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AI-powered study decodes the resilience of Spartina alterniflora

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AI-powered study decodes the resilience of Spartina alterniflora


Salt-stress survival: AI-powered study decodes the resilience of Spartina alterniflora
Workflow of the NetGO 3.0 framework. A Input data types. B Training set, test set, and cross-validation process. C Model training, model ranking, and GO term prediction. LR denotes logistic regression, KNN denotes k-nearest neighbor, and LTR denotes learning to rank. Credit: Chinese Academy of Sciences

Salt stress poses a major challenge to global crop production, especially in cereals, necessitating a comprehensive understanding of salt tolerance mechanisms. Halophytes like Spartina alterniflora, thriving in high-salinity environments, offer valuable insights due to their unique adaptations.

However, the molecular mechanisms behind their salt tolerance remain largely unexplored. Addressing these knowledge gaps is crucial for developing strategies to enhance crop resilience. Due to these challenges, there is a need for in-depth research to elucidate the genetic and molecular basis of salt tolerance in halophytes.

A collaborative research team from the Chinese Academy of Agricultural Sciences has made significant strides in this area, with their findings published in the journal Horticulture Research on March 28, 2024. The study employs machine learning to investigate the transcriptomic responses of Spartina alterniflora to various salt concentrations, revealing new insights into its salt tolerance mechanisms.

The study on Spartina alterniflora revealed significant transcriptional changes in response to salt stress, affecting key pathways such as gene transcription, ion transport, and reactive oxygen species metabolism.

A notable discovery was the identification of a SWEET gene family member, SA_12G129900.m1, which showed convergent selection with its rice ortholog, SWEET15. This gene is crucial for salt tolerance, suggesting its potential for genetic engineering to improve crop resilience.

The study also conducted genome-wide analyses of alternative splicing responses to salt stress, highlighting the complex interplay between transcriptional regulation and post-transcriptional modifications. Interestingly, there was minimal overlap between differentially expressed and differentially spliced genes, indicating distinct regulatory mechanisms.

This innovative approach, combining machine learning with transcriptomic analysis, provides a deeper understanding of salt tolerance mechanisms and offers valuable genetic resources for developing salt-tolerant crops.

Dr. Huihui Li, the corresponding author, stated, “Our innovative approach combining machine learning with transcriptomic analysis offers new insights into the salt tolerance mechanisms of Spartina alterniflora. This research not only enhances our understanding of halophyte biology but also provides valuable genetic resources for improving crop resilience in saline conditions.”

The findings from this study have significant implications for agricultural biotechnology. By identifying key genes and pathways involved in salt tolerance, researchers can develop genetically engineered crops with enhanced resilience to salt stress. This could lead to improved crop yields in saline environments, contributing to global food security in the face of climate change and soil salinization.

More information:
Zhangping Huang et al, Exploring salt tolerance mechanisms using machine learning for transcriptomic insights: case study in Spartina alterniflora, Horticulture Research (2024). DOI: 10.1093/hr/uhae082

Citation:
Salt-stress survival: AI-powered study decodes the resilience of Spartina alterniflora (2024, July 1)
retrieved 1 July 2024
from https://phys.org/news/2024-07-salt-stress-survival-ai-powered.html

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Portable engine can power artificial muscles in assistive devices

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Portable engine can power artificial muscles in assistive devices


Portable engine can power artificial muscles in assistive devices
Left: Evaluation of the effect of the assistance on the activity of the biceps muscle while lifting a weight of 5 kg. Results showed that on average the muscle activity was reduced by 39% with assistance compared to the condition without wearing the device. Middle: Demonstration of high assistive force: the muscle is able to lift a 20 kg object 18 mm off the ground. Right: Proof-of-concept demonstration of wearable robot application to assist ankle plantar flexion. Credit: Advanced Intelligent Systems (2024). DOI: 10.1002/aisy.202400171

Researchers have developed a lightweight fluidic engine to power muscle-mimicking soft robots for use in assistive devices. What sets the new engine apart is its ability to generate significant force without being tethered to an external power source.

