Keeping genetic engineering localized

Genetic engineering tools that spread genes within a target species have the potential to humanely control harmful pests as well as eradicate parasitic diseases such as malaria.

The tools, known as gene drives, ensure that engineered organisms transmit desired genetic variants to their offspring. These variants could ensure, for example, that the organisms only produce male offspring, or sterile females.

In this way, gene drives could be used to exterminate insects such as mosquitoes that carry pathogens, and that can spread malaria, dengue, and the Zika virus. Gene drives could also be used to control invasive species such as rodents that can threaten the survival of native animals.

However, previously described versions of gene drives based on the CRISPR genome editing system have the potential to spread far wider than their intended local population — to affect an entire species. The affects could also spread across international boundaries, potentially leading to disputes between countries where no prior agreement had been made.

These types of concerns could significantly delay, if not altogether prevent, the safe testing and introduction of the technology.

Now, in a paper published today in the Proceedings of the National Academy of Sciences, researchers at MIT and Harvard University describe a gene drive system with in-built controls.

The CRISPR-based drive consists of a series of genetic elements arranged in a so-called daisy chain, according to Kevin Esvelt, an assistant professor of media arts and sciences and head of the Sculpting Evolution research group at the MIT Media Lab who co-led the research.

One link within the daisy-drive system encodes the CRISPR gene editing system itself, while each of the other links encode guide RNA sequences. These guide sequences tell the CRISPR system to cut and copy the next link in the chain, Esvelt says.

Adding more links allows the daisy drive system to spread for additional generations within the population.

“Imagine you have a chain of daisies, and at each generation you remove the one on the end. When you run out, the daisy chain drive stops," Esvelt explains.

In this way, a small number of genetically-engineered organisms could be released into the wild to spread the daisy-drive within the local population, and then stop when programmed to.

“We’re programming the organism to do CRISPR genome editing on its own, within its reproductive cells, in each generation,” Esvelt says.

Esvelt developed the system in collaboration with George Church, a professor of genetics at Harvard Medical School, visiting professor at the Media Lab, and a senior associate member at the Broad Institute of MIT and Harvard. Co-first authors Charleston Noble and John Min, both graduate students at Harvard Medical School, led the modelling and the molecular biology experiments designed to ensure the system is evolutionarily stable, respectively.

“If the world is to benefit from new gene-drive technologies, we need to be very confident that we can reverse it and contain it, both theoretically and via controlled tests,” Church says.

“Many of the applications of gene drives involve islands and other geographical isolations, at least for initial tests, including invasive species and Lyme disease,” he noted. “It would be great if these highly motivated local governments can do tests that do not automatically affect adjacent islands or mainlands. The daisy-chain drives offer this.”

The research suggests that for every 100 wild counterpart, releasing just one engineered organism with a weak 3-link daisy-drive system, once per generation, should be enough to edit the entire population in about two generations — roughly a year in a fast-reproducing insect. That compares with existing systems that must release at least as many organisms as are already present in a local population, and sometimes 10 or 100 times as many.

The process could take several years in species that reproduce more slowly, such as mice, but would be more humane than the existing use of rodenticides, which can also harm people and predator species, Esvelt says.

In 2014, Esvelt and his colleagues first suggested that CRISPR-Cas9 could be used in gene-drive systems, and he has felt a moral responsibility to develop an alternative to self-propagating systems, he says. “Ideally, localization will let each community make decisions about its own environment, without forcing those decsions on others.

According to Professor Luke Alphey, head of arthropod genetics at The Pirbright Institute in the UK, self-propagating drive systems can spread rapidly through target populations. However, such drive systems are also thought likely to spread to all connected populations of the target species — which is desirable if you want to modify the entire species, undesirable if you do not, he says.

“Daisy-drives potentially provide a means to get much of the benefit of this type of gene drive, while constraining spread and also limiting persistence of the gene drive even in the target population,” Alphey says. “That is likely to be highly desirable when one wants to affect one population but not another of the same species, perhaps affecting an invasive pest population but not populations of the same species in its native range.”

Alphey was not involved in the initial daisy-drive research, but is now collaborating with Esvelt, including work on the use of daisy-drives in mosquitoes. 

Esvelt and the Sculpting Evolution group are also beginning to explore the possible use of this technology to heritably immunize white-footed mice, the primary reservoir of the bacteria responsible for Lyme disease in North America. They are also setting up a research collaboration to explore the use of daisy-drives in Cochliomyia, also known as the New World screwworm, a parasitic fly that produces larvae that eat the living tissue of warm-blooded animals, causing considerable suffering.

