully, you may end up approving a bonus scheme with results that are the opposite of what you intend. This article offers a way to help you align the signals your incentive scheme sends with your performance goals.

More than 30 years ago, author and lecturer Alfie Kohn, in a rather controversial but often cited HBR article , claimed that “rewards typically undermine the very processes they are intended to enhance.” Yet until recently, nearly all scientific studies that have documented such “backfiring” effects have been confined to laboratory experiments or field settings outside of the firm. This may cause some to question whether these effects are really present in commercial contexts. Our new research, which consists of two large field experiments in retail organizations, demonstrates that they do indeed occur.

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  • DS Dirk Sliwka is a professor of management in the Faculty of Management, Economics, and Social Sciences at the University of Cologne in Germany
  • TV Timo Vogelsang is an Associate Professor of Managerial Accounting at the Frankfurt School of Finance and Management in Germany

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Key things to know about U.S. election polling in 2024

Conceptual image of an oversized voting ballot box in a large crowd of people with shallow depth of field

Confidence in U.S. public opinion polling was shaken by errors in 2016 and 2020. In both years’ general elections, many polls underestimated the strength of Republican candidates, including Donald Trump. These errors laid bare some real limitations of polling.

In the midterms that followed those elections, polling performed better . But many Americans remain skeptical that it can paint an accurate portrait of the public’s political preferences.

Restoring people’s confidence in polling is an important goal, because robust and independent public polling has a critical role to play in a democratic society. It gathers and publishes information about the well-being of the public and about citizens’ views on major issues. And it provides an important counterweight to people in power, or those seeking power, when they make claims about “what the people want.”

The challenges facing polling are undeniable. In addition to the longstanding issues of rising nonresponse and cost, summer 2024 brought extraordinary events that transformed the presidential race . The good news is that people with deep knowledge of polling are working hard to fix the problems exposed in 2016 and 2020, experimenting with more data sources and interview approaches than ever before. Still, polls are more useful to the public if people have realistic expectations about what surveys can do well – and what they cannot.

With that in mind, here are some key points to know about polling heading into this year’s presidential election.

Probability sampling (or “random sampling”). This refers to a polling method in which survey participants are recruited using random sampling from a database or list that includes nearly everyone in the population. The pollster selects the sample. The survey is not open for anyone who wants to sign up.

Online opt-in polling (or “nonprobability sampling”). These polls are recruited using a variety of methods that are sometimes referred to as “convenience sampling.” Respondents come from a variety of online sources such as ads on social media or search engines, websites offering rewards in exchange for survey participation, or self-enrollment. Unlike surveys with probability samples, people can volunteer to participate in opt-in surveys.

Nonresponse and nonresponse bias. Nonresponse is when someone sampled for a survey does not participate. Nonresponse bias occurs when the pattern of nonresponse leads to error in a poll estimate. For example, college graduates are more likely than those without a degree to participate in surveys, leading to the potential that the share of college graduates in the resulting sample will be too high.

Mode of interview. This refers to the format in which respondents are presented with and respond to survey questions. The most common modes are online, live telephone, text message and paper. Some polls use more than one mode.

Weighting. This is a statistical procedure pollsters perform to make their survey align with the broader population on key characteristics like age, race, etc. For example, if a survey has too many college graduates compared with their share in the population, people without a college degree are “weighted up” to match the proper share.

How are election polls being conducted?

Pollsters are making changes in response to the problems in previous elections. As a result, polling is different today than in 2016. Most U.S. polling organizations that conducted and publicly released national surveys in both 2016 and 2022 (61%) used methods in 2022 that differed from what they used in 2016 . And change has continued since 2022.

A sand chart showing that, as the number of public pollsters in the U.S. has grown, survey methods have become more diverse.

One change is that the number of active polling organizations has grown significantly, indicating that there are fewer barriers to entry into the polling field. The number of organizations that conduct national election polls more than doubled between 2000 and 2022.

This growth has been driven largely by pollsters using inexpensive opt-in sampling methods. But previous Pew Research Center analyses have demonstrated how surveys that use nonprobability sampling may have errors twice as large , on average, as those that use probability sampling.