“Soft robots that are powered by fluid engines—such as hydraulic or pneumatic action—can be used to mimic the behavior of muscle in ways that rigid robots cannot,” says Hao Su, corresponding author of a paper on the work and an associate professor of mechanical and aerospace engineering at North Carolina State University.

“This makes these robots particularly attractive for use in assistive devices that improve people’s ability to move their upper or lower limbs.”

However, most fluid engines are physically connected to an external power source, such as a large air compressor. That significantly limits their utility. And previous fluid engines that were not tethered to external power sources were not able to generate much force, which also limited their utility.

“Our work here addresses both of those challenges,” Su says. “Our fluidic engine is not tethered to an external source but can still generate up to 580 Newtons of force.”

The new engine works by pumping oil into and out of a chamber in a soft robot, causing the soft robot to act as an artificial muscle that is flexing and relaxing. The fluidic engine’s pump is driven by a battery-powered high-torque motor that allows it to generate significant pressure, enabling the artificial muscle to exert significant force.






The untethered engine. Credit: North Carolina State University

In proof-of-concept testing, the researchers not only assessed the amount of force the new engine can generate, but how efficiently the engine converts electrical power into fluidic power.

“We found that we were able to generate an unprecedented amount of force for an untethered engine, while still keeping the weight of the fluidic engine low,” says Antonio Di Lallo, first author of the paper and a postdoctoral researcher at NC State.

“And the maximum efficiency of our fluidic engine is higher than previous portable, untethered engines.”

The paper, “Untethered Fluidic Engine for High-Force Soft Wearable Robots,” is published open access in the journal Advanced Intelligent Systems.

More information:
Antonio Di Lallo et al, Untethered Fluidic Engine for High‐Force Soft Wearable Robots, Advanced Intelligent Systems (2024). DOI: 10.1002/aisy.202400171

Citation:
Portable engine can power artificial muscles in assistive devices (2024, July 1)
retrieved 1 July 2024
from https://techxplore.com/news/2024-07-portable-power-artificial-muscles-devices.html

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Machine learning algorithm proves to be highly accurate in predicting Mount St. Helens eruptions

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Machine learning algorithm proves to be highly accurate in predicting Mount St. Helens eruptions


Machine learning algorithm proves to be highly accurate in predicting Mount St. Helens eruptions
Flowchart of the methodology designed for this analysis. Credit: Frontiers in Earth Science (2024). DOI: 10.3389/feart.2024.1342468

A team of physicists, geologists and signal theorists from the University of Granada, Spain, has developed a machine-learning-based algorithm designed to predict when Mount St. Helens will erupt.

In their study, published in the journal Frontiers in Earth Science, the group built their algorithm and used it to predict past eruptions using past data.

Scientists have for many years been trying to predict when a given volcano will erupt—as part of that effort, they have installed sensors on and near volcanoes to learn more about the types of volcanic activity that lead to eruptions.

Thus far, such efforts have failed to be of much use. It is still not possible to predict an eruption beyond a day or two because there is so much conflicting data. Some signals that might indicate an imminent eruption for one volcano may mean nothing for another.

In this new effort, the research team improved their odds of predicting eruptions by studying a single volcano, Mount St. Helens, located in Skamania County Washington, in the U.S.

The work involved collecting as much data as possible for the volcano recorded over many years, including prior to and during the massive eruption of 1980—one of the mightiest volcanic eruptions to have occurred in modern times in North America. It was also one of the deadliest and most economically destructive.

The researchers used the data to train a machine-learning algorithm, hoping it would find patterns that human researchers have missed. They also added math formulas designed to seek meaning from earthquake signals, such as the amount of pressure building up, or energy stored.

The researchers then trained the algorithm with data from several eruptions and prompted it to predict whether an eruption was imminent prior to those earlier eruptions. The team found their algorithm to be 95% accurate in predicting past eruptions at least three days in advance.

The new effort comes as other teams monitoring the volcano report that it’s exhibiting behavior that might be indicative of another impending eruption—350 earthquakes since February, many of which were centered miles below the crater floor.