In addtition, the researchers are also investigating this technology for use in nematode worms, microscopic creatures that reproduce every three days. This will allow them to carry out laboratory-based evolutionary studies of the daisy-drive engineered organisms, with the goal of ensuring the systems cannot become self-propagating.

de MIT News https://ift.tt/2CT1kim

Researchers tune material’s color and thermal properties separately

The color of a material can often tell you something about how it handles heat. Think of wearing a black shirt on a sweltering summer’s day — the darker the pigment, the warmer you’re likely to feel. Likewise, the more transparent a glass window, the more heat it can let through. A material’s responses to visible and infrared radiation are often naturally linked.

Now MIT engineers have made samples of strong, tissue-like polymer material, the color and heat properties of which they can tailor independently of the other. For instance, they have fabricated samples of very thin black film designed to reflect heat and stay cool. They’ve also made films exhibiting a rainbow of other colors, each made to reflect or absorb infrared radiation regardless of the way they respond to visible light.

The researchers can specifically tune the color and heat properties of this new material to fit the requirements for a host of wide-ranging applications, including colorful, heat-reflecting building facades, windows, and roofs; light-absorbing, heat-dissipating covers for solar panels; and lightweight fabric for clothing, outerwear, tents, and backpacks — all designed to either trap or reflect heat, depending on the environments in which they would be used.

“With this material, everything could look more colorful, because then you wouldn’t be concerned with what color does to the thermal balance of, say, a building, or a window, or your clothing,” says Svetlana Boriskina, a research scientist in MIT’s Department of Mechanical Engineering.

Boriskina is author of a study that appears today in the journal Optical Materials Express, outlining the new material-engineering technique. Her MIT co-authors are Luis Marcelo Lozano, Seongdon Hong, Yi Huang, Hadi Zandavi, Yoichiro Tsurimaki, Jiawei Zhou, Yanfei Xu, and Gang Chen, the Carl Richard Soderberg Professor of Power Engineering, along with Yassine Ait El Aoud and Richard Osgood III, both of the Combat Capabilities Development Command Soldier Center, in Natick, Massachusetts.

Polymer conductors

For this work, Boriskina was inspired by the vibrant colors in stained-glass windows, which for centuries have been made by adding particles of metals and other natural pigments to glass.

“However, despite providing excellent visual transparency, glass has many limitations as a material,” Boriskina notes. “It is bulky, inflexible, fragile, does not spread heat well, and is obviously not suitable for wearable applications.”

She says that while it’s relatively simple to tailor the color of glass, the material’s response to heat is difficult to tune. For instance, glass panels reflect room-temperature heat and trap it inside the room. Furthermore, if colored glass is exposed to incoming sunlight from a particular direction, the heat from the sun can create a hotspot, which is difficult to dissipate in glass. If a material like glass can’t conduct or dissipate heat well, that heat could damage the material.

The same can be said for most plastics, which can be engineered in any color but for the most part are thermal absorbers and insulators, concentrating and trapping heat rather than reflecting it away.

For the past several years, Chen’s lab has been looking into ways to manipulate flexible, lightweight polymer materials to conduct, rather than insulate, heat, mostly for applications in electronics. In previous work, the researchers found that by carefully stretching polymers like polyethylene, they could change the material’s internal structure in a way that also changed its heat-conducting properties.

Boriskina thought this technique might be useful not just for fabricating polymer-based electronics, but also in architecture and apparel. She adapted this polymer-fabrication technique, adding a twist of color.

“It’s very hard to develop a new material with all these different properties in it,” she says. “Usually if you tune one property, the other gets destroyed. Here, we started with one property that was discovered in this group, and then we added a new property creatively. All together it works as a multifunctional material.”

Hotspots stretched away

To fabricate the colorful films, the team started with a mixture of polyethylene powder and a chemical solvent, to which they added certain nanoparticles to give the film a desired color. For instance, to make black film, they added particles of silicon; other red, blue, green, and yellow films were made with the addition of various commercial dyes.

The team then attached each nanoparticle-embedded film onto a roll-to-roll apparatus, which they heated up to soften the film, making it more pliable as the researchers carefully stretched the material.

