University of South Carolina, The Daily Gamecock student newspaper, Editorial
from
Another act of deception from our school’s leadership is the supposed $11 million budget over the next five years for diversity and inclusion, a supposed initiative “to further the commission’s recommendations.”
Despite the implication that this money was new funding, it was actually the already existing diversity budget being marketed as new, in an attempt to offset the administration’s egregious inaction.
The Salk specializes in basic science. But it has begun to do more to help translate its findings into therapeutic drugs and to work on practical ways to fight climate change, such as developing plants that absorb greater amounts of carbon dioxide.
As part of the change, the institute has been heavily investing in computational biology, a field where the ever-growing ability to analyze massive data sets enabled scientists to quickly determine the genetic makeup of the various strains of COVID-19.
A Johns Hopkins engineer co-led a team that has sequenced the genome of the world’s most widely used model plant species, Arabidopsis thaliana, at a level of detail never previously achieved. Up until now, regions of this genome—including centromeres, the spindles which guide chromosomes as an organism grows rapidly from one to trillions of cells—have remained uncharted territory, due to their complex structure. Now, for the first time, researchers have revealed the secrets of the Arabidopsis centromeres, shedding light on their evolution, and providing insights into a paradox that has mystified scientists for decades. Their results were published Nov. 12 in Science.
Illinois Newsroom, Dana Cronin and Johnathan Hettinger
from
In 2013, mammoth U.S. investment company TIAA-CREF gave $5 million to the University of Illinois — to study an area of investment where the company has made a, sometimes controversial, name for itself. … As part of its Big Ag U series on the influence of corporations on public universities across the Midwest, Harvest Public Media and Investigate Midwest combed through documents related to the founding of the TIAA Center for Farmland Research to find out how it operates under the name of the number one farmland manager in the world, and one that’s been marked by controversy.
Johns Hopkins has received a $20 million grant from the National Institute on Aging to develop artificial intelligence (AI) devices to improve the lives of older people.
Researchers from the Johns Hopkins schools of Medicine, Nursing, the Whiting School of Engineering, and the Carey Business School will collaborate on the project.
In a proof-of-concept study, scientists at Delft University of Technology in the Netherlands and the University of Illinois have successfully repurposed DNA nanopore sequencing technology to scan single protein molecules.
As a helicase enzyme pulls a DNA-bound peptide string through a minuscule membrane channel, researchers can now decode changes in ion currents through the nanopore to read off the individual amino acid building blocks of the peptide one at a time. This ability is a landmark in protein identification, paving the way for single-molecule protein fingerprinting, de novo protein sequencing, and analyzing dynamic cellular proteomes.
California News Times, TechCrunch, Joe Hellerstein
from
“Data depletion,” a by-product of exponentially increasing calculations in the form of log files, has increased significantly, but standardized data has increased slightly.
As a result, instead of using uniform machine-oriented data, the variety of data and data types has increased significantly, resulting in poor data governance.
In addition to data depletion and machine-generated data, we have begun hostile use of data. This happened because the people involved in the data had many different incentives for their use.
This week, a handful of academic researcher teams will gain access to a new tool from Facebook designed to aggregate near-universal real-time data on the world’s biggest social network.
When it comes to who gets access to Facebook data and how, the company now known as Meta is still feeling reverberations from 2018’s Cambridge Analytica scandal, in which a political consulting firm harvested the personal data of millions of unaware Facebook users to build detailed profiles on potential voters. The company shut down thousands of APIs in the three years that followed and is only now beginning to restore broad access for academic research.
TechCrunch previewed Facebook’s new academic research API and spoke with Facebook Product Manager Kiran Jagadeesh, who spearheaded the project with the Facebook Open Research & Transparency (FORT) team.
The artificial intelligence (AI) revolution in protein structure prediction continues. Only 1 year ago, software programs first succeeded in modeling the 3D shapes of individual proteins as accurately as decades-old experimental techniques can determine them. This summer, researchers used those AI programs to assemble a near-complete catalog of human protein structures. Now, researchers have upped the ante once again, unveiling a combination of programs that can determine which proteins are likely to interact with one another and what the resulting complexes— crucial engines of the cell—look like.