The second change is that many of the more prominent polling organizations that use probability sampling – including Pew Research Center – have shifted from conducting polls primarily by telephone to using online methods, or some combination of online, mail and telephone. The result is that polling methodologies are far more diverse now than in the past.

(For more about how public opinion polling works, including a chapter on election polls, read our short online course on public opinion polling basics .)

All good polling relies on statistical adjustment called “weighting,” which makes sure that the survey sample aligns with the broader population on key characteristics. Historically, public opinion researchers have adjusted their data using a core set of demographic variables to correct imbalances between the survey sample and the population.

But there is a growing realization among survey researchers that weighting a poll on just a few variables like age, race and gender is insufficient for getting accurate results. Some groups of people – such as older adults and college graduates – are more likely to take surveys, which can lead to errors that are too sizable for a simple three- or four-variable adjustment to work well. Adjusting on more variables produces more accurate results, according to Center studies in 2016 and 2018 .

A number of pollsters have taken this lesson to heart. For example, recent high-quality polls by Gallup and The New York Times/Siena College adjusted on eight and 12 variables, respectively. Our own polls typically adjust on 12 variables . In a perfect world, it wouldn’t be necessary to have that much intervention by the pollster. But the real world of survey research is not perfect.

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Predicting who will vote is critical – and difficult. Preelection polls face one crucial challenge that routine opinion polls do not: determining who of the people surveyed will actually cast a ballot.

Roughly a third of eligible Americans do not vote in presidential elections , despite the enormous attention paid to these contests. Determining who will abstain is difficult because people can’t perfectly predict their future behavior – and because many people feel social pressure to say they’ll vote even if it’s unlikely.

No one knows the profile of voters ahead of Election Day. We can’t know for sure whether young people will turn out in greater numbers than usual, or whether key racial or ethnic groups will do so. This means pollsters are left to make educated guesses about turnout, often using a mix of historical data and current measures of voting enthusiasm. This is very different from routine opinion polls, which mostly do not ask about people’s future intentions.

When major news breaks, a poll’s timing can matter. Public opinion on most issues is remarkably stable, so you don’t necessarily need a recent poll about an issue to get a sense of what people think about it. But dramatic events can and do change public opinion , especially when people are first learning about a new topic. For example, polls this summer saw notable changes in voter attitudes following Joe Biden’s withdrawal from the presidential race. Polls taken immediately after a major event may pick up a shift in public opinion, but those shifts are sometimes short-lived. Polls fielded weeks or months later are what allow us to see whether an event has had a long-term impact on the public’s psyche.

How accurate are polls?

The answer to this question depends on what you want polls to do. Polls are used for all kinds of purposes in addition to showing who’s ahead and who’s behind in a campaign. Fair or not, however, the accuracy of election polling is usually judged by how closely the polls matched the outcome of the election.

A diverging bar chart showing polling errors in U.S. presidential elections.

By this standard, polling in 2016 and 2020 performed poorly. In both years, state polling was characterized by serious errors. National polling did reasonably well in 2016 but faltered in 2020.

In 2020, a post-election review of polling by the American Association for Public Opinion Research (AAPOR) found that “the 2020 polls featured polling error of an unusual magnitude: It was the highest in 40 years for the national popular vote and the highest in at least 20 years for state-level estimates of the vote in presidential, senatorial, and gubernatorial contests.”

How big were the errors? Polls conducted in the last two weeks before the election suggested that Biden’s margin over Trump was nearly twice as large as it ended up being in the final national vote tally.

Errors of this size make it difficult to be confident about who is leading if the election is closely contested, as many U.S. elections are .

Pollsters are rightly working to improve the accuracy of their polls. But even an error of 4 or 5 percentage points isn’t too concerning if the purpose of the poll is to describe whether the public has favorable or unfavorable opinions about candidates , or to show which issues matter to which voters. And on questions that gauge where people stand on issues, we usually want to know broadly where the public stands. We don’t necessarily need to know the precise share of Americans who say, for example, that climate change is mostly caused by human activity. Even judged by its performance in recent elections, polling can still provide a faithful picture of public sentiment on the important issues of the day.

