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Researchers have detected microplastics in human testicles. Volodymyr Zakharov/Getty Images hide caption

Shots - Health News

Plastic junk researchers find tiny particles in men's testicles.

May 22, 2024 • The new study has scientists concerned that microplastics may be contributing to reproductive health issues.

Harlan Gough holds a recently collected tiger beetle on a tether. Lawrence Reeves hide caption

To escape hungry bats, these flying beetles create an ultrasound 'illusion'

May 22, 2024 • A study of tiger beetles has found a possible explanation for why they produce ultrasound noises right before an echolocating bat swoops in for the kill.

A sea otter in Monterey Bay with a rock anvil on its belly and a scallop in its forepaws. Jessica Fujii hide caption

When sea otters lose their favorite foods, they can use tools to go after new ones

May 20, 2024 • Some otters rely on tools to bust open hard-shelled prey items like snails, and a new study suggests this tool use is helping them to survive as their favorite, easier-to-eat foods disappear.

Lauren Hill, a graduate student at Cal State LA, holds a bird at the bird banding site at Bear Divide in the San Gabriel Mountains. Grace Widyatmadja/NPR hide caption

On this unassuming trail near LA, bird watchers see something spectacular

May 13, 2024 • At Bear Divide, just outside Los Angeles, you can see a rare spectacle of nature. This is one of the only places in the western United States where you can see bird migration during daylight hours.

The inside of a cell is a complicated orchestration of interactions between molecules. Keith Chambers/Science Photo Library hide caption

AI gets scientists one step closer to mapping the organized chaos in our cells

May 13, 2024 • As artificial intelligence seeps into some realms of society, it rushes into others. One area it's making a big difference is protein science — as in the "building blocks of life," proteins! Producer Berly McCoy talks to host Emily Kwong about the newest advance in protein science: AlphaFold3, an AI program from Google DeepMind. Plus, they talk about the wider field of AI protein science and why researchers hope it will solve a range of problems, from disease to the climate.

NASA's Solar Dynamics Observatory captured this image of a strong solar flare on May 8, 2024. The Wednesday solar flares kicked off the geomagnetic storm happening this weekend. NASA/SDO hide caption

NOAA Issues First Severe Geomagnetic Storm Watch Since 2005

May 10, 2024 • Scientists at the National Oceanic and Atmospheric Administration observed a cluster of sunspots on the surface of the sun this week. With them came solar flares that kicked off a severe geomagnetic storm. That storm is expected to last throughout the weekend as at least five coronal mass ejections — chunks of the sun — are flung out into space, towards Earth! NOAA uses a five point scale to rate these storms, and this weekend's storm is a G4. It's expected to produce auroras as far south as Alabama. To contextualize this storm, we are looking back at the largest solar storm on record: the Carrington Event.

Esther Nesbitt lost two of her children to drug overdoses, and her grandchildren are among more than 320,000 who lost parents in the overdose epidemic. Andrew Lichtenstein/Corbis via Getty Images hide caption

In a decade of drug overdoses, more than 320,000 American children lost a parent

May 8, 2024 • New research documents how many children lost a parent to an opioid or other overdose in the period from 2011 to 2021. Bereaved children face elevated risks to their physical and emotional health.

This illustration depicts a washed-up Ichthyotitan severnensis carcass on the beach. Sergey Krasovskiy hide caption

Largest-ever marine reptile found with help from an 11-year-old girl

May 6, 2024 • A father and daughter discovered fossil remnants of a giant ichthyosaur that scientists say may have been the largest-known marine reptile to ever swim the seas.

A survey shows that doctors have trouble taking full vacations from their high-stress jobs. Even when they do, they often still do work on their time off. Wolfgang Kaehler/LightRocket via Getty Images hide caption

Perspective

When pto stands for 'pretend time off': doctors struggle to take real breaks.

May 4, 2024 • What's a typical vacation activity for doctors? Work. A new study finds that most physicians do work on a typical day off. In this essay, a family doctor considers why that is and why it matters.

Weliton Menário Costa (center) holds a laptop while surrounded by dancers for his music video, "Kangaroo Time." From left: Faux Née Phish (Caitlin Winter), Holly Hazlewood, and Marina de Andrade. Nic Vevers/ANU hide caption

'Dance Your Ph.D.' winner on science, art, and embracing his identity

May 4, 2024 • Weliton Menário Costa's award-winning music video showcases his research on kangaroo personality and behavior — and offers a celebration of human diversity, too.

Researchers in a rainforest in Indonesia spotted an injury on the face of a male orangutan they named Rakus. They were stunned to watch him treat his wound with a medicinal plant. Armas/Suaq Project hide caption

Orangutan in the wild applied medicinal plant to heal its own injury, biologists say

May 3, 2024 • It is "the first known case of active wound treatment in a wild animal with a medical plant," biologist Isabelle Laumer told NPR. She says the orangutan, called Rakus, is now thriving.

The federal government says it has taken steps toward developing a vaccine to protect against bird flu should it become a threat to humans. skodonnell/Getty Images hide caption

Launching an effective bird flu vaccine quickly could be tough, scientists warn

May 3, 2024 • Federal health officials say the U.S. has the building blocks to make a vaccine to protect humans from bird flu, if needed. But experts warn we're nowhere near prepared for another pandemic.

A Nazca booby in the Galápagos Islands incubates eggs with its webbed feet. Wolfgang Kaehler/LightRocket via Getty Images hide caption

The Science of Siblings

For birds, siblinghood can be a matter of life or death.

May 1, 2024 • Some birds kill their siblings soon after hatching. Other birds spend their whole lives with their siblings and will even risk their lives to help each other.

Planet Money

How do you counter misinformation critical thinking is step one.

April 30, 2024 • An economic perspective on misinformation

This image shows a brain "assembloid" consisting of two connected brain "organoids." Scientists studying these structures have restored impaired brain cells in Timothy syndrome patients. Pasca lab, Stanford University hide caption

Scientists restore brain cells impaired by a rare genetic disorder

April 30, 2024 • A therapy that restores brain cells impaired by a rare genetic disorder may offer a strategy for treating conditions like autism, epilepsy, and schizophrenia.

Katie Krimitsos is among the majority of American women who have trouble getting healthy sleep, according to a new Gallup survey. Krimitsos launched a podcast called Sleep Meditation for Women to offer some help. Natalie Champa Jennings/Natalie Jennings, courtesy of Katie Krimitsos hide caption

Helping women get better sleep by calming the relentless 'to-do lists' in their heads

April 26, 2024 • A recent survey found that Americans' sleep patterns have been getting worse. Adult women under 50 are among the most sleep-deprived demographics.

Bird flu is spreading through U.S. dairy cattle. Scientists say the risk to people is minimal, but open questions remain, including how widespread the outbreak is and how the virus is spreading. DOUGLAS MAGNO/AFP via Getty Images hide caption

As bird flu spreads in cows, here are 4 big questions scientists are trying to answer

April 26, 2024 • Health officials say there's very little risk to humans from the bird flu outbreak among dairy cattle, but there's still much they don't know. Here are four questions scientists are trying to answer.

A coyote at the Fort Worth Zoo is photographed in the hours leading up to the April 8 total solar eclipse. The Hartstone-Rose Research Lab, NC State hide caption

Animals get stressed during eclipses. But not for the reason you think

April 25, 2024 • After studying various species earlier this month, some scientists now say they understand the origin of animal behavior during solar eclipses.

