Hexbyte Glen Cove You can help train NASA’s rovers to better explore Mars

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With AI4Mars, users outline rock and landscape features in images from NASA’s Perseverance Mars rover. The project helps train an artificial intelligence algorithm for improved rover capabilities on Mars. Credit: NASA/JPL-Caltech

Members of the public can now help teach an artificial intelligence algorithm to recognize scientific features in images taken by NASA’s Perseverance rover.

Artificial intelligence, or AI, has enormous potential to change the way NASA’s spacecraft study the universe. But because all machine learning algorithms require training from humans, a recent project asks members of the public to label features of scientific interest in imagery taken by NASA’s Perseverance Mars rover.

Called AI4Mars, the project is the continuation of one launched last year that relied on imagery from NASA’s Curiosity rover. Participants in the earlier stage of that project labeled nearly half a million images, using a tool to outline features like sand and rock that rover drivers at NASA’s Jet Propulsion Laboratory typically watch out for when planning routes on the Red Planet. The end result was an algorithm, called SPOC (Soil Property and Object Classification), that could identify these features correctly nearly 98% of the time.

SPOC is still in development, and researchers hope it can someday be sent to Mars aboard a future spacecraft that could perform even more autonomous driving than Perseverance’s AutoNav technology allows.

Images from Perseverance will further improve SPOC by expanding the kinds of identifying labels that can be applied to features on the Martian surface. AI4Mars now provides labels to identify more refined details, allowing people to choose options like float rocks (“islands” of rocks) or nodules (BB-size balls, often formed by water, of minerals that have been cemented together).

The goal is to hone an algorithm that could help a future rover pick out needles from the haystack of data sent from Mars. Equipped with 19 cameras, Perseverance sends anywhere from dozens to hundreds of images to Earth each day for scientists and engineers to comb through for specific geological features. But time is tight: After those images travel millions of miles from Mars to Earth, the team members have a matter of hours to develop the next set of instructions, based on what they see in those images, to send to Perseverance.

“It’s not possible for any one scientist to look at all the downlinked images with scrutiny in such a short amount of time, every single day,” said Vivian Sun, a JPL scientist who helps coordinate Perseverance’s daily operations and consulted on the AI4Mars project. “It would save us time if there was an algorithm that could say, ‘I think I saw rock veins or nodules over here,’ and then the science team can look at those areas with more detail.”

Especially during this developmental stage, SPOC requires lots of validation from scientists to ensure it’s labeling accurately. But even when it improves, the algorithm is not intended to replace more complex analyses by human scientists.

It’s all about the data

Key to any successful algorithm is a good dataset, said Hiro Ono, the JPL AI researcher who led the development of AI4Mars. The more individual pieces of data available, the more an algorithm learns.

The robotic arm of NASA’s Perseverance rover is visible in this image used by the AI4Mars project. Users outline and identify different rock and landscape features to help train an artificial intelligence algorithm that will help improve the capabilities of Mars rovers. Credit: NASA/JPL-Caltech

“Machine learning is very different from normal software,” Ono said. “This isn’t like making something from scratch. Think of it as starting with a new brain. More of the effort here is getting a good dataset to teach that brain and massaging the data so it will be better learned.”

AI researchers can train their Earth-bound algorithms on tens of thousands of images of, say, houses, flowers, or kittens. But no such data archive existed for the Martian surface before the AI4Mars project. The team would be content with 20,000 or so images in their repository, each with a variety of features labeled.

The Mars-data repository could serve several purposes, noted JPL’s Annie Didier, who worked on the Perseverance version of AI4Mars. “With this algorithm, the rover could automatically select science targets to drive to,” she said. It could also store a variety of images onboard the rover, then send back just images of specific features that scientists are interested in, she said.

That’s on the horizon; scientists may not have to wait that long for the algorithm to benefit them, however. Before the algorithm ever makes it to space, it could be used to scan NASA’s vast public archive of Mars data, allowing researchers to find surface features in those images more easily.

Ono noted it’s important to the AI4Mars team to make their own dataset publicly available so that the entire data science community can benefit.

“If someone outside JPL creates an algorithm that works better than ours using our dataset, that’s great, too,” he said. “It just makes it easier to make more discoveries.”

More about the mission

A key objective for Perseverance’s mission on Mars is astrobiology, including the search for signs of ancient microbial life. The rover will characterize the planet’s geology and past climate, pave the way for human exploration of the Red Planet, and be the first mission to collect and cache Martian rock and regolith (broken rock and dust).

Subsequent NASA missions, in cooperation with ESA (European Space Agency), would send spacecraft to Mars to collect these sealed samples from the surface and return them to Earth for in-depth analysis.