The 2022 midterms saw generally accurate polling, despite a wave of partisan polls predicting a broad Republican victory. In fact, FiveThirtyEight found that “polls were more accurate in 2022 than in any cycle since at least 1998, with almost no bias toward either party.” Moreover, a handful of contrarian polls that predicted a 2022 “red wave” largely washed out when the votes were tallied. In sum, if we focus on polling in the most recent national election, there’s plenty of reason to be encouraged.

Compared with other elections in the past 20 years, polls have been less accurate when Donald Trump is on the ballot. Preelection surveys suffered from large errors – especially at the state level – in 2016 and 2020, when Trump was standing for election. But they performed reasonably well in the 2018 and 2022 midterms, when he was not.

Pew Research Center illustration

During the 2016 campaign, observers speculated about the possibility that Trump supporters might be less willing to express their support to a pollster – a phenomenon sometimes described as the “shy Trump effect.” But a committee of polling experts evaluated five different tests of the “shy Trump” theory and turned up little to no evidence for each one . Later, Pew Research Center and, in a separate test, a researcher from Yale also found little to no evidence in support of the claim.

Instead, two other explanations are more likely. One is about the difficulty of estimating who will turn out to vote. Research has found that Trump is popular among people who tend to sit out midterms but turn out for him in presidential election years. Since pollsters often use past turnout to predict who will vote, it can be difficult to anticipate when irregular voters will actually show up.

The other explanation is that Republicans in the Trump era have become a little less likely than Democrats to participate in polls . Pollsters call this “partisan nonresponse bias.” Surprisingly, polls historically have not shown any particular pattern of favoring one side or the other. The errors that favored Democratic candidates in the past eight years may be a result of the growth of political polarization, along with declining trust among conservatives in news organizations and other institutions that conduct polls.

Whatever the cause, the fact that Trump is again the nominee of the Republican Party means that pollsters must be especially careful to make sure all segments of the population are properly represented in surveys.

The real margin of error is often about double the one reported. A typical election poll sample of about 1,000 people has a margin of sampling error that’s about plus or minus 3 percentage points. That number expresses the uncertainty that results from taking a sample of the population rather than interviewing everyone . Random samples are likely to differ a little from the population just by chance, in the same way that the quality of your hand in a card game varies from one deal to the next.

A table showing that sampling error is not the only kind of polling error.

The problem is that sampling error is not the only kind of error that affects a poll. Those other kinds of error, in fact, can be as large or larger than sampling error. Consequently, the reported margin of error can lead people to think that polls are more accurate than they really are.

There are three other, equally important sources of error in polling: noncoverage error , where not all the target population has a chance of being sampled; nonresponse error, where certain groups of people may be less likely to participate; and measurement error, where people may not properly understand the questions or misreport their opinions. Not only does the margin of error fail to account for those other sources of potential error, putting a number only on sampling error implies to the public that other kinds of error do not exist.

Several recent studies show that the average total error in a poll estimate may be closer to twice as large as that implied by a typical margin of sampling error. This hidden error underscores the fact that polls may not be precise enough to call the winner in a close election.

Other important things to remember

Transparency in how a poll was conducted is associated with better accuracy . The polling industry has several platforms and initiatives aimed at promoting transparency in survey methodology. These include AAPOR’s transparency initiative and the Roper Center archive . Polling organizations that participate in these organizations have less error, on average, than those that don’t participate, an analysis by FiveThirtyEight found .

Participation in these transparency efforts does not guarantee that a poll is rigorous, but it is undoubtedly a positive signal. Transparency in polling means disclosing essential information, including the poll’s sponsor, the data collection firm, where and how participants were selected, modes of interview, field dates, sample size, question wording, and weighting procedures.