Dr. Jeffrey Stern, assistant professor in the Department of Surgery at NYU Grossman School of Medicine, and Dr. Robert Montgomery, director of the NYU Langone Transplant Institute, prepare the gene-edited pig kidney with thymus for transplantation. Joe Carrotta for NYU Langone Health hide caption

A woman with failing kidneys receives genetically modified pig organs

April 24, 2024 • Surgeons transplanted a kidney and thymus gland from a gene-edited pig into a 54-year-old woman in an attempt to extend her life. It's the latest experimental use of animal organs in humans.

Drug companies often do one-on-one outreach to doctors. A new study finds these meetings with drug reps lead to more prescriptions for cancer patients, but not longer survival. Chris Hondros/Getty Images hide caption

Oncologists' meetings with drug reps don't help cancer patients live longer

April 22, 2024 • Drug company reps commonly visit doctors to talk about new medications. A team of economists wanted to know if that helps patients live longer. They found that for cancer patients, the answer is no.

When the media covers scientific research, not all scientists are equally likely to be mentioned. A new study finds scientists with Asian or African names were 15% less likely to be named in a story. shironosov/Getty Images hide caption

Which scientists get mentioned in the news? Mostly ones with Anglo names, says study

April 19, 2024 • A new study finds that in news stories about scientific research, U.S. media were less likely to mention a scientist if they had an East Asian or African name, as compared to one with an Anglo name.

An artistic rendering of a washed-up Ichthyotitan severnensis carcass on the beach. Sergey Krasovskiy hide caption

An 11-year-old unearthed fossils of the largest known marine reptile

April 19, 2024 • When the dinosaurs walked the Earth, massive marine reptiles swam. Among them, a species of Ichthyosaur that measured over 80 feet long. Today, we look into how a chance discovery by a father-daughter duo of fossil hunters furthered paleontologist's understanding of the "giant fish lizard of the Severn." Currently, it is the largest marine reptile known to scientists.

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Study explains why the brain can robustly recognize images, even without color

Even though the human visual system has sophisticated machinery for processing color, the brain has no problem recognizing objects in black-and-white images. A new study from MIT offers a possible explanation for how the brain comes to be so adept at identifying both color and color-degraded images.

Using experimental data and computational modeling, the researchers found evidence suggesting the roots of this ability may lie in development. Early in life, when newborns receive strongly limited color information, the brain is forced to learn to distinguish objects based on their luminance, or intensity of light they emit, rather than their color. Later in life, when the retina and cortex are better equipped to process colors, the brain incorporates color information as well but also maintains its previously acquired ability to recognize images without critical reliance on color cues.

The findings are consistent with previous work showing that initially degraded visual and auditory input can actually be beneficial to the early development of perceptual systems.

"This general idea, that there is something important about the initial limitations that we have in our perceptual system, transcends color vision and visual acuity. Some of the work that our lab has done in the context of audition also suggests that there's something important about placing limits on the richness of information that the neonatal system is initially exposed to," says Pawan Sinha, a professor of brain and cognitive sciences at MIT and the senior author of the study.

The findings also help to explain why children who are born blind but have their vision restored later in life, through the removal of congenital cataracts, have much more difficulty identifying objects presented in black and white. Those children, who receive rich color input as soon as their sight is restored, may develop an overreliance on color that makes them much less resilient to changes or removal of color information.

MIT postdocs Marin Vogelsang and Lukas Vogelsang, and Project Prakash research scientist Priti Gupta, are the lead authors of the study, which appears today in Science . Sidney Diamond, a retired neurologist who is now an MIT research affiliate, and additional members of the Project Prakash team are also authors of the paper.

Seeing in black and white

The researchers' exploration of how early experience with color affects later object recognition grew out of a simple observation from a study of children who had their sight restored after being born with congenital cataracts. In 2005, Sinha launched Project Prakash (the Sanskrit word for "light"), an effort in India to identify and treat children with reversible forms of vision loss.

Many of those children suffer from blindness due to dense bilateral cataracts. This condition often goes untreated in India, which has the world's largest population of blind children, estimated between 200,000 and 700,000.

Children who receive treatment through Project Prakash may also participate in studies of their visual development, many of which have helped scientists learn more about how the brain's organization changes following restoration of sight, how the brain estimates brightness, and other phenomena related to vision.

In this study, Sinha and his colleagues gave children a simple test of object recognition, presenting both color and black-and-white images. For children born with normal sight, converting color images to grayscale had no effect at all on their ability to recognize the depicted object. However, when children who underwent cataract removal were presented with black-and-white images, their performance dropped significantly.

This led the researchers to hypothesize that the nature of visual inputs children are exposed to early in life may play a crucial role in shaping resilience to color changes and the ability to identify objects presented in black-and-white images. In normally sighted newborns, retinal cone cells are not well-developed at birth, resulting in babies having poor visual acuity and poor color vision. Over the first years of life, their vision improves markedly as the cone system develops.

Because the immature visual system receives significantly reduced color information, the researchers hypothesized that during this time, the baby brain is forced to gain proficiency at recognizing images with reduced color cues. Additionally, they proposed, children who are born with cataracts and have them removed later may learn to rely too much on color cues when identifying objects, because, as they experimentally demonstrated in the paper, with mature retinas, they commence their post-operative journeys with good color vision.

To rigorously test that hypothesis, the researchers used a standard convolutional neural network, AlexNet, as a computational model of vision. They trained the network to recognize objects, giving it different types of input during training. As part of one training regimen, they initially showed the model grayscale images only, then introduced color images later on. This roughly mimics the developmental progression of chromatic enrichment as babies' eyesight matures over the first years of life.

Another training regimen comprised only color images. This approximates the experience of the Project Prakash children, because they can process full color information as soon as their cataracts are removed.

The researchers found that the developmentally inspired model could accurately recognize objects in either type of image and was also resilient to other color manipulations. However, the Prakash-proxy model trained only on color images did not show good generalization to grayscale or hue-manipulated images.

"What happens is that this Prakash-like model is very good with colored images, but it's very poor with anything else. When not starting out with initially color-degraded training, these models just don't generalize, perhaps because of their over-reliance on specific color cues," Lukas Vogelsang says.

The robust generalization of the developmentally inspired model is not merely a consequence of it having been trained on both color and grayscale images; the temporal ordering of these images makes a big difference. Another object-recognition model that was trained on color images first, followed by grayscale images, did not do as well at identifying black-and-white objects.

"It's not just the steps of the developmental choreography that are important, but also the order in which they are played out," Sinha says.

The advantages of limited sensory input

By analyzing the internal organization of the models, the researchers found that those that begin with grayscale inputs learn to rely on luminance to identify objects. Once they begin receiving color input, they don't change their approach very much, since they've already learned a strategy that works well. Models that began with color images did shift their approach once grayscale images were introduced, but could not shift enough to make them as accurate as the models that were given grayscale images first.

A similar phenomenon may occur in the human brain, which has more plasticity early in life, and can easily learn to identify objects based on their luminance alone. Early in life, the paucity of color information may in fact be beneficial to the developing brain, as it learns to identify objects based on sparse information.

"As a newborn, the normally sighted child is deprived, in a certain sense, of color vision. And that turns out to be an advantage," Diamond says.

Researchers in Sinha's lab have observed that limitations in early sensory input can also benefit other aspects of vision, as well as the auditory system. In 2022, they used computational models to show that early exposure to only low-frequency sounds, similar to those that babies hear in the womb, improves performance on auditory tasks that require analyzing sounds over a longer period of time, such as recognizing emotions. They now plan to explore whether this phenomenon extends to other aspects of development, such as language acquisition.

The research was funded by the National Eye Institute of NIH and the Intelligence Advanced Research Projects Activity.