As they stretched each film, they found, unsurprisingly, that the material became more transparent. They also observed that polyethylene’s microscopic structure changed as it stretched. Where normally the material’s polymer chains resemble a disorganized tangle, similar to cooked spaghetti, when stretched these chains straighten out, forming parallel fibers.

When the researchers placed each sample under a solar simulator — a lamp that mimics the visible and thermal radiation of the sun — they found the more stretched out a film, the more heat it was able to dissipate. The long, parallel polymer chains essentially provided a direct route along which heat could travel. Along these chains, heat, in the form of phonons, could then shoot away from its source, in a “ballistic” fashion, avoiding the formation of hotspots.

The researchers also found that the less they stretched the material, the more insulating it was, trapping heat, and forming hotspots within polymer tangles.

By controlling the degree to which the material is stretched, Boriskina could control polyethylene’s heat-conducting properties, regardless of the material’s color. She also carefully chose the nanoparticles, not just by their visual color, but also by their interactions with invisible radiative heat. She says researchers can potentially use this technique to produce thin, flexible, colorful polymer films, that can conduct or insulate heat, depending on the application.

Going forward, she plans to launch a website that offers algorithms to calculate a material’s color and thermal properties, based on its dimensions and internal structure.

In addition to films, her group is now working on fabricating nanoparticle-embedded polyethylene thread, which can be stitched together to form lightweight apparel, designed to be either insulating, or cooling.

“This is in film factor now, but we’re working it into fibers and fabrics,” Boriskina says. “Polyethylene is produced by the billions of tons and could be recycled, too. I don’t see any significant impediments to large-scale production.”

This research was supported, in part, by the Combat Capabilities Development Command Soldier Center.

de MIT News https://ift.tt/2OF29QK

Teaching machines to reason about what they see

A child who has never seen a pink elephant can still describe one — unlike a computer. “The computer learns from data,” says Jiajun Wu, a PhD student at MIT. “The ability to generalize and recognize something you’ve never seen before — a pink elephant — is very hard for machines.”

Deep learning systems interpret the world by picking out statistical patterns in data. This form of machine learning is now everywhere, automatically tagging friends on Facebook, narrating Alexa’s latest weather forecast, and delivering fun facts via Google search. But statistical learning has its limits. It requires tons of data, has trouble explaining its decisions, and is terrible at applying past knowledge to new situations; It can’t comprehend an elephant that’s pink instead of gray.  

To give computers the ability to reason more like us, artificial intelligence (AI) researchers are returning to abstract, or symbolic, programming. Popular in the 1950s and 1960s, symbolic AI wires in the rules and logic that allow machines to make comparisons and interpret how objects and entities relate. Symbolic AI uses less data, records the chain of steps it takes to reach a decision, and when combined with the brute processing power of statistical neural networks, it can even beat humans in a complicated image comprehension test. 

A new study by a team of researchers at MIT, MIT-IBM Watson AI Lab, and DeepMind shows the promise of merging statistical and symbolic AI. Led by Wu and Joshua Tenenbaum, a professor in MIT’s Department of Brain and Cognitive Sciences and the Computer Science and Artificial Intelligence Laboratory, the team shows that its hybrid model can learn object-related concepts like color and shape, and leverage that knowledge to interpret complex object relationships in a scene. With minimal training data and no explicit programming, their model could transfer concepts to larger scenes and answer increasingly tricky questions as well as or better than its state-of-the-art peers. The team presents its results at the International Conference on Learning Representations in May.

“One way children learn concepts is by connecting words with images,” says the study’s lead author Jiayuan Mao, an undergraduate at Tsinghua University who worked on the project as a visiting fellow at MIT. “A machine that can learn the same way needs much less data, and is better able to transfer its knowledge to new scenarios.”

The study is a strong argument for moving back toward abstract-program approaches, says Jacob Andreas, a recent graduate of the University of California at Berkeley, who starts at MIT as an assistant professor this fall and was not involved in the work. “The trick, it turns out, is to add more symbolic structure, and to feed the neural networks a representation of the world that’s divided into objects and properties rather than feeding it raw images,” he says. “This work gives us insight into what machines need to understand before language learning is possible.”

The team trained their model on images paired with related questions and answers, part of the CLEVR image comprehension test developed at Stanford University. As the model learns, the questions grow progressively harder, from, “What’s the color of the object?” to “How many objects are both right of the green cylinder and have the same material as the small blue ball?” Once object-level concepts are mastered, the model advances to learning how to relate objects and their properties to each other.