There is evidence that when the public is told that a candidate is extremely likely to win, some people may be less likely to vote . Following the 2016 election, many people wondered whether the pervasive forecasts that seemed to all but guarantee a Hillary Clinton victory – two modelers put her chances at 99% – led some would-be voters to conclude that the race was effectively over and that their vote would not make a difference. There is scientific research to back up that claim: A team of researchers found experimental evidence that when people have high confidence that one candidate will win, they are less likely to vote. This helps explain why some polling analysts say elections should be covered using traditional polling estimates and margins of error rather than speculative win probabilities (also known as “probabilistic forecasts”).

National polls tell us what the entire public thinks about the presidential candidates, but the outcome of the election is determined state by state in the Electoral College . The 2000 and 2016 presidential elections demonstrated a difficult truth: The candidate with the largest share of support among all voters in the United States sometimes loses the election. In those two elections, the national popular vote winners (Al Gore and Hillary Clinton) lost the election in the Electoral College (to George W. Bush and Donald Trump). In recent years, analysts have shown that Republican candidates do somewhat better in the Electoral College than in the popular vote because every state gets three electoral votes regardless of population – and many less-populated states are rural and more Republican.

For some, this raises the question: What is the use of national polls if they don’t tell us who is likely to win the presidency? In fact, national polls try to gauge the opinions of all Americans, regardless of whether they live in a battleground state like Pennsylvania, a reliably red state like Idaho or a reliably blue state like Rhode Island. In short, national polls tell us what the entire citizenry is thinking. Polls that focus only on the competitive states run the risk of giving too little attention to the needs and views of the vast majority of Americans who live in uncompetitive states – about 80%.

Fortunately, this is not how most pollsters view the world . As the noted political scientist Sidney Verba explained, “Surveys produce just what democracy is supposed to produce – equal representation of all citizens.”

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How do people in the U.S. take Pew Research Center surveys, anyway?

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Activity of convalescent and vaccine serum against SARS-CoV-2 Omicron

Sera from unvaccinated, vaccinated, and previously infected and vaccinated individuals show reduced neutralizing and spike protein-binding activity towards the Omicron (B.1.1.529) variant of SARS-CoV-2 compared to other variants.

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Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies

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Striking antibody evasion manifested by the Omicron variant of SARS-CoV-2

The B.1.1.529/Omicron variant of SARS-CoV-2 is resistant to neutralization by serum not only from patients who recovered from COVID-19, but also from individuals vaccinated with one of the four widely used COVID-19 vaccines.

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Time-resolved structural analysis of an RNA-cleaving DNA catalyst

Using high-resolution NMR characterization, the kinetics and dynamics of the catalytic function of a DNAzyme are shown.

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Evolution of enhanced innate immune evasion by SARS-CoV-2

The SARS-CoV-2 Alpha variant suppresses innate immune responses more effectively than isolates of first-wave SARS-CoV-2, and this is a result of mutations outside of the spike coding region that lead to upregulation of viral innate immune antagonists.

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Broadly neutralizing antibodies overcome SARS-CoV-2 Omicron antigenic shift

Pseudovirus assays and surface plasmon resonance show that the Omicron receptor-binding domain binds to human ACE2 with increased affinity relative to the ancestral virus, and that most neutralizing antibodies are considerably less potent against Omicron.

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SARS-CoV-2 infection in free-ranging white-tailed deer

More than one-third of wild deer tested in northeast Ohio showed evidence of SARS-CoV-2 infection of human origin.

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Omicron extensively but incompletely escapes Pfizer BNT162b2 neutralization

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Single-year radiocarbon dating anchors Viking Age trade cycles in time

Disturbances in the radiocarbon record anchor a precisely dated archaeological stratigraphy of a medieval trading emporium in Denmark in time, revealing that the Viking expansion was associated with competition for trade routes rather than with raids.

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MicroRNA sequence codes for small extracellular vesicle release and cellular retention

MicroRNAs encode sorting sequences that determine whether they are secreted in exosomal vesicles to regulate gene expression in distant cells or retained in cells that produced them, with different sequences used by individual cell types.

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A high-resolution picture of kinship practices in an Early Neolithic tomb

Archaeological and ancient DNA analyses of 35 individuals entombed at Hazleton North long cairn approximately 5,700 years ago are used to reconstruct kinship practices in Early Neolithic Britain.