The Mars 2020 Perseverance mission is part of NASA’s Moon to Mars exploration approach, which includes Artemis missions to the Moon that will help prepare for human exploration of the Red Planet.



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You can help train NASA’s rovers to better explore Mars (2021, October 26)
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Hexbyte Glen Cove A new way to generate light through use of pre-existing defects in semiconductor materials

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A new method of quantum dot fabrication has been demonstrated by making use of intrinsic defects in LED materials. Through the formation of pyramids, localized bright luminescence emanates from the pyramid apexes containing indium-rich quantum dots. Credit: SMART

Researchers from the Low Energy Electronic Systems Interdisciplinary Research Group at Singapore-MIT Alliance for Research and Technology, MIT’s research enterprise in Singapore, together with collaborators at the MIT, National University of Singapore and Nanyang Technological University have discovered a new method of generating long-wavelength (red, orange, and yellow) light through the use of intrinsic defects in semiconducting materials, with potential applications as direct light emitters in commercial light sources and displays. This technology would be an improvement on current methods, which use phosphors, for instance, to convert one color of light to another.

A type of group-III element nitride-based -emitting diode (LED), indium gallium nitride (InGaN) LEDs were first fabricated over two decades ago in the 90s, and have since evolved to become ever smaller while growing increasingly powerful, efficient and durable. Today, InGaN LEDs can be found across a myriad of industrial and consumer use cases, including signals & optical communication and data storage—and are critical in high-demand consumer applications such as solid state lighting, television sets, laptops, mobile devices, augmented (AR) and virtual reality (VR) solutions.

Ever-growing demand for such electronic devices has driven over two decades of research into achieving higher optical output, reliability, longevity and versatility from semiconductors—leading to the need for LEDs that can emit different colors of light. Traditionally, InGaN material has been used in modern LEDs to generate purple and blue light, with aluminum gallium indium phosphide (AlGaInP) – a different type of semiconductor—used to generate red, orange, and yellow light. This is due to InGaN’s poor performance in the red and amber spectrum caused by a reduction in efficiency as a result of higher levels of indium required.

In addition, such InGaN LEDs with considerably high indium concentrations remain difficult to manufacture using conventional semiconductor structures. As such, the realization of fully solid-state white-light-emitting devices—which require all three primary colors of light—remains an unattained goal.

Addressing these challenges, SMART researchers have laid out their findings in a paper titled “Light-Emitting V-Pits: An Alternative Approach toward Luminescent Indium-Rich InGaN Quantum Dots”, recently published in the journal ACS Photonics. In their paper, the researchers describe a practical method to fabricate InGaN quantum dots with significantly higher indium concentration by making use of pre-existing defects in InGaN materials.

In this process, the coalescence of so-called V-pits, which result from naturally-existing dislocations in the material, directly forms indium-rich quantum dots, small islands of material that emit longer-wavelength light. By growing these structures on conventional silicon substrates, the need for patterning or unconventional substrates is further eliminated. The researchers also conducted high spatially-resolved compositional mapping of the InGaN quantum dots, providing the first visual confirmation of their morphology.

In addition to the formation of quantum dots, the nucleation of stacking faults—another intrinsic crystal defect—further contributes to emissions of longer wavelengths.

Jing-Yang Chung, SMART graduate student and lead author of the paper said, “For years, researchers in the field have attempted to tackle the various challenges presented by inherent defects in InGaN quantum well structures. In a novel approach, we instead engineered a nano-pit defect to achieve a platform for direct InGaN quantum dot growth. As a result, our work demonstrates the viability of using silicon substrates for new indium-rich structures, which along with addressing current challenges in the low efficiencies of long-wavelength InGaN light emitters, also alleviate the issue of expensive substrates.”

In this way, SMART’s discovery represents a significant step forward in overcoming InGaN’s reduced efficiency when producing red, orange and yellow light. In turn, this work could be instrumental in the future development of micro LED arrays consisting of a single material.

Dr. Silvija Gradečak, co-author and Principal Investigator at LEES, added, “Our discovery also has implications for the environment. For instance, this breakthrough could lead to a more rapid phasing out of non- sources—such as incandescent bulbs—and even the current phosphor-coated blue InGaN LEDs with a fully solid-state color-mixing solution, in turn leading to a significant reduction in global energy consumption.”

“Our work could also have broader implications for the semiconductor and electronics industry, as the new method described here follows standard industry manufacturing procedures and can be widely adopted and implemented at scale,” said SMART CEO and LEES Lead Principal Investigator Eugene Fitzgerald. “On a more macro level, apart from the potential ecological benefits that could result from InGaN-driven energy savings, our discovery will also contribute to the field’s continued research into and development of new efficient InGaN structures.”