More information:
Pablo Rey-Devesa et al, Universal machine learning approach to volcanic eruption forecasting using seismic features, Frontiers in Earth Science (2024). DOI: 10.3389/feart.2024.1342468

© 2024 Science X Network

Citation:
Machine learning algorithm proves to be highly accurate in predicting Mount St. Helens eruptions (2024, July 1)
retrieved 1 July 2024
from https://phys.org/news/2024-07-machine-algorithm-highly-accurate-mount.html

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Deep dive into past climates paints grim outlook for fish species

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Deep dive into past climates paints grim outlook for fish species


Deep dive into past climates paints grim outlook for fish species
A mallee eucalyptus species, in Fitzgerald River National Park, Western Australia. There are more than 500 species of eucalypt in WA and many of them are endemic, making them a big contributor to its status as a biodiversity hotspot. Credit: S Buckley (ECU/UWA)

Climatic stability over millions of years has allowed ancient and isolated freshwater fishes to flourish in areas such as the 356,000 square kilometers from Shark Bay to Esperance in southwest Western Australia.

But now accelerating climate changes threaten this biodiversity hotspot and its native fish species, according to new research in journal Heredity led by Matthew Flinders Professor Luciano Beheregaray and Ph.D. Sean Buckley.

Made up of temperate forests and grasslands, the corner of the continent hosts more than 8,000 species of plants, of which about half are endemic, and more than 500 recorded vertebrate species.

Unfortunately, the southwest section of WA is also a climate change hotspot as hotter, drier conditions take hold, a journal summary explains.

Since the 1970s, rainfall has decreased by 10–15% and is predicted to worsen in the coming decades. Over the last century, the region has also experienced a 1.1°C increase in temperature.

“This remarkable biodiversity is already suffering the consequences, including species declines and recent forest die-offs,” says Flinders University Molecular Ecology Lab researcher Dr. Buckley, now Lecturer in Molecular Ecology and Environmental Management at Edith Cowan University, WA.

“This is especially concerning if historically stable climates have been key to generating this biodiversity: climate change presents a novel threat to this incredible ecosystem, and endemic species might not have evolved the capacity to respond.

“Understanding the role of historical climate stability is required to better predict the potential impacts of climate change in the region.”

The research focused on two small freshwater fishes endemic to the region: the western (Nannoperca vittata) and little (Nannoperca pygmaea) pygmy perches.

The western pygmy perch is found across the region, while the little pygmy perch is only found in a handful of rivers (and is listed as Endangered in state, national and global conservation lists).

“Based on our prior research, we knew that these species had likely existed in the landscape for a very long time and would be ideal models to look at the interaction of climatic history and evolutionary patterns,” says Professor Beheregaray.

The Molecular Ecology Lab study generated genomic data from nine populations accessed through museum collections, assessing their evolutionary relationships, divergence histories, and gene flow over time.

He says, “We combined these methods with environmental approaches—specifically, species distribution modeling—to see how the climatic history of the region had shaped their evolution.

“Using a time calibration derived from previous studies, we found that these two cryptic species last shared an ancestor around nine million years ago, with no evidence for gene flow between them. This suggests that they have been persisting in isolation for a very long time.”

The environmental approaches supported this conclusion.

Using reconstructions of past climate in the region, the study found relatively little change in species ranges over time: save for a small expansion coastward during the lower sea levels of ice ages, pygmy perches have been found in the same areas since the Pliocene.

“These patterns reflect the climate itself, which has remained relatively stable over that same time period, particularly compared to other parts of Australia,” adds Dr. Buckley.

“However, modeling these distributions under future climate change produced a stark picture, with large declines in range across the species. In a business-as-usual scenario, this included the complete loss of suitable climate for one of the cryptic species within the next few decades.”

Conservation management actions which improve adaptive capacity, like genetic rescue, might be necessary to preserve the unique diversity of this part of WA.

Other ambitious strategies, like captive-breeding and reintroductions programs have been successful for other threatened pygmy perches, and may be necessary in the future, researchers say.