• Child Development
• Intelligence
• Learning Disorders
• Child Psychology
• Language Acquisition
• Brain Injury
• Color blindness
• Human skin color
• Occipital lobe
• Early childhood education
• Peripheral vision
• Social cognition

Story Source:

Materials provided by Massachusetts Institute of Technology . Original written by Anne Trafton. Note: Content may be edited for style and length.

Journal Reference :

• Marin Vogelsang, Lukas Vogelsang, Priti Gupta, Tapan K. Gandhi, Pragya Shah, Piyush Swami, Sharon Gilad-Gutnick, Shlomit Ben-Ami, Sidney Diamond, Suma Ganesh, Pawan Sinha. Impact of early visual experience on later usage of color cues . Science , 2024; 384 (6698): 907 DOI: 10.1126/science.adk9587

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Study explains why the brain can robustly recognize images, even without color

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Even though the human visual system has sophisticated machinery for processing color, the brain has no problem recognizing objects in black-and-white images. A new study from MIT offers a possible explanation for how the brain comes to be so adept at identifying both color and color-degraded images.

Using experimental data and computational modeling, the researchers found evidence suggesting the roots of this ability may lie in development. Early in life, when newborns receive strongly limited color information, the brain is forced to learn to distinguish objects based on their luminance, or intensity of light they emit, rather than their color. Later in life, when the retina and cortex are better equipped to process colors, the brain incorporates color information as well but also maintains its previously acquired ability to recognize images without critical reliance on color cues.

The findings are consistent with previous work showing that initially degraded visual and auditory input can actually be beneficial to the early development of perceptual systems.

“This general idea, that there is something important about the initial limitations that we have in our perceptual system, transcends color vision and visual acuity. Some of the work that our lab has done in the context of audition also suggests that there’s something important about placing limits on the richness of information that the neonatal system is initially exposed to,” says Pawan Sinha, a professor of brain and cognitive sciences at MIT and the senior author of the study.

The findings also help to explain why children who are born blind but have their vision restored later in life, through the removal of congenital cataracts, have much more difficulty identifying objects presented in black and white. Those children, who receive rich color input as soon as their sight is restored, may develop an overreliance on color that makes them much less resilient to changes or removal of color information.

MIT postdocs Marin Vogelsang and Lukas Vogelsang, and Project Prakash research scientist Priti Gupta, are the lead authors of the study, which appears today in Science . Sidney Diamond, a retired neurologist who is now an MIT research affiliate, and additional members of the Project Prakash team are also authors of the paper.

Seeing in black and white

The researchers’ exploration of how early experience with color affects later object recognition grew out of a simple observation from a study of children who had their sight restored after being born with congenital cataracts. In 2005, Sinha launched Project Prakash (the Sanskrit word for “light”), an effort in India to identify and treat children with reversible forms of vision loss.

Many of those children suffer from blindness due to dense bilateral cataracts. This condition often goes untreated in India, which has the world’s largest population of blind children, estimated between 200,000 and 700,000.

Children who receive treatment through Project Prakash may also participate in studies of their visual development, many of which have helped scientists learn more about how the brain's organization changes following restoration of sight, how the brain estimates brightness, and other phenomena related to vision.

In this study, Sinha and his colleagues gave children a simple test of object recognition, presenting both color and black-and-white images. For children born with normal sight, converting color images to grayscale had no effect at all on their ability to recognize the depicted object. However, when children who underwent cataract removal were presented with black-and-white images, their performance dropped significantly.

This led the researchers to hypothesize that the nature of visual inputs children are exposed to early in life may play a crucial role in shaping resilience to color changes and the ability to identify objects presented in black-and-white images. In normally sighted newborns, retinal cone cells are not well-developed at birth, resulting in babies having poor visual acuity and poor color vision. Over the first years of life, their vision improves markedly as the cone system develops.

Because the immature visual system receives significantly reduced color information, the researchers hypothesized that during this time, the baby brain is forced to gain proficiency at recognizing images with reduced color cues. Additionally, they proposed, children who are born with cataracts and have them removed later may learn to rely too much on color cues when identifying objects, because, as they experimentally demonstrated in the paper, with mature retinas, they commence their post-operative journeys with good color vision.

To rigorously test that hypothesis, the researchers used a standard convolutional neural network, AlexNet, as a computational model of vision. They trained the network to recognize objects, giving it different types of input during training. As part of one training regimen, they initially showed the model grayscale images only, then introduced color images later on. This roughly mimics the developmental progression of chromatic enrichment as babies’ eyesight matures over the first years of life.

Another training regimen comprised only color images. This approximates the experience of the Project Prakash children, because they can process full color information as soon as their cataracts are removed.

The researchers found that the developmentally inspired model could accurately recognize objects in either type of image and was also resilient to other color manipulations. However, the Prakash-proxy model trained only on color images did not show good generalization to grayscale or hue-manipulated images.

“What happens is that this Prakash-like model is very good with colored images, but it’s very poor with anything else. When not starting out with initially color-degraded training, these models just don’t generalize, perhaps because of their over-reliance on specific color cues,” Lukas Vogelsang says.

The robust generalization of the developmentally inspired model is not merely a consequence of it having been trained on both color and grayscale images; the temporal ordering of these images makes a big difference. Another object-recognition model that was trained on color images first, followed by grayscale images, did not do as well at identifying black-and-white objects.

“It’s not just the steps of the developmental choreography that are important, but also the order in which they are played out,” Sinha says.

The advantages of limited sensory input

By analyzing the internal organization of the models, the researchers found that those that begin with grayscale inputs learn to rely on luminance to identify objects. Once they begin receiving color input, they don’t change their approach very much, since they’ve already learned a strategy that works well. Models that began with color images did shift their approach once grayscale images were introduced, but could not shift enough to make them as accurate as the models that were given grayscale images first.

A similar phenomenon may occur in the human brain, which has more plasticity early in life, and can easily learn to identify objects based on their luminance alone. Early in life, the paucity of color information may in fact be beneficial to the developing brain, as it learns to identify objects based on sparse information.

“As a newborn, the normally sighted child is deprived, in a certain sense, of color vision. And that turns out to be an advantage,” Diamond says.

Researchers in Sinha’s lab have observed that limitations in early sensory input can also benefit other aspects of vision, as well as the auditory system. In 2022, they used computational models to show that early exposure to only low-frequency sounds, similar to those that babies hear in the womb, improves performance on auditory tasks that require analyzing sounds over a longer period of time, such as recognizing emotions. They now plan to explore whether this phenomenon extends to other aspects of development, such as language acquisition.

The research was funded by the National Eye Institute of NIH and the Intelligence Advanced Research Projects Activity.

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Science, health, and public trust.

September 8, 2021

Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

• Discoveries in Basic Science: A Perfectly Imperfect Process
• When Clinical Research Is in the News
• What is Basic Science and Why is it Important?
• ​ What is a Research Organism?
• What Are Clinical Trials and Studies?
• Basic Research – Digital Media Kit
• Decoding Science: How Does Science Know What It Knows? (NAS)
• Can Science Help People Make Decisions ? (NAS)

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How NASA Tracked the Most Intense Solar Storm in Decades

May 2024 has already proven to be a particularly stormy month for our Sun. During the first full week of May, a barrage of large solar flares and coronal mass ejections (CMEs) launched clouds of charged particles and magnetic fields toward Earth, creating the strongest solar storm to reach Earth in two decades — and possibly one of the strongest displays of auroras on record in the past 500 years.

We’ll be studying this event for years. It will help us test the limits of our models and understanding of solar storms.

Teresa Nieves-Chinchilla

Acting Director of NASA’s Moon to Mars (M2M) Space Weather Analysis Office

“We’ll be studying this event for years,” said Teresa Nieves-Chinchilla, acting director of NASA’s Moon to Mars (M2M) Space Weather Analysis Office. “It will help us test the limits of our models and understanding of solar storms.”