More information:
Jing-Yang Chung et al, Light-Emitting V-Pits: An Alternative Approach toward Luminescent Indium-Rich InGaN Quantum Dots, ACS Photonics (2021). DOI: 10.1021/acsphotonics.1c01009

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Hexbyte Glen Cove More states are passing laws limiting authority to respond to public health emergencies

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Credit: CC0 Public Domain

New data released today by the Temple University Center for Public Health Law Research on LawAtlas.org captures details of an emerging effort by states to limit executive authority to act in response to public health emergencies.

Legislators in nearly all US (46) have introduced bills in 2021 to limit governors’ or ‘ authority during the COVID-19 pandemic or other emergencies. According to the data, between January 1, 2021, and June 17, 2021, 11 of these bills were enacted into law and became effective.

“Laws that restrict the authority of governors and health agencies to act in times of emergency could significantly impact by limiting their ability to take actions necessary to respond to or mitigate the crisis,” said Katie Moran-McCabe, special projects manager at the Center for Public Health Law Research and lead researcher on this project.

States have taken a variety of approaches to curbing public health authority. As of June 17, 2021:

  • Eleven states have a law in effect that was passed since January 1, 2021, that limits state executive authority regarding public health orders.
  • Nine states limited both the then-governor’s authority and the authority of a state agency or official, with all those states limiting the scope of at least one type of order.
  • Five states limited the governor’s authority, the authority of a state agency or official, and the authority of a local agency or official.

Some laws limit the duration of a state of emergency or limit emergency orders to a specific number of days (as in Arkansas for example). Others require approval of state health officer actions by an elected official (as in North Dakota) or prohibit the governor or health officials from requiring vaccination (as in Tennessee).

Kansas was the first state in 2021 to pass a law limiting public health emergency orders. Kansas is the only state to allow counties to issue a local order that is less stringent than a governor’s order, and that a local order may operate in the county in lieu of the governor’s executive order.

Utah is the only state that limited both state and local health officials in all of the following areas: restricting the ability to issue emergency orders, limiting the duration of emergency orders, restricting the scope of emergency orders, and establishing that emergency orders may be terminated by legislature or another entity.

The data were produced using a novel legal mapping technique, sentinel surveillance of emerging laws and policies, developed by the Center for Public Health Law Research, to track laws faster so researchers may more quickly evaluate the impact of these laws and policies on , well-being and equity.

“The sentinel surveillance of emerging laws and policies process is an advancement in our ability to track emerging laws rapidly so we may better understand the impacts these laws are having,” said Moran-McCabe. “Our concern with these laws is that they may greatly hobble state and local officials’ ability to respond to an emergency like the COVID-19 pandemic in a swift and flexible way. Evaluation will help us better understand that impact.”

Funding for the data and the development of the sentinel surveillance of emerging laws and policies process was provided by the Robert Wood Johnson Foundation, and research for the dataset was provided by the Association of State and Territorial Health Officials.



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More states are passing laws limiting authority to respond to public health emergencies (2021, October 26)

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Hexbyte Glen Cove Study finds nearly 500 ancient ceremonial sites in southern Mexico

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Credit: Pixabay/CC0 Public Domain

A team of international researchers led by the University of Arizona reported last year that they had uncovered the largest and oldest Maya monument—Aguada Fénix. That same team has now uncovered nearly 500 smaller ceremonial complexes that are similar in shape and features to Aguada Fénix. The find transforms previous understanding of Mesoamerican civilization origins and the relationship between the Olmec and the Maya people.

The team’s findings are detailed in a new paper published in the journal Nature Human Behavior. UArizona anthropology professor Takeshi Inomata is the paper’s first author. His UArizona coauthors include anthropology professor Daniela Triadan and Accelerator Mass Spectrometry Lab director Greg Hodgins.

Using data gathered through an airborne laser mapping technique called lidar, the researchers identified 478 complexes in the Mexican states of Tabasco and Veracruz. Lidar penetrates the tree canopy and reflects three-dimensional forms of archaeological features hidden under vegetation. The lidar data was collected by the Mexican governmental organization Instituto Nacional de Estadística y Geografía and covered a 32,800-square-mile area, which is about the same size as the island of Ireland.

Publicly available lidar data allows researchers to study huge areas before they follow up with high-resolution lidar to study sites of interest in greater detail.

“It was unthinkable to study an area this large until a few years ago,” Inomata said. “Publicly available lidar is transforming archaeology.”

Missing Links?

There’s a longstanding debate over whether the Olmec civilization led to the development of the Maya civilization or if the Maya developed independently.

