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A pair of new security threats to Intel-based computer systems have been revealed. The beleaguered semiconductor chip manufacturer has faced a seemingly endless series of vulnerabilities over the past two years.

Although no known attacks have occurred, two teams of researchers have confirmed vulnerabilities in what is supposed to be the safest neighborhood within Intel processor architecture.

One attack, dubbed SGAxe, can gain entry into Intel’s Software Guard eXtensions (SGX) services that were specifically designed to protect critical data in the event of massive assault elsewhere in a system. A hacker theoretically can steal stored in SGX and use them to break protecting sensitive data such as financial records, copyrighted content or passwords.

WASHINGTON — For the second time in less than 18 months, SpaceX has abandoned plans to build a manufacturing facility at the Port of Los Angeles for its next-generation Starship launch vehicle.

In a March 27 letter obtained by SpaceNews, SpaceX notified the Port of Los Angeles that it was terminating a lease approved just a month earlier for a parcel of land at the port. News of the lease termination was first reported by the Los Angeles Times.

The letter, signed by Bret Johnsen, SpaceX’s chief financial officer, served as a 45-day notice of SpaceX’s intent to terminate the lease, making the effective end date of the lease May 11. The letter did not explain why the company was terminating the lease.

As the pandemic’s economic toll grows around the world, some experts fear it could harm science for decades by putting many thousands of researchers out of work and forcing nations to slash funding as they rebuild societies. Others say the pandemic could highlight the importance of science and spur long-term support, especially for basic research, much as the Second World War did.


Financial crises could spell trouble for science budgets but spending could surge in some countries: part 2 in a series on science after the pandemic.

Researchers in Italy have melded the emerging science of convolutional neural networks (CNNs) with deep learning — a discipline within artificial intelligence — to achieve a system of market forecasting with the potential for greater gains and fewer losses than previous attempts to use AI methods to manage stock portfolios. The team, led by Prof. Silvio Barra at the University of Cagliari, published their findings on IEEE/CAA Journal of Automatica Sinica.

The University of Cagliari-based team set out to create an AI-managed “buy and hold” (B&H) strategy — a system of deciding whether to take one of three possible actions — a long action (buying a stock and selling it before the market closes), a short action (selling a stock, then buying it back before the market closes), and a hold (deciding not to invest in a stock that day). At the heart of their proposed system is an automated cycle of analyzing layered images generated from current and past market data. Older B&H systems based their decisions on machine learning, a discipline that leans heavily on predictions based on past performance.

By letting their proposed network analyze current data layered over past data, they are taking market forecasting a step further, allowing for a type of learning that more closely mirrors the intuition of a seasoned investor rather than a robot. Their proposed network can adjust its buy/sell thresholds based on what is happening both in the present moment and the past. Taking into account present-day factors increases the yield over both random guessing and trading algorithms not capable of real-time learning.

The fast and efficient generation of random numbers has long been an important challenge. For centuries, games of chance have relied on the roll of a die, the flip of a coin, or the shuffling of cards to bring some randomness into the proceedings. In the second half of the 20th century, computers started taking over that role, for applications in cryptography, statistics, and artificial intelligence, as well as for various simulations—climatic, epidemiological, financial, and so forth.

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Moderna’s stock price skyrocketed as much as 30% on Monday after the biotech company announced promising early results for its coronavirus vaccine. As ordinary investors piled in, two insiders were quietly heading for the exits.

Moderna’s chief financial officer and chief medical officer executed options and sold nearly $30 million of shares combined on Monday and Tuesday, SEC filings reviewed by CNN Business show.

The sales occurred after Moderna (MRNA) excited Wall Street before markets opened Monday by announcing encouraging vaccine trial results. Moderna’s market value swelled to $29 billion — even though the company has no marketed products.

Various stem cell sources are being explored to treat diabetes since the proof-of-concept for cell therapy was laid down by transplanting cadaveric islets as a part of Edmonton protocol in 2000. Human embryonic stem (hES) cells derived pancreatic progenitors have got US-FDA approval to be used in clinical trials to treat type 1 diabetes mellitus (T1DM). However, these progenitors more closely resemble their foetal counterparts and thus whether they will provide long-term regeneration of adult human pancreas remains to be demonstrated. In addition to lifestyle changes and administration of insulin sensitizers, regeneration of islets from endogenous pancreatic stem cells may benefit T2DM patients. The true identity of pancreatic stem cells, whether these exist or not, whether regeneration involves reduplication of existing islets or ductal epithelial cells transdifferentiate, remains a highly controversial area. We have recently demonstrated that a novel population of very small embryonic-like stem cells (VSELs) is involved during regeneration of adult mouse pancreas after partial-pancreatectomy. VSELs (pluripotent stem cells in adult organs) should be appreciated as an alternative for regenerative medicine as these are autologous (thus immune rejection issues do not exist) with no associated risk of teratoma formation. T2DM is a result of VSELs dysfunction with age and uncontrolled proliferation of VSELs possibly results in pancreatic cancer. Extensive brainstorming and financial support are required to exploit the potential of endogenous VSELs to regenerate the pancreas in a patient with diabetes.

Diabetes is one of the major non-communicable diseases in the world with majority of patients belonging to India, China and USA. Along with associated complications like heart disease and stroke, diabetes results in increased morbidity and mortality and it is expected that by the year 2025, India alone will have more than 70 million diabetics1,2. Diabetes is a metabolic disorder associated with progressive loss or dysfunction of β-cells of pancreas. Onset of type 1 diabetes mellitus (T1DM) occurs when the β-cell mass is reduced to less than 20 per cent due to autoimmune effect, whereas the declining β-cell mass is unable to meet the age-related increased insulin demands of the body in type 2 (T2DM) as a result of insulin resistance and in due course the β-cells are lost by apoptosis. Thus, in both T1 and T2DM, restoration of a functional β-cell mass constitutes the central goal of diabetes therapy.

From navigation to remote banking, mobile device users rely on a variety of applications to streamline daily tasks, communicate, and dramatically increase productivity. While exceedingly useful, the ecosystem of third-party applications utilizes a number of sensors – microphones, GPS, pedometers, cameras – and user interactions to collect data used to enable functionality. Troves of sensitive personal data about users are accessible to these applications and as defense and commercial mobile device users become increasingly reliant on the technology, there are growing concerns around the challenge this creates for preserving user privacy.

Under DARPA’s Brandeis program, a team of researchers led by Two Six Labs and Raytheon BBN Technologies have developed a platform called Privacy Enhancements for Android (PE for Android) to explore more expressive concepts in regulating access to private information on mobile devices. PE for Android seeks to create an extensible privacy system that abstracts away the details of various privacy-preserving technologies, allowing application developers to utilize state-of-the-art privacy techniques, such as secure multi-party computation and differential privacy, without knowledge of their underlying esoteric technologies. Importantly, PE for Android allows mobile device users to take ownership of their private information by presenting them with more intuitive controls and permission enforcement options.

The researchers behind PE for Android today released a white paper detailing the platform’s capabilities and functionality, and published an open source release of its code to GitHub. In open sourcing PE for Android, the researchers aim to make it easier for the open-source Android community and researchers to employ enhanced privacy-preserving technologies within Android apps while also encouraging them to help address the platform’s current limitations and build upon its initial efforts.