The first signs of the solar storm started late on May 7 with two strong solar flares. From May 7 – 11, multiple strong solar flares and at least seven CMEs stormed toward Earth. Eight of the flares in this period were the most powerful type, known as X-class, with the strongest peaking with a rating of X5.8. (Since then, the same solar region has released many more large flares, including an X8.7 flare — the most powerful flare seen this solar cycle — on May 14.)

Traveling at speeds up to 3 million mph, the CMEs bunched up in waves that reached Earth starting May 10, creating a long-lasting geomagnetic storm that reached a rating of G5 — the highest level on the geomagnetic storm scale, and one that hasn’t been seen since 2003.

“The CMEs all arrived largely at once, and the conditions were just right to create a really historic storm,” said Elizabeth MacDonald, NASA heliophysics citizen science lead and a space scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland.

When the storm reached Earth, it created brilliant auroras seen around the globe. Auroras were even visible at unusually low latitudes, including the southern U.S. and northern India. The strongest auroras were seen the night of May 10, and they continued to illuminate night skies throughout the weekend. Thousands of reports submitted to the NASA-funded Aurorasaurus citizen science site are helping scientists study the event to learn more about auroras.

“Cameras — even standard cell phone cameras — are much more sensitive to the colors of the aurora than they were in the past,” MacDonald said. “By collecting photos from around the world, we have a huge opportunity to learn more about auroras through citizen science.”

By one measure of geomagnetic storm strength, called the disturbance storm time index which dates back to 1957, this storm was similar to historic storms in 1958 and 2003. And with reports of auroras visible to as low as 26 degrees magnetic latitude, this recent storm may compete with some of the lowest-latitude aurora sightings on record over the past five centuries, though scientists are still assessing this ranking.

“It’s a little hard to gauge storms over time because our technology is always changing,” said Delores Knipp, a research professor in the Smead Aerospace Engineering Science Department and a senior research associate at the NCAR High Altitude Observatory, in Boulder, Colorado. “Aurora visibility is not the perfect measure, but it allows us to compare over centuries.”

MacDonald encourages people to continue submitting aurora reports to Aurorasaurus.org , noting that even non-sightings are valuable for helping scientists understand the extent of the event.

Leading up to the storm, the National Oceanic and Atmospheric Administration’s Space Weather Prediction Center, which is responsible for forecasting solar storm impacts, sent notifications to operators of power grids and commercial satellites to help them mitigate potential impacts.

Warnings helped many NASA missions brace for the storm, with some spacecraft preemptively powering down certain instruments or systems to avoid issues. NASA's ICESat-2 — which studies polar ice sheets — entered safe mode, likely because of increased drag due to the storm.  

Looking Forward

Better data on how solar events influence Earth's upper atmosphere is crucial to understanding space weather's impact on satellites, crewed missions, and Earth- and space-based infrastructure. To date, only a few limited direct measurements exist in this region. But more are coming. Future missions, such as NASA’s Geospace Dynamics Constellation (GDC) and Dynamical Neutral Atmosphere-Ionosphere Coupling (DYNAMIC), will be able to see and measure exactly how Earth’s atmosphere responds to the energy influxes that occur during solar storms like this one. Such measurements will also be valuable as NASA sends astronauts to the Moon with the Artemis missions and, later, to Mars.

The solar region responsible for the recent stormy weather is now turning around the backside of the Sun, where its impacts can’t reach Earth. However, that doesn’t mean the storm is over. NASA’s Solar TErrestrial RElations Observatory (STEREO), currently located at about 12 degrees ahead of Earth in its orbit, will continue watching the active region an additional day after it is no longer visible from Earth.

“The active region is just starting to come into view of Mars,” said Jamie Favors, director for the NASA Space Weather Program at NASA Headquarters in Washington. “We’re already starting to capture some data at Mars, so this story only continues.”

By Mara Johnson-Groh NASA’s Goddard Space Flight Center, Greenbelt, Md.

Media Contact: Sarah Frazier NASA’s Goddard Space Flight Center, Greenbelt, Md.

Related Terms

• Citizen Science
• Goddard Space Flight Center
• Heliophysics
• Heliophysics Division
• ICESat-2 (Ice, Cloud and land Elevation Satellite-2)
• Science & Research
• Science Mission Directorate
• Skywatching
• Solar Dynamics Observatory (SDO)
• Solar Flares
• Space Weather
• STEREO (Solar TErrestrial RElations Observatory)
• The Solar System
• The Sun & Solar Physics
• Thermosphere

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What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

• Observational
• Experimental
• Descriptive
• Retrospective
• Prospective
• Cross-sectional
• Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

• Case series
• Surveillance studies

II. Analytical research

• Observational studies: cohort, case control and cross- sectional research
• Interventional research: quasi-experimental and clinical research
• Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
• Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
• Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

• Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

• Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
• Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

• H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
• H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

• Type-I (α) and type-II (β) error levels
• Difference between groups (d-difference) and effect size (ES)
• Distribution ratio of groups
• Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

December 21, 2015

The Most Popular Science Studies of the Year

The attention-grabbing academic papers of 2015 include research on sexist video games and Homo erectus

By Jennifer Hackett

Issouf Sanogo Getty Images

The 2015 science research that set the Internet abuzz included a super antibiotic, plastics pollution in the ocean , climate change , and species extinction , according to Altmetric , a start-up that analyzes online activity surrounding academic papers.

Research never rests: every year thousands of scientific articles are published across dozens of journals and disciplines. Some studies capture the media’s attention and get coverage in numerous news stories; others speak to a more niche audience and take off in passionate social media discussions. For the second year Altmetric has compiled a list of the top 100 academic articles of the year . They studied the attention garnered by scientific articles from November 2014 up until November 16, 2015, examining how papers fared in news coverage and social media outlets such as Twitter, Facebook, and the popular Chinese microblogging site Sina Weibo. They also looked to see if studies were referenced by Wikipedia and policy papers outlining plans of actions written by analysts and think tanks.

To be clear, theirs is not a list of the most important studies of 2015. “It’s not about quality, necessarily, or even always about impact,” says Stacy Konkiel, an outreach manager at Altmetric. “We’re just looking at attention.” That explains how the twentieth overall story achieved its rank. On the surface, it was a paleontology paper. But it wasn’t the new horned dinosaur that interested the public: It was a marriage proposal tucked away in the paper’s footnotes.

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This year’s list includes studies from 34 different journals—both traditional and open access, the latter of which is steadily gaining ground and tends to get more of a boost from social media. Forty-two of the top 100 studies came from an open access journal.

More than half of the hottest studies were health-related, with environment-related studies trending right behind. Some of these studies might have gotten a boost from the attention on climate change due to the COP21 talks in Paris. These papers were particularly successful with traditional news coverage, with some having more than 100 news articles written about them.

Health and environment are typically hot topics, but there were surprises too: On the list was a story that gained quite a bit of traction (the eighth most popular article ) despite the fact it didn’t belong to either of the popular categories and only had two news articles written about it. The study, which compared the time effectiveness of major document preparation systems (word processors, such as Microsoft Word and the science-beloved LaTeX,) used by researchers to create their manuscripts saw 1,000 more tweets than any of the other top ten articles. “That is very surprising to me, personally, because it’s such a niche audience,” Konkiel says. “It obviously captured the interest of scientists who are very active on social media.”

The most-tweeted about article, a psychology study investigating whether or not sexist video games imparted sexist attitudes or mindsets onto the people who played them, was also an outlier. The study shared the most via Facebook, on the other hand, was about Homo erectus using shells as tools. Neither, clearly, involved health or environment. “We’re definitely seeing social media amplify studies that the mainstream media wouldn’t pick up,” Konkiel says. “As long as there’s an active community on social media, we see stories that otherwise might be niche get a lot of attention as measured by our score.”