The newly uncovered sites are located in a broad area encompassing the Olmec region and the western Maya lowlands. The complexes were likely constructed between 1100 B.C. and 400 B.C. and were built by diverse groups nearly a millennium before the heyday of the Maya civilization between A.D. 250 and 950.

The researchers found that the complexes share similar features with the earliest center in the Olmec area, San Lorenzo, which peaked between 1400 and 1100 BC. Aguada Fenix in the Maya area and other related sites began to adopt San Lorenzo’s form and formalize it around 1100 BC.

At San Lorenzo, the team also found a previously unrecognized rectangular space.

“The sites are big horizontally but not vertically,” Inomata said. “People will be walking on one and won’t notice its rectangular space, but we can see it with lidar really nicely.”

The researchers’ work suggests that San Lorenzo served as a template for later constructions, including Aguada Fénix.

“People always thought San Lorenzo was very unique and different from what came later in terms of site arrangement,” Inomata said. “But now we show that San Lorenzo is very similar to Aguada Fénix—it has a rectangular plaza flanked by edge platforms. Those features become very clear in lidar and are also found at Aguada Fénix, which was built a little bit later. This tells us that San Lorenzo is very important for the beginning of some of these ideas that were later used by the Maya.”

Sites Were Likely Ritual Spaces

The sites uncovered by Inomata and his collaborators were likely used as ritual gathering sites, according to the paper. They include large central open spaces where lots of people could gather and participate in rituals.

The researchers also analyzed each site’s orientation and found that the sites seem to be aligned to the sunrise of a certain date, when possible.

“There are lots of exceptions; for example, not every site has enough space to place the rectangular form in a desired direction, but when they can, they seem to have chosen certain dates,” Inomata said.

While it’s not clear why the specific dates were chosen, one possibility is that they may be tied to Zenith passage day, which is when the sun passes directly overhead. This occurs on May 10 in the region where the sites were found. This day marks the beginning of the rainy season and the planting of maize. Some groups chose to orient their sites to the directions of the sunrise on days 40, 60, 80 or 100 days before the zenith passage day. This is significant because the later Mesoamerican calendars are based on the number 20.

San Lorenzo, Aguada Fénix and some other sites have 20 edge platforms along the eastern and western sides of the rectangular plaza. Edge platforms are mounds placed along the edges of the large rectangular plazas. They define the shape of the plazas, and each are usually no taller than about 3 feet.

“This means that they were representing cosmological ideas through these ceremonial spaces,” Inomata said. “In this space, people gathered according to this ceremonial calendar.”

Inomata stressed that this is just the beginning of the team’s work.

“There are still lots of unanswered questions,” he said.

Researchers wonder what the social organization of the people who built the complexes looked like. San Lorenzo possibly had rulers, which is suggested by sculptures.

“But Aguada Fénix doesn’t have those things,” Inomata said. “We think that people were still somehow mobile, because they had just begun to use ceramics and lived in ephemeral structures on the ground level. People were in transition to more settled lifeways, and many of those areas probably didn’t have much hierarchical organization. But still, they could make this kind of very well-organized center.”

Inomata’s team and others are still searching for more evidence to explain these differences in social organization.

“Continuing to excavate the sites to find these answers will take much longer,” Inomata said, “and will involve many other scholars.”



More information:
Takeshi Inomata, Origins and spread of formal ceremonial complexes in the Olmec and Maya regions revealed by airborne lidar, Nature Human Beh

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Hexbyte Glen Cove Researchers identify new threat to American chestnut trees

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Emily Dobry, a graduate student conducting research at the Lake Erie Regional Grape Research and Extension Center, has identified a new fungal threat to the American chestnut tree. Credit: Penn State Behrend

For lumber companies, the American chestnut was a nearly perfect tree—tall, straight, rot-resistant and easy to split. It also was prolific, sending up new shoots that grew quickly.

In the early 1900s, the species made up a substantial portion of eastern hardwood forests. There were nearly four billion American chestnut trees in the United States, each growing up to 100 feet, with trunks four to seven feet thick. Healthy trees lived for 400 to 600 years, producing several bushels of nuts every year.

Today, however, it can be difficult to find a healthy American chestnut. A fungal pathogen on trees imported from Japan and China wiped the species out in less than 40 years. That loss is considered to be the greatest ecological disaster to ever strike the world’s forests.

“The pathogen is native to Chinese and Japanese chestnuts, so the two co-evolved,” said Emily Dobry, a Penn State Behrend graduate now in Penn State’s plant sciences horticulture master’s-degree program. She is doing research work at the University’s Lake Erie Regional Grape Research and Extension Center (LERGREC) in North East. “The American chestnut had never been exposed to it before, however, so it had little natural resistance. Think of it as smallpox for trees.”

