Lifeboat Foundation

The animation describes the concept of launching a nuclear fusion reactor into orbit in sections for final assembly in space. The concept uses live footage of Pulsar’s existing hall effect plasma thrusters (HET) and hybrid rocket engines tested at RAF Westcott in March 2022. Pulsar is also developing LOX / Methane rocket motors to support this concept.

China has set up over 100 illegal police stations abroad. They have been tasked with policing the Chinese community, and threatening dissidents to return home. A lot of these police stations are in the West, but the Western govts are silent. Are they scared of China? Priyanka Sharma tells you.

#Gravitas #China #PoliceStations.

Continue reading “Gravitas | Operation dragon net: How China is setting up illegal police stations globally” »

ChatGPT is amazing. It really is.

It can write romantic poems, summarize complex text, provide engaging fun conversations, and answer sophisticated general knowledge questions. It can also produce a fake report for your boss of what you’ve (supposedly) been working on for the last few days — complete with perfectly (surface) plausible code snippets! It makes up stuff.

So could ChatGPT replace human agents in a contact center?

This Video Explains Long noncoding RNA.

Thank You For Watching.

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Even worms have a ticking fertility clock. Older worms are less efficient at repairing broken DNA strands while making egg cells—part of a process that’s essential for fertility. A new study from University of Oregon (UO) biologists suggests one possible reason that reproduction slows with age.

Researchers from the lab of Diana Libuda report the findings in a paper published Nov. 7 in PLOS Genetics.

Each sperm or egg cell has only half the number of chromosomes found in a regular cell. During meiosis, the cell division process that forms sperm and eggs, the parent cells must evenly divide their DNA. The costs of error can be high, since incorrectly divided chromosomes are a major cause of birth defects.

One of the promising technologies being developed for next-generation augmented/virtual reality (AR/VR) systems is holographic image displays that use coherent light illumination to emulate the 3D optical waves representing, for example, the objects within a scene. These holographic image displays can potentially simplify the optical setup of a wearable display, leading to compact and lightweight form factors.

On the other hand, an ideal AR/VR experience requires relatively high-resolution images to be formed within a large field-of-view to match the resolution and the viewing angles of the human eye. However, the capabilities of holographic image projection systems are restricted mainly due to the limited number of independently controllable pixels in existing image projectors and spatial light modulators.

A recent study published in Science Advances reported a deep learning-designed transmissive material that can project super-resolved images using low-resolution image displays. In their paper titled “Super-resolution image display using diffractive decoders,” UCLA researchers, led by Professor Aydogan Ozcan, used deep learning to spatially-engineer transmissive diffractive layers at the wavelength scale, and created a material-based physical image decoder that achieves super-resolution image projection as the light is transmitted through its layers.

When trying to make a purchase with a shopping app, we may quickly browse the recommendation list while admitting that the machine does know about us—at least, it is learning to do so. As an effective emerging technology, machine learning (ML) has become pretty much pervasive with an application spectrum ranging from miscellaneous apps to supercomputing.

Dedicated ML computers are thus being developed at various scales, but their productivity is somewhat limited: the workload and development cost are largely concentrated in their software stacks, which need to be developed or reworked on an ad hoc basis to support every scaled model.

To solve the problem, researchers from the Chinese Academy of Sciences (CAS) proposed a fractal parallel computing model and published their research in Intelligent Computing on Sept. 5.

It is common to hear news reports about large data breaches, but what happens once your personal data is stolen? Our research shows that, like most legal commodities, stolen data products flow through a supply chain consisting of producers, wholesalers and consumers. But this supply chain involves the interconnection of multiple criminal organizations operating in illicit underground marketplaces.

The stolen data supply chain begins with producers—hackers who exploit vulnerable systems and steal sensitive information such as credit card numbers, bank account information and Social Security numbers. Next, the stolen data is advertised by wholesalers and distributors who sell the data. Finally, the data is purchased by consumers who use it to commit various forms of fraud, including fraudulent credit card transactions, identity theft and phishing attacks.

This trafficking of stolen data between producers, wholesalers and consumers is enabled by darknet markets, which are websites that resemble ordinary e-commerce websites but are accessible only using special browsers or authorization codes.

In biological imaging, researchers aim to achieve 3D, high-speed, and high-resolution, with low photobleaching and phototoxicity. The light-sheet fluorescence microscope (LSFM) helps meet that aim. Based on a unique excitation and detection scheme, the LSFM can image live specimens with high spatiotemporal resolution and low photobleaching. It has shown great potential for 3D imaging of biological samples.

The principle of LSFM technology is to illuminate the sample with a thin light-sheet and then collect the emitted fluorescence along the axis perpendicular to the transmission of the light-sheet. Therefore, only fluorophores close to the focal plane are excited and detected. Using a thinner light-sheet improves the axial resolution, while a longer light-sheet improves the field of view (FoV) and imaging speed. Tradeoffs are required, as it is difficult to generate a thin, uniform light-sheet.

Multiple light-sheets can be tiled to generate a virtual light-sheet with a higher aspect ratio. However, multiple beams also introduce sidelobes, decreasing the axial resolution and optical sectioning. Axially swept light-sheet microscopy (ASLM) uses a slit to reject the sidelobes. It uses the rolling shutter of the sCMOS, which naturally serves as a slit, to synchronize beam scanning. ASLM can image an arbitrarily large FoV with optimal axial resolution. However, the fluorescence signal outside the rolling shutter will be rejected, so a larger FoV comes at the price of lower photon efficiency.