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(2021). Nuclear Technology: Vol. 207 No. 8 pp. 1163–1181.


Focusing on nuclear engineering applications, the nation’s leading cybersecurity programs are focused on developing digital solutions to support reactor control for both on-site and remote operation. Many of the advanced reactor technologies currently under development by the nuclear industry, such as small modular reactors, microreactors, etc., require secure architectures for instrumentation, control, modeling, and simulation in order to meet their goals. 1 Thus, there is a strong need to develop communication solutions to enable secure function of advanced control strategies and to allow for an expanded use of data for operational decision making. This is important not only to avoid malicious attack scenarios focused on inflicting physical damage but also covert attacks designed to introduce minor process manipulation for economic gain. 2

These high-level goals necessitate many important functionalities, e.g., developing measures of trustworthiness of the code and simulation results against unauthorized access; developing measures of scientific confidence in the simulation results by carefully propagating and identifying dominant sources of uncertainties and by early detection of software crashes; and developing strategies to minimize the computational resources in terms of memory usage, storage requirements, and CPU time. By introducing these functionalities, the computers are subservient to the programmers. The existing predictive modeling philosophy has generally been reliant on the ability of the programmer to detect intrusion via specific instructions to tell the computer how to detect intrusion, keep log files to track code changes, limit access via perimeter defenses to ensure no unauthorized access, etc.

The last decade has witnessed a huge and impressive development of artificial intelligence (AI) algorithms in many scientific disciplines, which have promoted many computational scientists to explore how they can be embedded into predictive modeling applications. The reality, however, is that AI, premised since its inception on emulating human intelligence, is still very far from realizing its goal. Any human-emulating intelligence must be able to achieve two key tasks: the ability to store experiences and the ability to recall and process these experiences at will. Many of the existing AI advances have primarily focused on the latter goal and have accomplished efficient and intelligent data processing. Researchers on adversarial AI have shown over the past decade that any AI technique could be misled if presented with the wrong data. 3 Hence, this paper focuses on introducing a novel predictive paradigm, referred to as covert cognizance, or C2 for short, designed to enable predictive models to develop a secure incorruptible memory of their execution, representing the first key requirement for a human-emulating intelligence. This memory, or self-cognizance, is key for a predictive model to be effective and resilient in both adversarial and nonadversarial settings. In our context, “memory” does not imply the dynamic or static memory allocated for a software execution; instead, it is a collective record of all its execution characteristics, including run-time information, the output generated in each run, the local variables rendered by each subroutine, etc.

This post is a collaboration with Dr. Augustine Fou, a seasoned digital marketer, who helps marketers audit their campaigns for ad fraud and provides alternative performance optimization solutions; and Jodi Masters-Gonzales, Research Director at Beacon Trust Network and a doctoral student in Pepperdine University’s Global Leadership and Change program, where her research intersects at data privacy & ethics, public policy, and the digital economy.

The ad industry has gone through a massive transformation since the advent of digital. This is a multi-billion dollar industry that started out as a way for businesses to bring more market visibility to products and services more effectively, while evolving features that would allow advertisers to garner valuable insights about their customers and prospects. Fast-forward 20 years later and the promise of better ad performance and delivery of the right customers, has also created and enabled a rampant environment of massive data sharing, more invasive personal targeting and higher incidences of consumer manipulation than ever before. It has evolved over time, underneath the noses of business and industry, with benefits realized by a relative few. How did we get here? More importantly, can we curb the path of a burgeoning industry to truly protect people’s data rights?

There was a time when advertising inventory was finite. Long before digital, buying impressions was primarily done through offline publications, television and radio. Premium slots commanded higher CPM (cost per thousand) rates to obtain the most coveted consumer attention. The big advertisers with the deepest pockets largely benefitted from this space by commanding the largest reach.

Huge thanks to:
Blue Origin: https://www.youtube.com/c/blueoriginchannel/featured.
Everyday Astronaut: https://www.youtube.com/c/EverydayAstronaut.
ULA: https://www.youtube.com/channel/UCnrGPRKAg1PgvuSHrRIl3jg.
Lab Padre: https://www.youtube.com/channel/UCFwMITSkc1Fms6PoJoh1OUQ
NASA: https://www.youtube.com/c/NASA/featured.
Evan Karen: https://www.youtube.com/channel/UCDN1X8Fz1oAXX-rBcOWjzmg.
Ocean Cam: https://www.youtube.com/channel/UCF8IYFF60clbbznjvJ7qoTQ