Like other hybrid AI models, MIT’s works by splitting up the task. A perception module of neural networks crunches the pixels in each image and maps the objects. A language module, also made of neural nets, extracts a meaning from the words in each sentence and creates symbolic programs, or instructions, that tell the machine how to answer the question. A third reasoning module runs the symbolic programs on the scene and gives an answer, updating the model when it makes mistakes.

Key to the team’s approach is a perception module that translates the image into an object-based representation, making the programs easier to execute. Also unique is what they call curriculum learning, or selectively training the model on concepts and scenes that grow progressively more difficult. It turns out that feeding the machine data in a logical way, rather than haphazardly, helps the model learn faster while improving accuracy.

Once the model has a solid foundation, it can interpret new scenes and concepts, and increasingly difficult questions, almost perfectly. Asked to answer an unfamiliar question like, “What’s the shape of the big yellow thing?” it outperformed its peers at Stanford and nearby MIT Lincoln Laboratory with a fraction of the data. 

While other models trained on the full CLEVR dataset of 70,000 images and 700,000 questions, the MIT-IBM model used 5,000 images and 100,000 questions. As the model built on previously learned concepts, it absorbed the programs underlying each question, speeding up the training process. 

Though statistical, deep learning models are now embedded in daily life, much of their decision process remains hidden from view. This lack of transparency makes it difficult to anticipate where the system is susceptible to manipulation, error, or bias. Adding a symbolic layer can open the black box, explaining the growing interest in hybrid AI systems.

“Splitting the task up and letting programs do some of the work is the key to building interpretability into deep learning models,” says Lincoln Laboratory researcher David Mascharka, whose hybrid model, Transparency by Design Network, is benchmarked in the MIT-IBM study.      

The MIT-IBM team is now working to improve the model’s performance on real-world photos and extending it to video understanding and robotic manipulation. Other authors of the study are Chuang Gan and Pushmeet Kohli, researchers atthe MIT-IBM Watson AI Lab and DeepMind, respectively.

de MIT News https://ift.tt/2UplWJ3

School of Science announces 2019 Infinite Mile Awards

The MIT School of Science has announced the winners of the 2019 Infinite Mile Award, which is presented annually to staff members within the school who demonstrate exemplary dedication to making MIT a better place.

Nominated by their colleagues, these winners are notable for their unrelenting and extraordinary hard work in their positions, which can include mentoring fellow community members, innovating new solutions to problems big and small, building their communities, or going far above and beyond their job descriptions to support the goals of their home departments, labs, and research centers.

The 2019 Infinite Mile Award winners are:

Christine Brooks, an administrative assistant in the Department of Chemistry, nominated by Mircea Dincă and several members of the Dincă, Schrock, and Cummins groups;

Annie Cardinaux, a research specialist in the Department of Brain and Cognitive Sciences, nominated by Pawan Sinha;

Kimberli DeMayo, a human resources consultant in the Department of Mathematics, nominated by Nan Lin, Dennis Porche, and Paul Seidel, with support from several other faculty members;

Arek Hamalian, a technical associate at the Picower Institute for Learning and Memory, nominated by Susumu Tonegawa;

Jonathan Harmon, an administrative assistant in the Department of Mathematics, nominated by Pavel Etingof and Kimberli DeMayo, with support from several other faculty members;

Tanya Khovanova, a lecturer in the Department of Mathematics, nominated by Pavel Etingof, David Jerison, and Slava Gerovitch;

Kelley Mahoney, an SRS financial staff member in the Kavli Institute for Astrophysics and Space Research, nominated by Sarah Brady, Michael McDonald, Anna Frebel, Jacqueline Hewitt, Jack Defandorf, and Stacey Sullaway;

Walter Massefski, the director of instrumentation facility in the Department of Chemistry, nominated by Timothy Jamison and Richard Wilk;

Raleigh McElvery, a communications coordinator in the Department of Biology, nominated by Vivian Siegel with support from Amy Keating, Julia Keller, and Erika Reinfeld; and

Kate White, an administrative officer in the Department of Brain and Cognitive Sciences, nominated by Jim DiCarlo, Michale Fee, Sara Cody-Larnard, Rachel Donahue, Federico Chiavazza, Matthew Regan, Gayle Lutchen, and William Lawson.

