Tuesday June 18, 2019

Researchers Find Molecule Effective Against Tuberculosis

In addition, they also found that administering the molecule to Mtb mouse models killed some of the bacteria they carried without harming them

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Tuberculosis
Novel drug may offer treatment for TB. Pixabay

Researchers have found a molecule that is effective against tuberculosis, says a new study on mice.

In the study, the group describes how it worked when tested in vitro and in a mouse model.

Tuberculosis is a bacterial infection caused by Mycobacterium tuberculosis (Mtb). This airborne pathogen tends to infect the lungs and is passed from person to person.

Back in the 1950s, researchers developed drugs to treat the disease.However, since that time, the bacteria has become resistance today, and almost one-third of all new cases are caused by antimicrobial-resistant strains.

Tuberculosis
Researchers identify molecule 8918 effective in killing TB bacteria. (Representational image). IANS

In this new effort, published in the journal Science, the researchers from University of Cape Town in South Africa, found that introducing the 8918 molecule to Mtb in a petri dish resulted in its death.

In addition, they also found that administering the molecule to Mtb mouse models killed some of the bacteria they carried without harming them.

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However, before 8918 can be considered a candidate for clinical trials, researchers must overcome one obstacle — it has a short half-life, which results in rapid microsomal metabolism indicating that it does not hang around long enough to kill many Mtb before the body flushes it away, the study noted. (IANS)

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Researchers Teaching Artificial Intelligence to Connect Senses Like Vision and Touch

The new AI-based system can create realistic tactile signals from visual inputs

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Tool, Humans, Robots
Members of that same MIT team applied the new algorithm to the BMW factory floor experiments and found that instead of freezing in place, the robot simply rolled on . Pixabay

A team of researchers at the Massachusetts Institute of Technology (MIT) have come up with a predictive Artificial Intelligence (AI) that can learn to see by touching and to feel by seeing.

While our sense of touch gives us capabilities to feel the physical world, our eyes help us understand the full picture of these tactile signals.

Robots, however, that have been programmed to see or feel can’t use these signals quite as interchangeably.

The new AI-based system can create realistic tactile signals from visual inputs, and predict which object and what part is being touched directly from those tactile inputs.

Teaching, Artificial Intelligence, Researchers
) A team of researchers at the Massachusetts Institute of Technology (MIT) have come up with a predictive Artificial Intelligence (AI). Pixabay

In the future, this could help with a more harmonious relationship between vision and robotics, especially for object recognition, grasping, better scene understanding and helping with seamless human-robot integration in an assistive or manufacturing setting.

“By looking at the scene, our model can imagine the feeling of touching a flat surface or a sharp edge”, said Yunzhu Li, PhD student and lead author from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).

“By blindly touching around, our model can predict the interaction with the environment purely from tactile feelings,” Li added.

The team used a KUKA robot arm with a special tactile sensor called GelSight, designed by another group at MIT.

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Using a simple web camera, the team recorded nearly 200 objects, such as tools, household products, fabrics, and more, being touched more than 12,000 times.

Breaking those 12,000 video clips down into static frames, the team compiled “VisGel,” a dataset of more than three million visual/tactile-paired images.

“Bringing these two senses (vision and touch) together could empower the robot and reduce the data we might need for tasks involving manipulating and grasping objects,” said Li.

The current dataset only has examples of interactions in a controlled environment.

Teaching, Artificial Intelligence, Researchers
While our sense of touch gives us capabilities to feel the physical world, our eyes help us understand the full picture of these tactile signals. Pixabay

The team hopes to improve this by collecting data in more unstructured areas, or by using a new MIT-designed tactile glove, to better increase the size and diversity of the dataset.

“This is the first method that can convincingly translate between visual and touch signals”, said Andrew Owens, a post-doc at the University of California at Berkeley.

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The team is set to present the findings next week at the “Conference on Computer Vision and Pattern Recognition” in Long Beach, California. (IANS)