Today, there are fewer than 1,000 American chestnut trees, largely in isolated areas outside of the tree’s historical range in the eastern half of the United States, along the Appalachian mountain ridge and throughout New England.

A few can be found at LERGREC, where researchers have been conducting a trial since 2013 with 15 chestnut trees—five each of the American, Chinese, and American-Chinese hybrid species developed by scientists, all planted in one long row.

“The idea was to plant American and Chinese chestnuts side by side with some of the hybrids that have been developed, and to allow them to be challenged with chestnut blight over the years,” said Bryan Hed, a plant pathologist at LERGREC.

“Most of the trees have suffered dieback from disease, insects or weather and have had to be cut back and renewed,” he said. “The hybrid trees are notable exceptions: Three of them are currently 17 to 21 feet in height.”

Trees are renewed using sucker growth from the original rootstock.

“The American chestnut is now designated as ‘functionally extinct,'” which means that although the species still technically survives, it cannot reproduce,” Dobry said. “The shoots rarely grow large enough to produce nuts, and therefore, future generations.”

The most promising hope for the American chestnut now is probably transgenic—the development of a genetically modified tree. Scientists are trying to engineer a tree that is as close to an American chestnut as possible, with just enough genetic material from the Chinese chestnut to resist the blight.

“Researchers have developed partially blight-resistant transgenic American chestnuts that are capable of surviving infection from the pathogen that causes blight,” Dobry said. “It doesn’t kill the pathogen; it’s still present, but it doesn’t destroy the tree.”

The current balance of species in U.S. forests could pose another problem as scientists try to reintroduce the American chestnut: The oak tree has risen to fill its place.

“It will be a challenge for the American chestnut to establish itself into the forest ecosystem again, “Dobry said.

The American chestnut could bring other problems to the forest. In 2018, while working as an undergraduate researcher at LERGREC, Dobry discovered a fungus that was atypical for the American chestnut species.

“Initially, we assumed this was an unusual presentation of chestnut blight infection,” she said, “but after taking samples and doing research, we did not find , but a pathogen commonly known as chestnut brown rot. At the time, there had been no published report of this fungus in our hemisphere.”

Dobry continues to study the domestically isolated strain, examining whether it may be harmful to species of trees closely related to the chestnut, such as oaks.

“If this proves pathogenic to oak, it could be another blow to dynamics,” she said. “That’s why the chestnut project and others like it are so important to protect the diversity and future of our forests.”



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Researchers identify new threat to American chestnut trees (2021, October 25)
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Hexbyte Glen Cove Study explores how climate change may affect rain in U.S. Corn Belt

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by Angela M. Rogers

Late-season Iowa corn field. Credit: Andrew carleton

Air humidity is more important than soil moisture in influencing whether it rains in the United States Corn Belt, an agricultural area in the Midwest, stretching from Indiana to Nebraska and responsible for more than 35% of the world’s most important grain crop, according to a new study by Penn State researchers.

“We were curious about the effect has on convective in the Corn Belt under different atmospheric conditions, such as dry or humid,” said Connor Chapman, who graduated in 2020 with a master of science degree in geography and is lead author on the paper. “Plenty of research of this nature has been done for the Great Plains region, but the neighboring Corn Belt—which has a different climate type—has received much less attention.”

Soil moisture is considered an essential climate variable, according to the Global Climate Observing System, because it determines the amount of evaporation and cooling of the air near the Earth’s surface. As soil moisture amounts decrease, either during drought or as a result of climate change, the reduced evaporation can amplify the warming, Carleton said.

“This study is important also because Corn Belt agriculture is mainly rainfed, rather than irrigated,” said Chapman’s adviser and co-author, E. Willard and Ruby S. Miller Professor of Geography Andrew Carleton. “So the Corn Belt is much more susceptible to year-to-year climate variations, like droughts and wet periods, and to the impacts from which are likely to increase this variability and lead to even greater extremes.”

For the Corn Belt, continued warming is likely to shift crop types northward and with a longer growing season, likely increasing climatic and market economic uncertainties going forward, Carleton said.

“Connor brought to bear—and integrated—a range of datasets spanning multiple scales; in particular, soil moisture data, vertical profiles of wind for the low-level jet stream and mapped atmospheric re-analyses of variables such as pressure and height,” Carleton said.

For this study, Chapman analyzed nine consecutive years of growing-season data on soil moisture, near-surface and low altitude wind velocity. He also created three sub-seasonal groups: Early, middle and late to see how the results might vary because as the growing season progresses in the Corn Belt, the land cover changes from bare to short crops to tall, intensely-evapotranspiring crops.

“The most challenging aspect of our study is the low amount of long-term soil data available for the Corn Belt,” Chapman said. “Compared with the Great Plains region, the Corn Belt does not have as much available in situ soil data, and only a limited number of soil data stations met the criteria for our study.”