The recipients will receive a monetary award in addition to being honored at a celebratory reception, along with their peers, family and friends, and the recipients of the 2019 Infinite Kilometer Award this month.

de MIT News https://ift.tt/2CRkcOT

Finding common ground

One evening last November, something unexpected came out of a microfluidics and nanofluidics lab at MIT.

As postdocs David Cheng and Rozzeta Dolah ran an experiment, their conversation drifted from the work at hand to their future plans. “It’s a somewhat inevitable question that postdocs hate ... yet just cannot escape from discussing,” says Cheng. Both wished they had more role models, particularly past postdocs, that they could reach out to for advice.

Then an idea emerged. What about holding an event to enable current and former postdocs to network and share experiences?

Cheng and Dolah — officers of the MIT Postdoctoral Association (PDA) — ended up doing just that, hosting the first-ever MIT PDA Homecoming on March 15. With support from the Office of the Vice President for Research (VPR) and the MIT Alumni Association, the PDA organized a panel discussion and reception that drew more than 120 attendees, including 21 past postdocs and a number of current students.

Five former postdocs with a range of academic and industry experience participated in the panel: Brent Grocholski, a physical science associate editor for Science; Sisir Karumanchi, a robotics technologist in mobility and robotics systems at NASA’s Jet Propulsion Laboratory; Lamia Youseff, a research scientist in scalable machine learning at Stanford University and a Sloan Fellow at Stanford’s business school; Rajesh Jugulum, an infomatics director at CIGNA and adjunct professor at Northeastern University; and Virginia Burger, a senior scientist and director of scientific collaborations at XtalPi, Inc.

The event kicked off with virtual remarks from Vice President for Research Maria Zuber, whose office provides oversight of postdoctoral affairs, and professor of physics Edmund Bertschinger, who serves as faculty advisor to the PDA. Zuber noted recent enhancements, done in collaboration with the PDA, to support the over 1,500 postdocs at MIT. They include an increased focus on mentoring, career guidance, and professional development; partnering with the Alumni Association to offer postdocs access to infinite connection accounts and the job board, and adding postdoc representation to Institute committees.

“While we have more to do to achieve in the coming years, let us take pride and celebrate the success of our past and current postdocs,” Zuber said. “May the bonds of MIT and the spirit of 'mens et manus' ['mind and hand'] guide us as we strive to create new knowledge and transform society for the better, wherever we are.”

Both Zuber and Bertschinger offered special recognition to Dana Bresee Keeth, director of postdoctoral services in VPR. Keeth plans to retire in April after eight years of service in that role.

Alex Albanese, a postdoc in the Institute for Medical Engineering and Science, moderated a panel discussion. He said his “full-time hobby” is producing a podcast called GLiMPSE, offering a window into the work of postdocs and scientists across MIT. “The diversity of cultures, perspectives, and scientific backgrounds never ceases to amaze me,” he said in his opening remarks. Albanese peppered the panelists with questions about their postdoc experiences; making the transition to a career outside MIT; current responsibilities and challenges; and general advice for success at MIT and beyond.

Throughout the discussion, panelists described how their current work differs from their postdoc experience. “You get good at a specific problem as a postdoc,” Grocholski said, adding that now he doesn’t have the “bandwidth” to understand all the technical aspects of the papers he reviews. “I need to look at the 30,000-foot view. That’s something that requires you to stretch yourself and try to see things a bit more broadly.”

“In academia, you look for perfection in a particular topic or concept, and time is not a factor,” Jugulum said. In industry, perfection is not that important, “but time is a factor … you have to understand the importance of time.”

Being nimble and adapting to change is key, Youseff said. “The ability to be flexible, and move across technologies, understand the different foundations of the technology” but not be tied to any particular one, has served her well as her career has progressed.

The importance of communication was also a common theme. “All the skill sets [you have] in writing proposals or papers will come in very handy” no matter what you do, Karumanchi told the audience. Conveying technical concepts to a broader audience, however, has often proved challenging.

Understanding your audience is important, Jugulum said. Talking to a business leader is a different skill for those with a technical background. A colleague recommended using a storytelling approach. “Tell the story first. What is the result? How did you achieve these results? Then go to the technique,” he said.

When asked what skill they wished they had developed as postdocs, several panelists said they should have networked and explored. “I urge all of you to take advantage of the opportunities that are here to the fullest extent,” Grocholski said.