Source of thumb:
Blue Origin: https://twitter.com/blueorigin.
Alexander Svan: https://twitter.com/AlexSvanArt.
Izan Ramos: https://twitter.com/IzanRamos2002
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Our video content is referenced by video sources at these sites:
https://en.wikipedia.org.
https://twitter.com.
https://arstechnica.com.
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Raptor and BE4SpaceX and Blue Origin have been competing with each other for many space crafts and commercial contracts. We have also talked about their rivalry many times but today is all about their engines that fire up the massive rockets both the companies are developing. SpaceX, the leading space company has made many rocket engines since its launch in 2002. A few months ago, SpaceX completed its 100th Raptor Engine. This extraordinary milestone was achieved in just 29 months. Blue Origin’s rocket engines game started work on the BE-4 in 2011. Importantly, they said the “BE-4 would be ‘ready for flight’ by 2017″, but at this moment Blue Origin’s powerful BE-4 engine is more than four years late. The first flight test of the new engine is now expected no earlier than 2022 on the Vulcan rocket. This is a big problem and we need to talk about that.
So, How did Blue Origin’s BE-4 turn into a joke whereas SpaceX’s Raptor is the leading example?
Let’s find out:
Firstly, how has BE-4 gone through almost a decade of failure?
This was their first engine to combust liquid oxygen and liquified natural gas propellants. It was initially planned for the engine to be used exclusively on a Blue Origin proprietary launch vehicle New Glenn, the company’s first orbital rocket. However, it was announced in 2014 that the engine would also be used on the United Launch Alliance (ULA) Vulcan Centaur launch vehicle, the successor to the Atlas V launch vehicle. This was labeled “a stunner” choice. The company planned to begin full-scale engine testing in late 2016 and expected to complete the development of the engine in 2017.However, the first engine was not fully assembled until March 2017. Also, in March, United Launch Alliance indicated that the economic risk of the Blue Origin engine selection option had been retired, but that the technical risk on the project would remain until a series of engine firing tests were completed later in 2017. A test anomaly occurred on 13 May 2017 and Blue Origin reported that they lost a set of powerpack hardware.
SpaceX’s Raptor Engines completely HUMILIATED Blue Origin BE-4 Engines!!

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Arm is releasing new chip design offerings in the internet of things (IoT), virtual hardware, and 5G sectors.

Cambridge, United Kingdom-based Arm designs the architecture that other licensed chip makers use to build their chips. Arm likes to make it easier for those licensees to come up with their applications and create a foundation for an IoT economy.

So the company said its Arm Total Solutions for IoT now delivers a full-stack solution to significantly accelerate the development and return-on-investment for IoT chip products. And Arm Virtual Hardware removes the need to develop on physical silicon, enabling software and hardware co-design and accelerating product design by up to two years, the company claimed.

The 24th Annual International Mars Society Convention is a 4-day event that brings together leading scientists, engineers, aerospace industry representatives, government policymakers and journalists to talk about the latest scientific discoveries, technological advances and political-economic developments that could help pave the way for a human mission to the planet Mars.

Cryptocurrency is viewed positively by some investors as a means of eradicating economic disparity. Authorities worldwide are debating how to manage the disruption it may bring. Tesla and SpaceX creator Elon Musk advised governments against attempting to “destroy” them. However, he agreed that they can halt its progress.

Similar to the relationship between an engine and oil, data and artificial intelligence (AI) are symbiotic. Data fuels AI, and AI helps us to understand the data available to us. Data and AI are two of the biggest topics in technology in recent years, as both work together to shape our lives on a daily basis…

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When this happens, it’s usually because the owner only shared it with a small group of people, changed who can see it or it’s been deleted.

The technical potential could rise to ‘nearly 150 PW-hr by 2060′.

The best way to incentivize sustainable energy is to make it affordable.

And the sharp drop in the price of photovoltaic systems has made solar capable of rivaling coal power in China, according to an analysis from researchers published in the journal Proceedings of the National Academy of Sciences of the United States of America.

However, as solar power comes to encompass a greater slice of a national economy’s power grid, it becomes harder to achieve a sustainable balance against the fact that solar can only generate power intermittently, potentially exacerbating energy management challenges.

Full Story:

China could soon outlaw all the news media outlets that are not directly funded by the Communist Party. China’s top economic planner has unveiled a new proposal that would bar private investment in news-related entities. China says that it is proposing to ban private investments to control “unlawful news media-related businesses”. Beijing is preparing to exercise greater control over the news industry, which is already heavily regulated. The current crackdown comes in the midst of a campaign by Xi Jinping to limit the power of private businesses.
#ChinaMediaBan #ChinaCrackdown #Xijinping.

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Daily exposure to chemicals called phthalates, which are used in the manufacture of plastic food containers and many cosmetics, may lead to roughly 100,000 premature deaths among older Americans each year, a new study shows. The resulting annual economic burden is between $40 billion and $47 billion, a value more than quadruple that of previous estimates.


NYU Langone study shows deaths linked to endocrine-disrupting chemicals called phthalates may cost United States billions in lost productivity. Learn more.