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Local and systemic responses to SARS-CoV-2 infection in children and adults

Mechanisms explaining the milder clinical syndrome that is observed in children with SARS-CoV-2 infection.

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Targeting SWI/SNF ATPases in enhancer-addicted prostate cancer

PROTAC degrader–induced SWI/SNF inactivation abolishes DNA accessibility at enhancer elements of oncogenes and also tempers supra-physiologic expression of driver transcription factors, resulting in potent inhibition of tumour growth in mouse models.

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https://www.nist.gov/news-events/news/2024/08/us-ai-safety-institute-signs-agreements-regarding-ai-safety-research

U.S. AI Safety Institute Signs Agreements Regarding AI Safety Research, Testing and Evaluation With Anthropic and OpenAI

These first-of-their-kind agreements between the u.s. government and industry will help advance safe and trustworthy ai innovation for all..

GAITHERSBURG, Md. — Today, the U.S. Artificial Intelligence Safety Institute at the U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) announced agreements that enable formal collaboration on AI safety research, testing and evaluation with both Anthropic and OpenAI.

Each company’s Memorandum of Understanding establishes the framework for the U.S. AI Safety Institute to receive access to major new models from each company prior to and following their public release. The agreements will enable collaborative research on how to evaluate capabilities and safety risks, as well as methods to mitigate those risks. 

“Safety is essential to fueling breakthrough technological innovation. With these agreements in place, we look forward to beginning our technical collaborations with Anthropic and OpenAI to advance the science of AI safety,” said Elizabeth Kelly, director of the U.S. AI Safety Institute. “These agreements are just the start, but they are an important milestone as we work to help responsibly steward the future of AI.”

Additionally, the U.S. AI Safety Institute plans to provide feedback to Anthropic and OpenAI on potential safety improvements to their models, in close collaboration with its partners at the U.K. AI Safety Institute. 

The U.S. AI Safety Institute builds on NIST’s more than 120-year legacy of advancing measurement science, technology, standards and related tools. Evaluations under these agreements will further NIST’s work on AI by facilitating deep collaboration and exploratory research on advanced AI systems across a range of risk areas.

Evaluations conducted pursuant to these agreements will help advance the safe, secure and trustworthy development and use of AI by building on the Biden-Harris administration’s Executive Order on AI and the voluntary commitments made to the administration by leading AI model developers.

About the U.S. AI Safety Institute

The U.S. AI Safety Institute , located within the Department of Commerce at the National Institute of Standards and Technology (NIST), was established following the Biden-Harris administration’s 2023 Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence to advance the science of AI safety and address the risks posed by advanced AI systems. It is tasked with developing the testing, evaluations and guidelines that will help accelerate safe AI innovation here in the United States and around the world. 

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Cannabis and hallucinogen use among adults remained at historic highs in 2023

Vaping among younger adults and binge drinking among mid-life adults also maintained historically high levels, NIH-supported study shows

Young woman thoughtfully looking around while moving up on an escalator in a subway station

Past-year use of cannabis and hallucinogens stayed at historically high levels in 2023 among adults aged 19 to 30 and 35 to 50, according to the latest findings  from the  Monitoring the Future survey . In contrast, past-year use of cigarettes remained at historically low levels in both adult groups. Past-month and daily alcohol use continued a decade-long decline among those 19 to 30 years old, with binge drinking reaching all-time lows. However, among 35- to 50-year-olds, the prevalence of binge drinking in 2023 increased from five and 10 years ago. The Monitoring the Future study is conducted by scientists at the University of Michigan’s Institute for Social Research, Ann Arbor, and is funded by the National Institutes of Health.

Reports of vaping nicotine or vaping cannabis in the past year among adults 19 to 30 rose over five years, and both trends remained at record highs in 2023. Among adults 35 to 50, the prevalences of nicotine vaping and of cannabis vaping stayed steady from the year before, with long-term (five and 10 year) trends not yet observable in this age group as this question was added to the survey for this age group in 2019.