“It’s not just about how many citations you’ve got or the impact factor of the journal you’ve published in, it’s who’s they’re sharing it with, and if they’re incorporating it into their day to day lives,” Konkiel says.

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Mass spectrometry is the gold standard for documenting and quantifying – down to a single cell – the peptides and proteins that inform human health and disease. At the Vincent Coates Foundation Mass Spectrometry Laboratory, students in the Translational Research and Applied Medicine (M-TRAM) program learn about the capabilities of the lab’s brand-new Bruker timsTOF Ultra. The instrument is one of a handful in the country and was part of a multiyear investment by the Office of the Vice Provost and Dean of Research to bring innovative technology to support researchers. The rapid analysis that the Bruker timsTOF Ultra provides is the backbone of modern biomedical research, and students are given this rare opportunity for direct access and training on their operation and capabilities.

This month-long immersive experience propels students to design more impactful research, helps them understand more deeply the causes of disease and effects of treatments, and prepares them for the evolving, science-based workforce they are about to enter. Take a peek inside the program.

Images by Aaron Kehoe

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The Stanford University Mass Spectrometry (SUMS) multidisciplinary research facility is an institution-wide resource of the Office of the Vice Provost and Dean of Research . The laboratory provides faculty, postdocs, and student researchers  in the fields of the physical and life sciences, medicine, and engineering with state-of-the-art, user-friendly training, technology, and services.

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Research Process

• Select a Topic
• Find Background Info
• Focus Topic
• List Keywords
• Search for Sources
• Evaluate & Integrate Sources
• Cite and Track Sources

What is Scientific Research?

Research study design, natural vs. social science, qualitative vs. quantitative research, more information on qualitative research in the social sciences, acknowledgements.

Thank you to Julie Miller, reference intern, for helping to create this page.

Some people use the term research loosely, for example:

• People will say they are researching different online websites to find the best place to buy a new appliance or locate a lawn care service.
• TV news may talk about conducting research when they conduct a viewer poll on current event topic such as an upcoming election.
• Undergraduate students working on a term paper or project may say they are researching the internet to find information.
• Private sector companies may say they are conducting research to find a solution for a supply chain holdup.

However, none of the above is considered “scientific research” unless:

• The research contributes to a body of science by providing new information through ethical study design or
• The research follows the scientific method, an iterative process of observation and inquiry.

The Scientific Method

• Make an observation: notice a phenomenon in your life or in society or find a gap in the already published literature.
• Ask a question about what you have observed.
• Hypothesize about a potential answer or explanation.
• Make predictions if our hypothesis is correct.
• Design an experiment or study that will test your prediction.
• Test the prediction by conducting an experiment or study; report the outcomes of your study.
• Iterate! Was your prediction correct? Was the outcome unexpected? Did it lead to new observations?

The scientific method is not separate from the Research Process as described in the rest of this guide, in fact the Research Process is directly related to the observation stage of the scientific method. Understanding what other scientists and researchers have already studied will help you focus your area of study and build on their knowledge.

Designing your experiment or study is important for both natural and social scientists. Sage Research Methods (SRM) has an excellent "Project Planner" that guides you through the basic stages of research design. SRM also has excellent explanations of qualitative and quantitative research methods for the social sciences.

For the natural sciences, Springer Nature Experiments and Protocol Exchange have guidance on quantitative research methods.

Books, journals, reference books, videos, podcasts, data-sets, and case studies on social science research methods.

Sage Research Methods includes over 2,000 books, reference books, journal articles, videos, datasets, and case studies on all aspects of social science research methodology. Browse the methods map or the list of methods to identify a social science method to pursue further. Includes a project planning tool and the "Which Stats Test" tool to identify the best statistical method for your project. Includes the notable "little green book" series (Quantitative Applications in the Social Sciences) and the "little blue book" series (Qualitative Research Methods).

Platform connecting researchers with protocols and methods.

Springer Nature Experiments has been designed to help users/researchers find and evaluate relevant protocols and methods across the whole Springer Nature protocols and methods portfolio using one search. This database includes:

• Nature Protocols
• Nature Reviews Methods Primers
• Nature Methods
• Springer Protocols

Open repository for sharing scientific research protocols. These protocols are posted directly on the Protocol Exchange by authors and are made freely available to the scientific community for use and comment.

Includes these topics:

• Biochemistry
• Biological techniques
• Chemical biology
• Chemical engineering
• Cheminformatics
• Climate science
• Computational biology and bioinformatics
• Drug discovery
• Electronics
• Energy sciences
• Environmental sciences
• Materials science
• Molecular biology
• Molecular medicine
• Neuroscience
• Organic chemistry
• Planetary science

Qualitative research is primarily exploratory. It is used to gain an understanding of underlying reasons, opinions, and motivations. Qualitative research is also used to uncover trends in thought and opinions and to dive deeper into a problem by studying an individual or a group.

Qualitative methods usually use unstructured or semi-structured techniques. The sample size is typically smaller than in quantitative research.

Example: interviews and focus groups.

Quantitative research is characterized by the gathering of data with the aim of testing a hypothesis. The data generated are numerical, or, if not numerical, can be transformed into useable statistics.

Quantitative data collection methods are more structured than qualitative data collection methods and sample sizes are usually larger.

Example: survey

Note: The above descriptions of qualitative and quantitative research are mainly for research in the Social Sciences, rather than for Natural Sciences as most natural sciences rely on quantitative methods for their experiments.

Qualitative research is approaching the world in its natural setting and in a way that reveals the particularities rather than doing studies in a controlled setting. It aims to understand, describe, and sometimes explain social phenomena in a number of different ways:

• Experiences of individuals or groups
• Interactions and communications
• Documents (texts, images, film, or sounds, and digital documents)
• Experiences or interactions

Qualitative researchers seek to understand how people conceptualize the world around them, what they are doing, how they are doing it or what is happening to them in terms that are significant and that offer meaningful learnings.

Qualitative researchers develop and refine concepts (or hypotheses, if they are used) in the process of research and of collecting data. Cases (its history and complexity) are an important context for understanding the issue that is studied. A major part of qualitative research is based on text and writing – from field notes and transcripts to descriptions and interpretations and finally to the presentation of the findings and of the research as a whole.

For more information, see:

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• Last Updated: May 21, 2024 1:45 PM
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Dozens of Egyptian pyramids, some in Giza, sat along a branch of the Nile, study says

The pyramids in and around Giza have presented a fascinating puzzle for millennia. 

How did ancient Egyptians move limestone blocks, some weighing more than a ton, without using wheels? Why were these burial structures seemingly built in the remote and inhospitable desert? 

New research — published Thursday in the journal Communications Earth & Environment — offers a possible answer, providing new evidence that an extinct branch of the Nile River once weaved through the landscape in a much wetter climate. Dozens of Egyptian pyramids across a 40-mile-long range rimmed the waterway, the study says, including the best-known complex in Giza.

The waterway allowed workers to transport stone and other materials to build the monuments, according to the study. Raised causeways stretched out horizontally, connecting the pyramids to river ports along the Nile’s bank. 

Drought, in combination with seismic activity that tilted the landscape, most likely caused the river to dry up over time and ultimately fill with silt, removing most traces of it.

The research team based its conclusions on data from satellites that send radar waves to penetrate the Earth’s surface and detect hidden features. It also relied on sediment cores and maps from 1911 to uncover and trace the imprint of the ancient waterway. Such tools are helping environmental scientists map the ancient Nile, which is now covered by desert sand and agricultural fields. 