Chapman said he was surprised by his results, which further illustrate how adjacent regions with different land cover experience different climate conditions.

“We found that during the early season when croplands are bare, convective precipitation is more likely to occur with drier soil, high humidity, and strong, humid low-altitude winds,” Chapman said. “Although soil moisture and wind vary across the , we found that high near-surface humidity consistently was most important for convective precipitation or rain.”

The article, Soil moisture influence on warm season convective precipitation for the U.S. Corn Belt, will be published in an upcoming issue of the Journal of Applied Meteorology and Climatology.



More information:
Connor J. Chapman et al, Soil moisture influence on warm-season convective precipitation for the U.S. Corn Belt, Journal of Applied Meteorology and Climatology (2021). DOI: 10.1175/JAMC-D-20-0285.1

Citation:
Study explores how climate change may affect rain in U.S. Corn Belt (2021, October 25)
retrieved 25 October 2021
from https://phys.org/news/2021-10-exp

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Hexbyte Glen Cove Nature-inspired coatings could power tiny chemistry labs for medical testing and more

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A newly developed coating that allows for certain liquids to move across surfaces without fluid loss could usher in new advances in a range of fields, including medical testing.

This new coating—created in the DREAM (Durable Repellent Engineered Advanced Materials) Laboratory, led by University of Toronto Engineering Professor Kevin Golovin—was inspired by the natural world.

“Nature has already developed strategies to transport liquids across surfaces in order to survive,” says Mohammad Soltani, researcher in the DREAM Laboratory and lead author of a new paper recently published in Advanced Functional Materials.

“We were inspired by the structural model of natural materials such as cactus leaves or spider silk. Our can directionally transport not only , but also low tension liquids that easily spread on most surfaces.”

The innovation has important implications for microfluidics, a field where small quantities of liquids are transported within tiny channels, often less than a millimetre wide. This technique has many applications, one of them being to miniaturize the standard analytical tests that are currently preformed in chemical laboratories.







New polymer coatings, developed by Professor Kevin Golovin and his team at the University of Toronto, show the precision with which liquids can move across surfaces. Credit: Mohammad Soltani / University of Toronto Engineering

By reducing the quantity of sample and reagents required, and automating protocols for working with them, microfluidics can power lab-on-a-chip devices that offer fast, inexpensive medical tests. Proponents hope this could lead to diagnosing multiple conditions in minutes using only a drop or two of blood.

But current microfluidic devices have a key limitation: they can only effectively handle liquids with high surface tension, such as water. This property, also known as cohesion, means that the has a greater tendency to stick to itself than to the sides of the channel it is being transported through.

High surface tension liquids form discrete droplets that can be moved around independently, like raindrops on window glass. Cohesion can even be exploited to pull the liquid droplets along the channel through a process known as .

By contrast, low surface tension liquids, such as alcohols and other solvents, tend to stick to the sides of the channels, and can currently be transported for only about 10 millimetres before the droplet disintegrates. Capillary action no longer applies, so this transport requires an external force, such as magnetism or heat, to move the droplets.

The new coating enables low surface tension liquids to be transported over distances of over 150 millimetres without losing any of the liquid, about 15 times longer than currently possible.







Credit: University of Toronto

The technology uses two newly developed polymer coatings, one of which is more liquid-repellent than the other. Both are composed of liquid-like polymer brushes. The more repellent coating acts as a background, surrounding the less repellent and creating tiny channels along the surface. The channels allow for the liquids to move in a desired pattern or direction without losing any of the liquid during transport or requiring additional energy input.

“Polymer brush coatings reduce the fluid friction and allow the droplets to be transported passively,” says Soltani, “Less friction means more energy is available to transport the liquid. We then create a driving force by designing the channels with specific patterns.”

The ability to transport low surface tension liquids without loss will allow for advancements in lab-on-a-chip devices. Using these unique coatings, researchers have the ability to transport liquids over a longer range, move multiple liquids at the same time along a precise pathway and even merge and split droplets—all without losing any volume or experiencing cross-contamination.

This technology will also help limit waste in research labs. With no residue left behind on the surface of the device and therefore no risk of cross-contamination, researchers can use the same devices over and over again.

“We’re looking at using this technology for microfluidics bioassays, as this is an area where every drop of liquid is precious,” says Golovin. “Our findings also have great potential to advance point-of-care diagnostics, such as liver or kidney disease, where biological marker screening is often performed in non-aqueous media.”