“It’s a really cool result,” says Michael Snyder, a systems biologist at Stanford University. “Everything in biology works in complexes. So, knowing who works with who is critical.” Those relationships were hard to reach with previous techniques. The new ability to predict them, he says, should yield an array of insights into cell biology and possibly reveal new targets for the next generation of therapeutic drugs.
@SchultzzyRun
and I use the Survey of Earned Doctorates – a census of all PhDs from US institutions – to study the socioeconomic background of econ PhDs
To proxy for socioeconomic background, we use the highest level of parental education.
In this preliminary work, we’re focusing just on US-born individuals (30% of US econ PhDs) since parental education means diff’t things for SES across diff’t countries.
Every day, millions of people take selfies with their smartphones or webcams to share online. And they almost invariably smile when they do so.
To Ehsan Hoque and his collaborators at the University of Rochester, those pictures are worth far more than the proverbial “thousand words.” Computer vision software—based on algorithms that the computer scientist and his lab have developed—can analyze the brief videos, including the short clips created while taking selfies, detecting subtle movements of facial muscles that are invisible to the naked eye.
The software can then predict with remarkable accuracy whether a person who takes a selfie is likely to develop Parkinson’s disease—as reliably as expensive, wearable digital biomarkers that monitor motor symptoms.
Pew Research Center; Colleen McClain, Regina Widjaya, Gonzalo Rivero and Aaron Smith
from
A minority of Twitter users produce a majority of tweets from U.S. adults, and the most active tweeters are less likely to view the tone or civility of discussions as a major problem on the site
The National Student Clearinghouse announced Monday it’s working with an AI company to associate the experience earned through various degrees, credentials and internships with skills needed by employers.
The organization, which offers digital information services for more than 3,600 higher education institutions, is examining how to use tools from AstrumU, which develops technology to help fill gaps in the workforce. AstrumU tools, already used at universities nationwide, use data from both employers and higher education institutions to recommend students potential careers through using machine learning to parse students’ experiences.
The partnership is addressing a problem pervasive in career services and higher education, in which employers can’t easily find matches for their open positions who earned relevant experience outside of a traditional degree.
Boston, MA November 30, starting at 4 p.m. “Attendees will hear from BU data scientists engaged in research that uncovers racial inequity in a variety of contexts and provides a data-driven pathway to an equitable society.” [rsvp required]
Leading entrepreneurs and luminaries representing a swath of the technology sector are uniting to voice their support for Code.org and Hour of Code in a call for increased computer science access and equitable representation of women and people of color across the industry.
For a limited time from November 9 through December 2, a collective of leaders — including Marc Benioff, Stacy Brown-Philpot, Mark Cuban, Reid Hoffman, Ashton Kutcher, Ellen Pao, Jennifer Tejada, and more — are offering supporters the unique opportunity to receive an elusive Twitter “follow” from one of them, and at the same time, make a meaningful impact in advancing computer science education, particularly for young women and students from groups underrepresented in computer science.
Berkeley, CA February 10-11, 2022. “The BITSS Annual Meeting brings together actors from academia, scholarly publishing, and policy to share novel research and discuss efforts to improve the credibility of social science by advancing research transparency, reproducibility, rigor, and ethics.” Deadline for submissions is December 5.
SPONSORED CONTENT
The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
Twitter, Engineering blog, Lu Zhang and Chukwudiuto Malife
from
For the interaction and engagement pipeline, we collect and process data from various real-time streams and server and client logs, to extract Tweet and user interaction data with various levels of aggregations, time granularities, and other metrics dimensions. That aggregated interaction data is particularly important and is the source of truth for Twitter’s ads revenue services and data product services to retrieve information on impression and engagement metrics. In addition, we need to guarantee fast queries on the interaction data in the storage systems with low latency and high accuracy across different data centers. To build such a system, we split the entire workflow into several components, including pre-processing, event aggregation, and data serving.
@sastoudt
, @valeri_vasquez
, & @CieraReports
discuss establishing a community of practice rooted in data narratives and the ways they can be created, explored, & shared.