Experts have suspected for decades that boats transported workers and tools to build the pyramids. Some past research has put forward hypotheses similar to the new study; the new findings solidify the theory and map a much broader area.  

“The mapping of the Nile’s ancient channel system has been fragmented and isolated,” an author of the new study, Eman Ghoneim, a professor of earth and ocean sciences at the University of North Carolina Wilmington, wrote in an email. “Ancient Egyptians were using waterways for transportation more often than we thought.”

The study looks at 31 pyramids between Lisht, a village south of Cairo, and Giza. They were constructed over roughly 1,000 years, beginning about 4,700 years ago. The pyramid complexes contained tombs for Egyptian royals. High officials were often buried nearby. 

Some of the granite blocks used to construct them were sourced from locations hundreds of miles south of their sites. In some cases, the blocks could be “mammoth,” weighing several tons, said Peter Der Manuelian, a professor of Egyptology at Harvard University and the director of the Harvard Museum’s Museum of the Ancient East.

Manuelian, who was not involved in the new study, said wheels were not used to move the large blocks, which is one reason researchers have long suspected the Egyptians moved materials by water.

“It’s all sledges,” he said. “Water helps an awful lot.”  

In the past, researchers have posited that the Egyptians might have carved canals to the pyramid sites. 

“Canals and waterway systems have been in the consciousness for decades now,” Manuelian said. But newer theories suggest that the Nile was closer to the pyramids than researchers once thought, he added, and new tools can provide some proof. 

“Archaeology has gotten more scientific, and you have ground-penetrating radar and satellite imagery,” he said.

He added that the new study helps improve maps of ancient Egypt.

The findings suggest that millennia ago, the Egyptian climate was wetter overall and the Nile carried a higher volume of water. It separated into multiple branches, one of which — the researchers call it the Ahramat Branch — was about 40 miles long. 

The locations of the pyramid complexes included in the study correspond in time with estimates of the river branch’s location, according to the authors, as water levels ebbed and flowed over centuries. 

In addition, several pyramid temples and causeways appear to line up horizontally with the ancient riverbed, which suggests that they were directly connected to the river and most likely used to transport building materials. 

The study builds on research from 2022 , which used ancient evidence of pollen grains from marsh species to suggest that a waterway once cut through the present-day desert.

Hader Sheisha, an author of that study who is now an associate professor in the natural history department at the University Museum of Bergen, said the new findings add much-needed evidence to bolster and expand the theory. 

“The new study, in concordance to our study, shows that when the pyramids were built, the landscape was different from that we see today and shows how the ancient Egyptians could interact with their physical world and harness their environment to achieve their immense projects,” Sheisha said in an email. 

Ghoneim and her team explain in the study that the Ahramat Branch shifted eastward over time, a process that might have been propelled by drought about 4,050 years ago. Then it gradually dissolved, only to be covered in silt. 

She said they plan to expand their map and work to detect additional buried branches of the Nile floodplain. Determining the outline and shape of the ancient river branch could help researchers locate the remains of settlements or undiscovered sites before the areas get built over. 

Manuelian said that today, “housing almost goes right up to the edge of the Giza plateau. Egypt is a vast outdoor museum, and there’s more to be discovered.”

Evan Bush is a science reporter for NBC News. He can be reached at [email protected].

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Recent Research in Science Teaching and Learning

• Sarah L. Eddy

*Address correspondence to: Sarah L. Eddy ( E-mail Address: [email protected] ).

Department of Biological Sciences, STEM Transformation Institute, Florida International University, Miami, FL 33199

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The Current Insights feature is designed to introduce life science educators and researchers to current articles of interest in other social science and education journals. In this installment, I highlight three diverse research studies: one addresses the relationships between active learning and teaching evaluations; one presents an observation tool for documenting metacognition in the classroom; and the last explores things teachers can say to encourage students to employ scientific reasoning during class discussions.

STUDENT EVALUATIONS AND ACTIVE LEARNING

Henderson, C., Khan, R., & Dancy, M. (2018). Will my student evaluations decrease if I adopt an active learning instructional strategy? American Journal of Physics , 86 (12), 934–942. https://doi.org/10.1119/1.5065907

Student evaluations are widely used and are often the sole source for the evaluation of faculty teaching. As described in the Introduction, fear that one’s student evaluations may decrease is one of the oft-cited reasons for faculty not adopting active-learning techniques. Yet this phenomenon has not been studied on a large scale. Henderson and colleagues test the hypothesis that active learning lowers student evaluations in a population of physics and astronomy instructors who participated in a long-running faculty development workshop. Forty percent (40%) of new physics and astronomy faculty attended this workshop. Of the more than 1300 workshop participants, 431 responded to a follow-up survey. Participants were asked about their use of active-learning methods in their most recent quantitative physics class; whether their student evaluations were impacted by the use of active learning; and whether students complained about the inclusion of active learning. If a faculty member reported a change in student evaluations, he or she was given an opportunity to provide an explanation for that change.

The majority of respondents saw either an increase (48%) or no change in their student evaluations (32%). The subset of instructors who reported receiving lower teaching evaluations also reported substantially less time lecturing than instructors who reported better evaluations. This pattern seemed driven by people using interactive methods for more than 80% of a class period, as this population was more likely to report reduced evaluations. Student complaints followed a similar pattern, with an increase in complaints becoming the most common outcome for instructors using active methods more than 80% of class time.

The reasons shared by instructors for why their evaluations changed were varied. For those who reported their evaluations improving, more than 20% of the instructors thought this increase was due to each of the following: students believing they were learning more, students enjoying class more, students enjoying interacting with one another, or students enjoying using technology. For those who reported lower evaluations, 40% reported that the students felt that the instructor was not teaching. Interestingly, many of these instructors also confessed as part of this comment that they were not good at “selling” the active learning. They next most common explanation given for lower evaluations was that students did not like working during class time; they would rather be listeners.

The results of this study suggest that, for the majority of faculty, adopting active learning will not negatively impact student evaluations. The study also suggests that those instructors concerned about student evaluations could incorporate active-learning activities for as much as 80% of class time and still not be likely to see a negative impact on their evaluations. This could be useful information to share with departmental colleagues and anyone mentoring new faculty who are deciding how to teach. As always, though, some caution should be taken in applying these results in a new context. Specifically, the authors acknowledge that they did not account for what types of active learning instructors implemented. It may be that some methods are more accepted by students than others.

TEACHERS TALKING METACOGNITION

Zepeda, C. D., Hlutkowsky, C. O., Partika, A. C., & Nokes-­Malach, T. J. (2018, October 29). Identifying teachers’ supports of metacognition through classroom talk and its relation to growth in conceptual learning. Journal of Educational Psychology (advance online publication). https://doi.org/10.1037/edu0000300

Metacognition refers to one’s knowledge and awareness of one’s own thought processes. As reviewed in the Introduction, metacognition is considered highly desirable for students, because it has been linked to many positive outcomes in experimental and classroom studies, including achievement, transfer of knowledge from one context to another, and motivation. Although many studies have focused on the use of planned interventions for metacognition, few have looked at what teachers are saying and doing spontaneously in the classroom that might influence student metacognition.

Zepeda and colleagues developed an observation protocol to detect classroom talk directed toward metacognitive growth in middle school students in math classrooms. They identified both the metacognitive content of the talk and the delivery method by documenting four dimensions, each with three possible states: the type of metacognitive knowledge being promoted; the metacognitive skill being worked on; the manner in which the teacher delivered this content; and how specific the metacognitive skill is frame d (from specific to the question being worked on to a more global approach to problem solving). For example, a teacher might say, “Alright, so explain to us what you are doing right now.” This would be coded as personal knowledge, because the student is asked about his or her own process. The skill being worked on would be monitoring, (i.e., being aware of why they are doing what they are doing). The manner in which the teacher delivers the content would be directive, because the teacher is telling the student to do something. The framing could be domain general, because the prompt could be used with any type of problem. I am not going to go further into the individual states for each dimension due to space, but there are lengthy descriptions of them within the original paper.