Burger recalled that when she was just a few months shy of the end of her postdoc appointment, her plan to stay in academia changed radically. Having submitted her faculty applications, she had more time to participate in activities beyond her field. She discovered a passion for entrepreneurship that changed the trajectory of her career. In retrospect, she said, it would have been good to make an effort to explore “something outside of my interest” every semester.

The panel also resonated with Jose Ruiperez, a postdoc in open learning, and Christina Tringides, a graduate student in health sciences and technology. “For me, the postdoc is an important point when you have decide whether you’re going to remain in academia or move into industry,” Ruiperez said. After going back and forth, he’s decided to stay in academia, “but it’s nice to see why other people decided to move to industry or to environments other than the typical academic environment.”

“The event was really nicely done,” Tringides said. “Everyone had such different backgrounds, but they still said a lot of the same themes.” She appreciated getting a sense of career options for postdocs at this stage of her training.

In closing the program, Albanese gave the audience an assignment.

“I know a lot of panelists regretted not networking. We heard it’s a really important skill," he said. "So talk to one new person tonight.”

de MIT News https://ift.tt/2JXNmSp

MIT launches 2019 AAU survey on sexual misconduct, responds to National Academies report

Continuing its commitment to preventing and responding to sexual misconduct, MIT is taking important steps during Sexual Assault Awareness Month (SAAM): launching a student survey on sexual misconduct and establishing new leadership groups to advance efforts to combat sexual misconduct at MIT and to respond to the recommendations from a recent National Academies of Sciences, Engineering, and Medicine (NASEM) report.

Chancellor Cynthia Barnhart SM ’85 PhD ’88 and Provost Martin Schmidt SM ’83, PhD ’88 announced these efforts in a letter to the community today.

“To live up to MIT’s creative promise, we must work constantly to treat one another with decency, integrity, respect, and kindness. By definition then, we must never stop building and strengthening a culture that treats sexual harassment, coercion, and assault as absurdly out of bounds — unthinkable for anyone, of any age, in any context,” said MIT President L. Rafael Reif. “I am tremendously grateful that in this work, we can count on the leadership and persistence of our senior leaders and hundreds of staff, students, and faculty across MIT. In the end, however, the most important work is up to all of us.”

2019 AAU Campus Climate Survey on Sexual Misconduct

MIT is participating in the Association of American Universities (AAU) second national campus climate survey on sexual misconduct. All students will receive an invitation to participate from Barnhart on April 2, and the survey will be open for completion until May 1.

The 2019 AAU Campus Climate Survey on Sexual Misconduct will allow the Institute to measure the progress made to combat sexual misconduct in the five years since MIT conducted its landmark 2014 Campus Attitudes on Sexual Assault (CASA) survey; identify and respond to new issues the AAU survey may uncover; and put MIT’s results into the context of national AAU aggregate data. Thirty-two other public and private research universities are participating in the 2019 AAU survey.

AAU retained Westat, a leading social science research firm, to lead the development of the survey questions. The design team for the questions included representatives from MIT and other participating schools as well as individuals with relevant expertise across the nation. Westat will administer the survey, and respondents will remain anonymous; no identifying information about an individual or a group will be linked to responses, and individual responses will remain confidential. Westat will provide MIT with a report of MIT’s results, which will be released to the community next fall.

In order to help MIT and other participating institutions better understand how sexual misconduct affects their student communities, and so schools can measure the effectiveness of their prevention and response efforts, the 2019 AAU survey includes sections that ask about students’ knowledge and beliefs about social situations; their perceptions related to sexual misconduct on campus; and their knowledge of resources available at MIT. The survey also asks respondents about their personal experience with sexual misconduct, such as gender- and identity-based harassment, intimate partner violence, sexual assault, and other forms of sexual violence. More information about the survey, including Frequently Asked Questions, can be found here.

Responding to NASEM report at MIT and nationally

Last summer, NASEM released “Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine.” Institute Professor Sheila Widnall co-chaired the committee responsible for producing the consensus study report, which found that between 20 and 50 percent of female students and more than 50 percent of female faculty and staff experienced sexually harassing behavior while in academia. Widnall joined her co-chair Wellesley College President Paula A. Johnson; Reif; and Brandeis University Professor and MIT Research Affiliate Anita Hill for a community discussion about the report in September.