More information:
Mohammad Soltani et al, Lossless, Passive Transportation of Low Surface Tension Liquids Induced by Patterned Omniphobic Liquidlike Polymer Brushes, Advanced Functional Materials (2021). DOI: 10.1002/adfm.202107465

Citation:
Nature-inspired coatings could power tiny chemistry labs for medical testing and more (2021, October 22)
retrieved 24 October 2021
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Hexbyte Glen Cove Astronomers discover infant planet

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Discovery image of the planet 2M0437, which lies about 100 times the Earth-Sun distance from its parent star. The image was taken with the Subaru Telescope on Maunakea. The much-brighter host star has been mostly removed, and the four “spikes” are artifacts produced by the optics of the telescope. Credit: Subaru Telescope and Gaidos, et al. (2021)

One of the youngest planets ever found around a distant infant star has been discovered by an international team of scientists led by University of Hawaiʻi at Mānoa faculty, students, and alumni.

Thousands of planets have been discovered around other , but what sets this one apart is that it is newly-formed and can be directly observed. The planet, named 2M0437b, joins a handful of objects advancing our understanding of how planets form and change with time, helping shed new light on the origin of the Solar System and Earth. The in-depth research was recently published in Monthly Notices of the Royal Astronomical Society.

“This serendipitous discovery adds to an elite list of planets that we can directly observe with our telescopes,” explained lead author Eric Gaidos, a professor in the UH Mānoa Department of Earth Sciences. “By analyzing the light from this planet we can say something about its composition, and perhaps where and how it formed in a long-vanished disk of gas and dust around its host star.”

The researchers estimate that the planet is a few times more massive than Jupiter, and that it formed with its star several million years ago, around the time the main Hawaiian Islands first emerged above the ocean. The planet is so young that it is still hot from the energy released during its formation, with a temperature similar to the lava erupting from Kīlauea Volcano.

Subaru Telescope and Keck Observatory on Maunakea. Credit: University of Hawaii Institute for Astronomy

Key Maunakea telescopes

In 2018, 2M0437b was first seen with the Subaru Telescope on Maunakea by UH Institute for Astronomy (IfA) visiting researcher Teruyuki Hirano. For the past several years, it has been studied carefully utilizing other telescopes on the mauna.

Gaidos and his collaborators used the Keck Observatory on Maunakea to monitor the position of the as it moved across the sky, confirming that planet 2M0437b was truly a companion to the star, and not a more distant object. The observations required three years because the star moves slowly across the sky.

The planet and its parent star lie in a stellar “nursery” called the Taurus Cloud. 2M0437b is on a much wider orbit than the planets in the Solar System; its current separation is about one hundred times the Earth-Sun distance, making it easier to observe. However, sophisticated “adaptive” optics are still needed to compensate for the image distortion caused by Earth’s atmosphere.

“Two of the world’s largest telescopes, and Maunakea’s clear skies were all needed to make this discovery,” said co-author Michael Liu, an astronomer at IfA. “We are all looking forward to more such discoveries, and more detailed studies of such with the technologies and telescopes of the future.”

Future research potential

Gathering more in-depth research about the newly-discovered planet may not be too far away. “Observations with space telescopes such as NASA’s Hubble and the soon-to-be-launched James Webb Space Telescope could identify gases in its atmosphere and reveal whether the planet has a moon-forming disk,” Gaidos added.



More information:
Zodiacal Exoplanets in Time (ZEIT) XII: A Directly-Imaged Planetary-Mass Companion to a Young Taurus M Dwarf Star, Monthly Notices of the Royal Astronomical Society (2021). DOI: 10.1093/mnras/stab3069 , arxiv.org/abs/2110.08655

Citation:
Astronomers discover infant planet (2021, October 22)
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Hexbyte Glen Cove Machine learning predicts antibiotic resistance spread

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Credit: CC0 Public Domain

Genes aren’t only inherited through birth. Bacteria have the ability to pass genes to each other, or pick them up from their environment, through a process called horizonal gene transfer, which is a major culprit in the spread of antibiotic resistance.

Cornell researchers used machine learning to sort by their functions and use this information to predict with near-perfect accuracy how genes are transferred between them, an approach that could potentially be used to stop the spread of antibiotic resistance.

The team’s paper, “Functions Predict Horizontal Gene Transfer and the Emergence of Antibiotic Resistance,” published Oct. 22 in Science Advances. The lead author is doctoral student Hao Zhou.

“Organisms basically can acquire resistance genes from other organisms. And so it would help if we knew which organisms were exchanging with, and not only that, but we could figure out what are the driving factors that implicate organisms in this transfer,” said Ilana Brito, assistant professor and the Mong Family Sesquicentennial Faculty Fellow in Biomedical Engineering in the College of Engineering, and the paper’s senior author. “If we can figure out who is exchanging genes with who, then maybe it would give insight into how this actually happens and possibly even control these processes.”