For the first time in 2023, 19- to 30-year-old female respondents reported a higher prevalence of past-year cannabis use than male respondents in the same age group, reflecting a reversal of the gap between sexes. Conversely, male respondents 35 to 50 years old maintained a higher prevalence of past-year cannabis use than female respondents of the same age group, consistent with what’s been observed for the past decade.

“We have seen that people at different stages of adulthood are trending toward use of drugs like cannabis and psychedelics and away from tobacco cigarettes,” said Nora D. Volkow, M.D., director of NIH’s National Institute on Drug Abuse (NIDA). “These findings underscore the urgent need for rigorous research on the potential risks and benefits of cannabis and hallucinogens – especially as new products continue to emerge.”

Since 1975, the Monitoring the Future study has annually surveyed substance use behaviors and attitudes among a nationally representative sample of teens. A longitudinal panel study component of Monitoring the Future conducts follow-up surveys on a subset of these participants (now totaling approximately 20,000 people per year), collecting data from individuals every other year from ages 19 to 30 and every five years after the participants turn 30 to track their drug use through adulthood. Participants self-report their drug use behaviors across various time periods, including lifetime, past year (12 months), past month (30 days), and other use frequencies depending on the substance type. Data for the 2023 panel study were collected via online and paper surveys from April 2023 through October 2023.

Full data summaries and data tables showing the trends below, including breakdowns by substance, are available in the report . Key findings include:

Cannabis use in the past year and past month remained at historically high levels for both adult age groups in 2023. Among adults 19 to 30 years old, approximately 42% reported cannabis use in the past year, 29% in the past month, and 10% daily use (use on 20 or more occasions in the past 30 days). Among adults 35 to 50, reports of use reached 29%, 19%, and 8%, respectively. While these 2023 estimates are not statistically different from those of 2022, they do reflect five- and 10-year increases for both age groups.

Cannabis vaping in the past year and past month was reported by 22% and 14% of adults 19 to 30, respectively, and by 9% and 6% of adults 35 to 50 in 2023. For the younger group, these numbers represent all-time study highs and an increase from five years ago.

Nicotine vaping among adults 19 to 30 maintained historic highs in 2023. Reports of past-year and past-month vaping of nicotine reached 25% and 19%, respectively. These percentages represent an increase from five years ago, but not from one year ago. For adults 35 to 50, the prevalence of vaping nicotine remained steady from the year before (2022), with 7% and 5% reporting past-year and past-month use.

Hallucinogen use in the past year continued a five-year steep incline for both adult groups, reaching 9% for adults 19 to 30 and 4% for adults 35 to 50 in 2023. Types of hallucinogens reported by participants included LSD, mescaline, peyote, shrooms or psilocybin, and PCP.

Alcohol remains the most used substance reported among adults in the study. Past-year alcohol use among adults 19 to 30 has showed a slight upward trend over the past five years, with 84% reporting use in 2023. However, past month drinking (65%), daily drinking (4%), and binge drinking (27%) all remained at study lows in 2023 among adults 19 to 30. These numbers have decreased from 10 years ago. Past-month drinking and binge drinking (having five or more drinks in a row in the past two week period) decreased significantly from the year before for this age group (down from 68% for past month and 31% for binge drinking reported in 2022).

Around 84% of adults 35 to 50 reported past-year alcohol use in 2023, which has not significantly changed from the year before or the past five or 10 years. Past-month alcohol use and binge drinking have slightly increased over the past 10 years for this age group; in 2023, past-month alcohol use was at 69% and binge drinking was at 27%. Daily drinking has decreased in this group over the past five years and was at its lowest level ever recorded in 2023 (8%).

Additional data: In 2023, past-month cigarette smoking, past-year nonmedical use of prescription drugs, and past-year use of opioid medications (surveyed as “narcotics other than heroin”) maintained five- and 10-year declines for both adult groups. Among adults 19 to 30 years old, past-year use of stimulants (surveyed as “amphetamines”) has decreased for the past decade, whereas for adults 35 to 50, past-year stimulant use has been modestly increasing over 10 years. Additional data include drug use reported by college/non-college young adults and among various demographic subgroups, including sex and gender and race and ethnicity.