In their letter, Barnhart and Schmidt also announced a presidential advisory board and working groups that will be responsible for building on MIT’s ongoing prevention and response work as well as advancing the NASEM report recommendations. The board is comprised of senior officers, and the four working groups of faculty, students, post-docs, and staff will focus on leadership and engagement; training and prevention; policies and reporting; and academic and organizational relationships. More information about the membership, charges, and deadlines for the board and working groups is available here.

To help move the report’s recommendations forward nationally, MIT has agreed to be a founding member and to serve on the steering committee of the new Action Collaborative on Preventing Sexual Harassment in Higher Education. The collaborative’s academic leaders and stakeholders have four goals:

• raise awareness about sexual harassment and how it occurs, the consequences of sexual harassment, and the organizational characteristics and approaches that can prevent it;
• share and elevate evidence-based, institutional solutions and strategies;
• contribute to setting the research agenda, and gather and apply research results across institutions; and
• develop a standard for measuring progress in higher education.

According to NASEM, the collaborative will help academic institutions “achieve together what they cannot achieve individually: targeted, collective action at the institutional level for addressing and preventing all forms of sexual harassment and promoting a campus climate of civility and respect.”

de MIT News https://ift.tt/2FHC8fq

3 Questions: Lisa Barsotti on the new and improved LIGO

The search for infinitely faint ripples in space-time is back in full swing. Today, LIGO, the Laser Interferometer Gravitational-wave Observatory, operated jointly by Caltech and MIT, resumes its hunt for gravitational waves and the immense cosmic phenomena from which they emanate.

Over the past several months, LIGO’s twin detectors, in Washington and Lousiana, have been offline, undergoing upgrades to their lasers, mirrors, and other components, which will enable the detectors to listen for gravitational waves over a far greater range, out to about 550 million light-years away — around 190 million light-years farther out than before.

As the LIGO detectors turn back on, they will be joined by Virgo, the European-based counterpart based in Italy, which also turns on today after undergoing upgrades that doubled its sensitivity. With both LIGO and Virgo back online, scientists anticipate that detections of gravitational waves from the farthest reaches of the universe may be a regular occurrence.

MIT News spoke with LIGO member Lisa Barsotti, principal research scientist at MIT’s Kavli Institute for Astrophysics and Space Research, about the potential discoveries that lie ahead.

Q: Give us a sense of the new capabilities that the LIGO detectors now have. What sort of upgrades were made?

A: Both LIGO detectors are coming back online more sensitive than ever before, thanks to a wide range of improvements. In particular, we more than doubled the laser power in the interferometers to reduce one of the LIGO fundamental noise sources — quantum "shot noise,” caused by the uncertainty of the arrival time of photons onto the main photodetector. We also deployed a new technology, "squeezed" light, that uses quantum optics to further reduce shot noise.

Combined with other upgrades to mitigate technical noises (for example noises introduced by the control scheme or from stray light) we improved the sensitivity to binary neutron stars by 40 percent in each detector, with respect to the past observing run.

Q: What do these new capabilities mean for you, as a researcher who will be looking through the data from these upgraded detectors?

A: I am personally very excited to see the LIGO detectors operating with squeezed light! This new technology has been developed here at MIT after many years of research to make it compatible with the very stringent LIGO requirements, and our graduate students have been leading the commissioning of this new system at the observatories. It is particularly rewarding to see that we succeeded in making LIGO better.

Also, operation at high laser power has been enabled by another upgrade developed and built here at MIT — an "acoustic mode damper" glued to the main LIGO optics that mitigates instabilities originating with high laser power. We are looking forward to seeing many years of work in our labs pay off in this observing run!

Q: What new phenomena are you hoping to detect, and how soon could you detect them, with these new capabilities?

A: We hope to detect more binary neutron star systems (so far only one has been detected), and thanks to the improved LIGO sensitivity, we should be able to observe them with high signal-to-noise ratio. And more black holes, obviously! The more sources we detect, the more we can learn about the way these systems form and evolve.

If we are very lucky, we might observe something new, like a neutron star-black hole system, or maybe even something totally unexpected. Not only are the LIGO detectors better than before — the Virgo detector in Italy more than doubled its sensitivity with respect to the last observing run, and this will improve our ability to localize sources in the sky, facilitating the follow-up of telescopes at multiple wavelengths. So, if the last observing run, “O2,” will be remembered as the one that started multimessenger astronomy, I hope the upcoming one, “O3,” will be the one in which multimessenger astronomy becomes the new normal!

de MIT News https://ift.tt/2U9oqfh