The authors use this observation tool with one class session from 39 middle school math instructors. The classes were selected from a larger national data set of middle school classrooms. Every class included in this larger data set had math knowledge assessments. The current authors created a smaller data set that included instructors who had the most student growth on the math assessment over a year and a set of instructors who had the least growth after accounting for various student- and instructor-level factors. Each video was transcribed and each teacher statement was examined for metacognitive talk. Any instance of metacognitive talk was coded for the four dimensions in the observation tool.

Overall, there were very few metacognitive statements made by teachers (∼7% of teacher statements), but even with this low overall percentage, there were some interesting patterns. The odds of teachers engaging in metacognitive talk were 4.75 times greater during whole-class activities than during activities done individually by students. In addition, in high math growth classes, the odds of instructors engaging in metacognitive talk were 1.5 times higher than in low math growth classes.

The content of the metacognitive talk differed between these two class types as well. In terms of the knowledge dimension, teachers in the high math growth classes elicited more personal knowledge statements in which students shared their own understanding of what they were doing in class than teachers in the low math growth classes. The high math growth class also had more statements focused on the skills of monitoring and evaluating their own work. In terms of how the metacognitive content was delivered (manner), the high math growth class had more directive statements. Finally, the high math growth classes had more domain-general framing of the metacognitive statements.

This study demonstrates that classroom observations can be used to explore metacognition and that the same methods that work most effectively in interventions designed to promote metacognition may also work more informally during teach talk in class. Although the authors cannot rule out that teachers who are more effective in other ways are also more likely to engage in metacognitive talk, the results do suggest that certain ways and certain content of metacognitive talk is more effective than others.

BUILDING STUDENT’S SCIENTIFIC REASONING IN CONVERSATIONS

Grinath, A. S., & Southerland, S. A. (2018). Applying the ambitious science teaching framework in undergraduate biology: Responsive talk moves that support explanatory rigor. Science Education ,  103 (1), 92–122. https://doi.org/10.1002/sce.21484

Active learning is centered around the idea that it encourages students to engage in their own learning, often through conversations about course content. Yet the quality of these conversations can vary. In this paper, Grinath and Southerland explore how instructors can influence in-class student discussions.

To explore the question of facilitation effects without confounding variables of differences between lessons, content, and students, the authors chose to work with 26 teaching assistants (TAs) instructing sections of the same introductory biology lab for nonmajors at the same university. This controlled both the content being presented to students across instructors and the structure of the lessons, as each TA was provided the same slides and the same training in how to conduct the lab. The laboratory lessons were designed around the Ambitious Science Teaching framework described in the Introduction, which is meant to help students engage in the meaningful practices of their discipline, including scientific dialogue. One aspect of this framework is helping students connect their everyday explanations of their experiences to the scientific principles underlying them, that is, bridging their everyday way of talking and science talk. This initial conversation is thought to help them meaningfully engage in the subsequent lesson. This study focuses on these initial conversations.

Grinath and Southerland recorded the 8- to 22-minute–long class discussions that opened a lab class exploring how organisms respond to stimuli. At the start of class, students were asked to describe how they experience stress and explain what is driving this response. The authors transcribed the recordings and characterized each TA discourse “move,” a statement made by a TA that served a specific communication function. These moves were coded as conservative or ambitious . Conservative patterns follow the traditional classroom pattern, in which the expertise lies with the instructor only. These moves include the instructor asking questions that only have one correct answer, usually about recalling facts or procedures; evaluating a student response as right or wrong; and explaining the connection between the student response and the scientific concept rather than having students make the connection. Ambitious patterns of discourse allow students to be experts, and the instructor is the facilitator. These instructor moves include asking questions with many possible reasonable answers, probing student responses, and pressing students to supply explanations for their answers. Finally, observers also coded TA moves as inclusive or not inclusive . Inclusive moves could include providing opportunities for multiple students to respond to a question, acknowledging a contribution without indicating correctness, and repeating student responses out loud.

The discourse moves were correlated with student talk. Grinath and Southerland used a framework for explanatory rigor of scientific talk to code student responses in the initial class discussion. There were three codes for student answers: fact , observation , and explanation . A turn of student talk was coded as fact if it was short and a vocabulary word or scientific definition not grounded in personal experience. Observations were what a student thought was happening based on personal experience. Finally, explanations were students’ ideas of why something was happening. The goal of ambitious science teaching is to help students start making their own explanations of phenomena grounded in science and their own experiences. Thus, TA discourse moves that promoted student explanations were considered the most important in this study.

Using linear regressions with a Bonferroni correction for multiple comparisons, Grinath and Southerland found that conservative discourse moves by TAs were related to an increase in student responses being simply fact statements. Ambitious questions (with multiple possible answers) did not predict student responses, but ambitious responses in which TAs deliberately probed student response and pressed students to expand on their answers did relate to increased explanations. Finally, inclusive moves together related to increased observations given by students.

This work highlights several interesting principles that could be expanded beyond labs. First, it seems that, without deliberately pressing for it (and removing the instructor’s explanations), students are not making explanations themselves. They offer facts or observations and wait for the instructor to put them together. Yet explaining phenomena is a key scientific practice and one students should develop. Second, how instructors respond to student answers is critical for creating meaningful conversations in the classroom, maybe even more critical than the qualities of the initial question itself.

• A Critical Feminist Approach for Equity and Inclusion in Undergraduate Biology Education 22 April 2021

© 2019 S. L. Eddy. CBE—Life Sciences Education © 2019 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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• 23 Apr 2024
• In Practice

Getting to Net Zero: The Climate Standards and Ecosystem the World Needs Now

What can companies and regulators do as climate predictions grow grimmer? They should measure impact, strengthen environmental institutions, and look to cities to lead, say Robert Kaplan, Shirley Lu, and Rosabeth Moss Kanter.

• 22 Apr 2024
• Research & Ideas

When Does Impact Investing Make the Biggest Impact?

More investors want to back businesses that contribute to social change, but are impact funds the only approach? Research by Shawn Cole, Leslie Jeng, Josh Lerner, Natalia Rigol, and Benjamin Roth challenges long-held assumptions about impact investing and reveals where such funds make the biggest difference.

• 18 Mar 2024

When It Comes to Climate Regulation, Energy Companies Take a More Nuanced View

Many assume that major oil and gas companies adamantly oppose climate-friendly regulation, but that's not true. A study of 30 years of corporate advocacy by Jonas Meckling finds that energy companies have backed clean-energy efforts when it aligns with their business interests.

• 12 Mar 2024

How Used Products Can Unlock New Markets: Lessons from Apple's Refurbished iPhones

The idea of reselling old smartphones might have seemed risky for a company known for high-end devices, but refurbished products have become a major profit stream for Apple and an environmental victory. George Serafeim examines Apple's circular model in a case study, and offers insights for other industries.

• 27 Feb 2024
• Cold Call Podcast

How Could Harvard Decarbonize Its Supply Chain?

