How To Take away Textual content From Footage And Images

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Computer images show cell that killed millions



a close up of a coral: MailOnline logo


© Provided by Daily Mail
MailOnline logo

A team of scientists in China have created the first images of the COVID-19 virus in an important milestone on the road to finding a vaccine and cure.

Dr Sai Li, a structural biologist at Tsinghua University in Beijing, worked with virologists who were creating the virus in a biosafety lab in the city of Hangzhou. 

They treated the virus with a chemical to make it harmless, then sent a sample of virus-filled fluid to Li.

He and his team reduced the virus to a single drop, which Li flash-froze, and then looked at through a cryo-electron microscope.  

‘I saw a screen full of viruses,’ Li told the New York Times, looking at something that measured less than a millionth of an inch.

‘I thought, I was the first guy in the world to see the virus in such good resolution.’



a close up of a colorful background: The coronavirus COVID-19 as seen using a new technique pioneered by a doctor in Beijing


© Provided by Daily Mail
The coronavirus COVID-19 as seen using a new technique pioneered by a doctor in Beijing



a close up of a plant: The new images are being used around the world to try and understand how the virus works


© Provided by Daily Mail
The new images are being used around the world to try and understand how the virus works

Li’s work has enabled scientists to learn how the virus some of its proteins to slip into cells.

They learnt how its twisted genes take over the body’s biochemistry. 

Researchers have observed how some viral proteins serve to wreak havoc on our cellular factories, while others build nurseries for making new viruses. 

And some researchers are using supercomputers to create complete, virtual viruses that they hope to use to understand how the real viruses have spread with such devastating ease.

‘This time is unlike anything any of us has experienced, just in terms of the bombardment of data,’ said Rommie Amaro, a computational biologist at the University of California at

Microsoft releases tool to update Defender inside Windows install images

microsoft-defender-atp-now-scans-windows-5eef8de69c89f47042ec66fd-1-jun-23-2020-12-00-14-poster.jpg

Microsoft has released on Friday a new tool that will allow system administrators to update the Defender security package inside Windows installation images (WIM or VHD supported).

The new tool was created for enterprise environments where workstations and servers are serviced or mass-installed using installation images.

Some of these images are reused for months at a time, and the Microsoft Defender (default antivirus) package found inside would usually end up being installed using an out-of-date detection database.

The newly installed Windows operating systems would eventually update the Defender package, but Microsoft says that this creates a “protection gap” during which systems could be easily attacked and infected.

Microsoft’s new tool is intended to allow system administrators to update their WIM or VHD installation images to contain the most recent Defender component before deploying it on their device fleet.

The new tool was provided for both 32-bit and 64-bit architectures and supports installation images for Windows 10 (Enterprise, Pro, and Home editions), Windows Server 2019, and Windows Server 2016.

“These links point to zip files defender-update-kit-[x86|x64].zip. Extract the .zip file to get the Defender update package (defender-dism-[x86|x64].cab) and an update patching tool (defenderupdatewinimage.ps1) that assists update operation for OS installation images,” Microsoft said on Friday.

iso-defender.png

To run the tool, just run the DefenderUpdateWinImage.ps1 Powershell script.

This script needs to be run with Administrator privileges from a 64-bit Windows 10 or later OS environment with PowerShell 5.1 or later versions. Powershell required modules include Microsoft.Powershell.Security and DISM.

How to apply this update

PS C:> DefenderUpdateWinImage.ps1 – WorkingDirectory<path> –Action AddUpdate – ImagePath <path_to_Os_Image> -Package <path_to_package>

How to remove or roll back this update

PS C:> DefenderUpdateWinImage.ps1 – WorkingDirectory<path> –Action RemoveUpdate – ImagePath <path_to_Os_Image>

How to list details of installed update

PS C:> DefenderUpdateWinImage.ps1 – WorkingDirectory<path> –

New Brain-Computer Interface Transforms Thoughts to Images

TheDigitalArtist/Pixabay

Source: TheDigitalArtist/Pixabay

Achieving the next level of brain-computer interface (BCI) advancement, researchers at the University of Helsinki used artificial intelligence (AI) to create a system that uses signals from the brain to generate novel images of what the user is thinking and published the results earlier this month in Scientific Reports.

“To the best of our knowledge, this is the first study to use neural activity to adapt a generative computer model and produce new information matching a human operator’s intention,” wrote the Finnish team of researchers.

The brain-computer interface industry holds the promise of innovating future neuroprosthetic medical and health care treatments. Examples of BCI companies led by pioneering entrepreneurs include Bryan Johnson’s Kernel and Elon Musk’s Neuralink.  

Studies to date on brain-computer interfaces have demonstrated the ability to execute mostly limited, pre-established actions such as two-dimensional cursor movement on a computer screen or typing a specific letter of the alphabet. The typical solution uses a computer system to interpret brain-signals linked with stimuli to model mental states. Seeking to create a more flexible, adaptable system, the researchers created an artificial system that can imagine and output what a person is visualizing based on brain signals. The researchers report that their neuroadaptive generative modeling approach is “a new paradigm that may strongly impact experimental psychology and cognitive neuroscience.”

The University of Helsinki researchers used a combination of a generative neural network with neuroadaptive brain interfacing to create a new BCI paradigm. Neuroadaptive generative modeling is the estimation of a person’s intentions via adapting a generative model to neural activity. To expand capabilities and not be limited to pre-defined categories, the researchers based the solution on a generative adversarial network (GAN) to generate novel information from a latent representation of an input space.

Generative adversarial networks are a relatively recent