More information:
Sean James Buckley et al, Long-term climatic stability drives accumulation and maintenance of divergent freshwater fish lineages in a temperate biodiversity hotspot, Heredity (2024). DOI: 10.1038/s41437-024-00700-6

Citation:
Deep dive into past climates paints grim outlook for fish species (2024, July 1)
retrieved 1 July 2024
from https://phys.org/news/2024-07-deep-climates-grim-outlook-fish.html

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Advocacy groups push Sen. Sanders to share Amazon investigation details

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Advocacy groups push Sen. Sanders to share Amazon investigation details


Amazon
Credit: Unsplash/CC0 Public Domain

Congress is pressing Amazon to share more information about its safety record—from warehouses to delivery drivers—but some workers’ rights advocacy groups say lawmakers aren’t moving fast enough.

On Thursday, roughly one year since Sen. Bernie Sanders launched a congressional investigation into Amazon’s warehouse working conditions, more than 30 advocacy groups sent a letter to the Vermont lawmaker asking for a public release of the findings.

Sanders asked Amazon warehouse workers last June to share their stories and the company to share information about its injury rate, employee turnover, pace of work and in-house medical services to treat workplace injuries.

“Given the high stakes of this investigation, we are eager to see progress,” the advocacy groups wrote on June 27.

“If lawmakers and regulators fail to take action, the company’s dangerous and extractive model will become the standard in warehousing, logistics and retail,” the letter continued. “The result will be a punishing, untenable reality for workers in these important jobs.”

The groups hoped to get more information about the investigation by mid-July, when Amazon’s annual Prime Day sale will mean a spike in orders and the possibility of increased pressure on workers to keep packages moving through the warehouses.

Amazon disputed Sanders’ original allegations last June that the company’s warehouses are “one of the most dangerous” places to work. The company said it has seen a decline in injury rates for two consecutive years, due to investments in training, workplace “safety professionals,” technology and equipment.

But, some advocacy groups, including some of the organizations that signed Thursday’s letter, have accused Amazon of failing to tell the whole story in its safety reports. On top of that, the groups say, Amazon still has an incredibly high injury rate at its warehouses.

Amazon spokesperson Maureen Lynch Vogel said the company has cooperated with the investigation and will continue to. “Our safety record has continued to improve,” she said. “We continue to work to be best in class.”

Sanders, who chairs the Senate’s Health, Education, Labor and Pensions, or HELP, Committee, didn’t respond to requests for comment in time for publication.

The letter comes at the same time a bipartisan group of senators is looking into another aspect of Amazon’s workforce. A group of 29 senators sent a letter to Amazon CEO Andy Jassy in January asking for more information about working conditions for Amazon’s network of independent delivery drivers.

Some of the company’s Delivery Service Partners, independent businesses that help make deliveries for Amazon, have accused the company of setting an unsafe pace of work and creating a hazardous work environment for drivers, including skipping breaks and making deliveries in extreme weather conditions without proper equipment.

Those allegations have led drivers to picket 25 Amazon warehouses in nine states, according to the congressional letter.

“Over the last few years, reports of unsafe and unfair working conditions have demonstrated that widespread safety and labor violations appear to be a feature, not a bug, of the DSP program,” lawmakers wrote in the letter. “Clearly, further Senate oversight of Amazon’s DSP program is overdue.”

Amazon disputed the allegations in the letter.

“DSPs are small business owners and entrepreneurs who are creating good jobs, with great pay and benefits, for more than 275,000 drivers around the world,” Lynch Vogel said. “We strongly dispute the claims in the letter and look forward to sharing the facts.”

Ryan Gerety, executive director of the Athena Coalition, one of the advocacy groups that signed Thursday’s letter, said the groups look forward to seeing the results of both inquiries but are particularly concerned about the status of the investigation into warehouse working conditions because it has been a year since it began.

“In response to a groundswell of Amazon workers organizing for better conditions across the country, multiple state and federal investigations are currently scrutinizing Amazon’s treatment of its workers,” Gerety said. “Now, we need action.”

2024 The Seattle Times. Distributed by Tribune Content Agency, LLC.

Citation:
Advocacy groups push Sen. Sanders to share Amazon investigation details (2024, July 1)
retrieved 1 July 2024
from https://techxplore.com/news/2024-07-advocacy-groups-sen-sanders-amazon.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





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