Harvard University aims to be fossil-fuel neutral by 2026 and totally free of fossil fuels by 2050. As part of this goal, the university is trying to decarbonize its supply chain and considers replacing cement with a low-carbon substitute called Pozzotive®, made with post-consumer recycled glass. A successful pilot project could jump start Harvard’s initiative to reduce embodied carbon emissions, but it first needs credible information about the magnitude and validity of potential carbon reductions. Harvard Business School professor emeritus Robert Kaplan and assistant professor Shirley Lu discuss the flow of emissions along the supply chain of Harvard University’s construction projects, the different methods of measuring carbon emissions, including the E-liability approach, and the opportunity to leverage blockchain technology to facilitate the flow of comparable and reliable emissions information in the case, “Harvard University and Urban Mining Industries: Decarbonizing the Supply Chain.”

• 30 Jan 2024

Can Second-Generation Ethanol Production Help Decarbonize the World?

Raízen, a bioenergy company headquartered in São Paulo, is Brazil’s leader in sugar and ethanol production and the world’s leading ethanol trader. Since its creation in 2011, the company had primarily produced first-generation ethanol (E1G) from sugarcane, a crop that can also be used to produce sugar. In 2015, Raízen also started to produce second-generation ethanol (E2G), a biofuel derived from residual and waste materials, such as cane bagasse and straw – which don’t compete with food production. The company’s growth strategy focused on developing and boosting a low carbon portfolio that focused on E2G, based on the belief that Raízen—and Brazil—could help the world decarbonize and profit from the energy transition. Paula Kovarsky, Raízen’s chief strategy and sustainability officer, was confident the company could become a global green energy champion. But after the board’s approval for the first round of E2G investments, she faced a complex challenge: how to expand the market for second-generation ethanol and other sugar-cane waste biofuels, in order to ensure Raízen’s long-term growth? Harvard Business School professor Gunnar Trumbull and Kovarsky discuss the company’s strategy for bringing second-generation ethanol to the world in the case, “Raízen: Helping to Decarbonize the World?”

• 29 Jan 2024

Do Disasters Rally Support for Climate Action? It's Complicated.

Reactions to devastating wildfires in the Amazon show the contrasting realities for people living in areas vulnerable to climate change. Research by Paula Rettl illustrates the political ramifications that arise as people weigh the economic tradeoffs of natural disasters.

• 17 Jan 2024

Are Companies Getting Away with 'Cheap Talk' on Climate Goals?

Many companies set emissions targets with great fanfare—and never meet them, says research by Shirley Lu and colleagues. But what if investors held businesses accountable for achieving their climate plans?

• 09 Jan 2024

Could Clean Hydrogen Become Affordable at Scale by 2030?

The cost to produce hydrogen could approach the $1-per-kilogram target set by US regulators by 2030, helping this cleaner energy source compete with fossil fuels, says research by Gunther Glenk and colleagues. But planned global investments in hydrogen production would need to come to fruition to reach full potential.

• 02 Jan 2024

Should Businesses Take a Stand on Societal Issues?

Should businesses take a stand for or against particular societal issues? And how should leaders determine when and how to engage on these sensitive matters? Harvard Business School Senior Lecturer Hubert Joly, who led the electronics retailer Best Buy for almost a decade, discusses examples of corporate leaders who had to determine whether and how to engage with humanitarian crises, geopolitical conflict, racial justice, climate change, and more in the case, “Deciding When to Engage on Societal Issues.”

10 Trends to Watch in 2024

Employees may seek new approaches to balance, even as leaders consider whether to bring more teams back to offices or make hybrid work even more flexible. These are just a few trends that Harvard Business School faculty members will be following during a year when staffing, climate, and inclusion will likely remain top of mind.

• 19 Sep 2023

What Chandrayaan-3 Says About India's Entrepreneurial Approach to Space

India reached an unexplored part of the moon despite its limited R&D funding compared with NASA and SpaceX. Tarun Khanna discusses the significance of the landing, and the country's advancements in data and digital technology.

• 12 Sep 2023
• What Do You Think?

Who Gets the Loudest Voice in DEI Decisions?

Business leaders are wrestling with how to manage their organizations' commitment to diversity, equity, and inclusion. If you were a CEO, which constituency would you consider most: your employees, customers, or investors? asks James Heskett. Open for comment; 0 Comments.

• 26 Jul 2023

STEM Needs More Women. Recruiters Often Keep Them Out

Tech companies and programs turn to recruiters to find top-notch candidates, but gender bias can creep in long before women even apply, according to research by Jacqueline Ng Lane and colleagues. She highlights several tactics to make the process more equitable.

• 18 Jul 2023

Will Global Demand for Oil Peak This Decade?

The International Energy Agency expects the world's oil demand to start to ebb in the coming years. However, Joseph Lassiter and Lauren Cohen say the outlook will likely be more complex, especially as poor and fast-growing regions seek energy sources for their economies.

• 28 Apr 2023

Sweden’s Northvolt Electric Battery Maker: A Startup with a Mission

In Stockholm, Sweden an upstart battery maker, Northvolt, is trying to recreate the value chain for European car manufacturers making the switch to EVs. With two founders from Tesla and two experienced financiers at the helm, the company seems bound for success. But can they partner with government, scale fast enough, and truly be part of the climate solution? Harvard Business School professor George Serafeim discusses what it takes to scale a business—the right people, in the right place, at the right time—with the aim of providing a climate solution in the case, “Northvolt, Building Batteries to Fight Climate Change.” As part of a new first-year MBA course at Harvard Business School, this case examines the central question: what is the social purpose of the firm?

• 18 Apr 2023

What Happens When Banks Ditch Coal: The Impact Is 'More Than Anyone Thought'

Bank divestment policies that target coal reduced carbon dioxide emissions, says research by Boris Vallée and Daniel Green. Could the finance industry do even more to confront climate change?

• 11 Apr 2023

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How do songs and speech compare around the world? Northeastern music scientist contributes to groundbreaking study

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The Chinese folk tale “Butterfly Lovers” has been adapted for Chinese opera , television and film , and a folk tune of the legend has even inspired a violin concerto.  

Thanks to Northeastern University music professor Psyche Loui , the tale is also part of a groundbreaking new study that found common features of songs across many cultures.

The study, Loui says, united a large network of music science researchers, singers and musicians to look at how songs and speech compare around the world. 

“I’ve been interested in these questions about song and speech and how they differ around the world and how musical structure differs from linguistic structure around the world more generally,” says Loui, an associate professor of creativity and creative practice in the Department of Music and director of the MIND (Music, Imaging and Neural Dynamics) Lab at Northeastern.

“It’s a general question that’s been out there for a long time,” says Loui, who was part of a team of musicians and music scientists recruited by her fellow researcher Patrick Savage, who conducted the study.

A musicologist at the University of Auckland in New Zealand, Savage recorded songs in 55 languages.

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It is the second time that Loui and Savage collaborated. They co-authored a 2020 paper , “Music as a coevolved system for social bonding,” which established that one of the evolutionary reasons for music is to bring people together.

For the latest study, Loui recorded the “Butterfly Lovers” folk tune in Cantonese.

She did several takes. 

First, Loui sang the traditional song.

“I’m not even sure where it came from,” Loui says. “That’s the case with a lot of traditional music around the world. Nobody knows who wrote it, but we just recognize the tuning when we hear it.”

Loui then recorded herself saying the words of the song, followed by recording herself describing in Cantonese why she chose to contribute the song. 

Finally, she recorded herself playing that song on violin (Loui is a Western classically trained violinist).

Savage analyzed the songs to measure six features such as pitch and tempo. 

He found that songs across the cultures featured more pitch variation in song than in speech and slower pitch movement in song than in speech. 

Songs also tended to be a little bit louder and more extensive in the range of pitches they featured than speech.

“It seems like what I have noticed about singing and speaking are very common around the world,” Loui says. “It’s nice when these findings kind of fit with our intuitions, but it’s also good to know that what we’re doing is not a cultural anomaly.”

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