The 2023 survey year was the first time a cohort from the Monitoring the Future study reached 65 years of age; therefore, trends for the 55- to 65-year-old age group are not yet available.

“The data from 2023 did not show us many significant changes from the year before, but the power of surveys such as Monitoring the Future is to see the ebb and flow of various substance use trends over the longer term,” said Megan Patrick, Ph.D., of the University of Michigan and principal investigator of the Monitoring the Future panel study. “As more and more of our original cohorts – first recruited as teens – now enter later adulthood, we will be able to examine the patterns and effects of drug use throughout the life course. In the coming years, this study will provide crucial data on substance use trends and health consequences among older populations, when people may be entering retirement and other new chapters of their lives.”

View more information on data collection methods for the Monitoring the Future panel study and how the survey adjusts for the effects of potential exclusions in the report . Results from the related 2023 Monitoring the Future study of substance use behaviors and related attitudes among teens in the United States were released in December 2023, and 2024 results are upcoming in December 2024.

If you or someone you know is struggling or in crisis, help is available. Call or text 988 or chat at 988lifeline.org . To learn how to get support for mental health, drug or alcohol conditions visit  FindSupport.gov . If you are ready to locate a treatment facility or provider, you can go directly to  FindTreatment.gov or call  800-662-HELP (4357) .

About the National Institute on Drug Abuse (NIDA): NIDA is a component of the National Institutes of Health, U.S. Department of Health and Human Services. NIDA supports most of the world’s research on the health aspects of drug use and addiction. The Institute carries out a large variety of programs to inform policy, improve practice, and advance addiction science. For more information about NIDA and its programs, visit www.nida.nih.gov .

About the National Institutes of Health (NIH): NIH, the nation’s medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov .

About substance use disorders: Substance use disorders are chronic, treatable conditions from which people can recover. In 2022, nearly 49 million people in the United States had at least one substance use disorder. Substance use disorders are defined in part by continued use of substances despite negative consequences. They are also relapsing conditions, in which periods of abstinence (not using substances) can be followed by a return to use. Stigma can make individuals with substance use disorders less likely to seek treatment. Using preferred language can help accurately report on substance use and addiction. View NIDA’s online guide .

NIH…Turning Discovery Into Health®

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UConn Today

September 3, 2024 | Thomas Rettig

Electrical Aviation

UConn research is on the cutting edge of research into decarbonizing aviation

UConn research is on the cutting edge of research into decarbonizing aviation ( )

In recent decades, carbon emissions in the aviation sector have grown faster than in shipping, rail, or road. What’s more, aviation presents one of the biggest challenges for decarbonization, given that there’s no aircraft equivalent of the electric cars that are becoming increasingly popular.

That might change in the future, though, if Xiao-Dong Zhou, Director of the Center for Clean Energy Engineering and the Nicholas E. Madonna Chair in Sustainability at UConn, and his students have anything to say about it.

One of their projects involves using fuel cell technology to develop electrically powered aircraft – something they’ve demonstrated can be done in a prototype. That kind of hands-on experimentation is critical, Zhou explains.

“We are not only doing research, we are also training students to get excited about this field,” he says.

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Mobile phone use doesn't increase brain cancer risk, says research review

The authors also found no increased risk of leukaemia or brain cancers in children from radio or TV transmitters or mobile phone base stations.

Tuesday 3 September 2024 16:29, UK

File pic: iStock

A review of 63 studies has found no link between mobile phone use and an increased risk of brain cancer.

Commissioned by the World Health Organization (WHO), it found no rise in cases despite a huge increase in wireless technology over the last 20 years.

The review was headed by experts from the Australian Radiation Protection and Nuclear Safety Agency, and included investigators from 10 countries.

It looked at research on radio frequencies in the wavelengths of 300 Hz to 300 GHz - used for mobile phones, wi-fi, radar, baby monitors and other applications.

Co-author of the review Professor Mark Elwood, an honorary professor of cancer epidemiology at University of Auckland, said the team looked at cancers of the brain, pituitary gland, salivary glands, and leukaemias.