Many novel traits are shared through gene transfer. But scientists haven’t been able to determine why some bacteria engage in gene transfer while others do not.

Instead of testing individual hypotheses, Brito’s team looked to bacteria genomes and their various functions—which can range from DNA replication to metabolizing carbohydrates—in order to identify signatures that indicate “who” were swapping genes and what was driving these networks of exchange.

Brito’s team used several , each of which teased out different phenomena embedded in the data. This enabled them to identify multiple networks of different antibiotic resistance genes, and across strains of the same organism.

For the study, the researchers focused on organisms associated with soil, plants and oceans, but their model is also well-suited to look at human-associated organisms and pathogens, such as Acinetobacter baumannii and E. coli, and within localized environments, such as an individual’s gut microbiome.

They found the machine-learning models were particularly effective when applied to antibiotic resistance genes.

“I think one of the big takeaways here is that the network of bacterial gene exchange—specifically for antibiotic resistance—is predictable,” Brito said. “We can understand it by looking at the data, and we can do better if we actually look at each organism’s genome. It’s not a .”

One of the most surprising findings was that the modeling predicted many possible antibiotic resistance transfers between human-associated bacteria and pathogens that haven’t yet been observed. These probable, yet undetected, transfer events were almost exclusive to human-associated bacteria in the or oral microbiome.

The research is emblematic of Cornell’s recently launched Center for Antimicrobial Resistance, according Brito, who serves on the center’s steering committee.

“One can imagine that if we can predict how these genes spread, we might be able to either intervene or choose a specific antibiotic, depending what we see in a patient’s gut,” Brito said. “More broadly, we may see where certain types of organisms are predicted to transfer with others in a certain environment. And we think there might be novel antibiotic targets in the data. For example, genes that could cripple these organisms, potentially, in terms of their ability to persist in certain environments or acquire these .”

Juan Felipe Beltrán, Ph.D. ’19, contributed to the research.



More information:
Hao Zhou et al, Functions predict horizontal gene transfer and the emergence of antibiotic resistance, Science Advances (2021). DOI: 10.1126/sciadv.abj5056. www.science.org/doi/10.1126/sciadv.abj5056

Citation:
Machine learning predicts antibiotic resistance spread (2021, October 22)
retrieved 24 October 2021
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Hexbyte Glen Cove US targeting Feb. 2022 to launch new lunar program Artemis

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A NASA employee holds the official Artemis mission patch at NASA Plum Brook Station in Sandusky, Ohio.

NASA is aiming to launch its uncrewed lunar mission Artemis 1 in February next year, the space agency said Friday, the first step in America’s plan to return humans to the Moon.

The agency had initially hoped to launch the by the end of this year, with astronauts set to walk on the Moon by 2024.

It achieved a major milestone Wednesday when it stacked the Orion crew capsule atop its Space Launch System megarocket, which now stands 322 feet (98 meters) tall inside the Vehicle Assembly Building at NASA Kennedy Space Center in Florida.

After further tests, it will be wheeled out to the launchpad for a “wet dress rehearsal” in January, with the first window for launch opening in February, officials told reporters on a call.

“The February launch period opens on the 12th and our last opportunity in February is on the 27th,” said Mike Sarafin, Artemis 1 mission manager. The next windows are in March and April.

These potential launch periods are dependent on orbital mechanics and the relative position of the Earth with respect to the Moon. The mission duration is expected to be four to six weeks.

NASA will also deploy small satellites, known as CubeSats, to perform experiments and technology demonstrations.

NASA achieved a major milestone when it stacked the Orion crew capsule atop its Space Launch System megarocket.

Artemis 2 is then scheduled for 2023 and Artemis 3 for the following year, when humans will walk on the Moon for the first time since 1972. Both missions are now likely to be pushed back, however.

NASA says the moonwalkers will include the first woman and first person of color to make the trip.

The is seeking to establish a sustainable presence on the Moon as well as use the lessons it learns to plan a crewed trip to Mars in the 2030s.

Selfies with the Moon

Orion first flew into in 2014, launched by a Delta IV rocket, making two circumnavigations of Earth and testing its heat shield on re-entry into the atmosphere.

But this time, NASA’s Sarafin said, the capsule will travel much faster and the temperature will be much higher when it returns from the Moon.

Artemis 1 has several objectives: to demonstrate Orion’s ability to return from the Moon and operate in where it is “much colder than in low Earth orbit,” and to successfully recover the spacecraft, he added.

The mission also plans to study radiation and take selfies of the capsule with the Moon in the background.



© 2021 AFP

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US targeting Feb. 2022 to launch new lunar program Artemis (2021, October 23)
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