"None of the major questions studied showed increased risks," he said.

"For the main issue, mobile phones and brain cancers, we found no increased risk, even with 10+ years exposure and the maximum categories of call time or number of calls."

During the pandemic, 5G mobile phone masts were attacked in the UK and elsewhere in the baseless belief they were contributing to the virus.

The research review looked at 63 relevant articles, published between 1994 and 2022, from 22 countries.

Communication engineers work on a mobile phone mast near Knutsford, northern England, April 8, 2016. REUTERS/Phil Noble

"For mobile phones and brain cancers, there were studies with 10 or more years' use, and quite extensive use," said Professor Elwood.

"Most phone use in these studies was from past years and 1G -2G networks; the newer 3G-4G networks have substantially lower RF emissions.

"There were several studies that reported some increased risks, but these were outweighed in considering all the available evidence."

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When it comes to 5G mobile networks, Professor Elwood said there were no major studies so far, but that studies of radar - which has similar high frequencies - did not show an increased brain cancer risk.

The review is published in the Environment International journal and took four years to complete.

The risk in relation to other cancer types is due to be reported separately.

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Read more from Sky News: Brazil's Supreme Court upholds X ban Strange noises from Boeing spacecraft aren't serious - NASA

Professor Alberto Najera, a physicist and expert on radio frequencies and health at the University of Castilla-La Mancha in Spain, praised the "exhaustive systematic review".

He said the conclusions were "robust" and "supported by quality studies".

"The main implications of this study are that, according to the best available evidence to date, exposure to radiofrequency electromagnetic fields, such as those produced by mobile phones or telephone antennas, does not appear to significantly increase the risk of developing cancer," said Professor Najera.

Silvi Shah, MD, shown in the UC College of Medicine

UC physician studies which dialysis may work better at home

Silvi shah, md, speaks with local 12 news about her latest dialysis research.

headshot of Cedric Ricks

Globally, more than 2 million people undergo dialysis each year, and about 550,000 undergo the procedure in the United States. These patients may benefit from the latest research findings from Silvi Shah, MD, associate professor in the UC College of Medicine. 

She led a team of researchers who found that dialysis patients using a more traditional home hemodialysis procedure have lower incidence of cardiovascular disease than patients using a less invasive peritoneal catheter for dialysis at home.

"Cardiovascular disease is the leading cause of death in patients who have kidney failure and who are on dialysis," Shah told Local 12 News for a recent segment featuring her research.

Shah studied the medical outcomes of thousands of patients who used home hemodialysis and peritoneal dialysis. The findings were published in Kidney360 , an open access journal of the American Society of Nephrology, and showed that patients on home hemodialysis had a 42% lower risk of stroke, 17% lower risk of acute coronary syndrome, 22% lower risk of cardiovascular death and 8% lower risk of death.

Knowing the health outcomes can help patients determine their options if they have the choice of home hemodialysis or peritoneal dialysis. Patients also consider lifestyle choices when deciding on dialysis options. Petritoneal dialysis can be done at night while the patient is sleeping.

View the Local 12 News segment featuring Dr. Shah’s research.

Learn more about Dr. Shah’s work online .

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  27. Cannabis and hallucinogen use among adults remained at historic highs

    However, among 35- to 50-year-olds, the prevalence of binge drinking in 2023 increased from five and 10 years ago. The Monitoring the Future study is conducted by scientists at the University of Michigan's Institute for Social Research, Ann Arbor, and is funded by the National Institutes of Health.

  28. Electrical Aviation

    UConn research is on the cutting edge of research into decarbonizing aviation In recent decades, carbon emissions in the aviation sector have grown faster than in shipping, rail, or road. What's more, aviation presents one of the biggest challenges for decarbonization, given that there's no aircraft equivalent of the electric cars that are ...

  29. Mobile phone use doesn't increase brain cancer risk, says research

    The research review looked at 63 relevant articles, published between 1994 and 2022, from 22 countries. Advertisement Image: During the pandemic, wild theories circulated linking COVID to 5G masts.

  30. Local 12 News features the latest dialysis research from Silvi Shah, MD

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