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A transition to a carbon-free economy is the reality of the modern energy industry. Reduction in CO2 emission is one of the main challenge in energy engineering in the last decades. Renewable energy sources are playing an important role on the way to a zero-carbon economy [1,2]. Solar energy is one of the main and almost unlimited energy sources in the World. The different technologies of solar energy use have been developed in the last years [[3], [4], [5], [6], [7], [8]]. However, even though the progress in the development of solar energy technologies is notable, there are a lot of challenges for energy science. One of them is the fact that more than 60% of electricity is produced by conventional technologies via hydrocarbon fuel combustion: steam turbines, gas turbines, etc. While the share of electricity produced by using solar energy is no more than a few percent [9].

Among various ways of utilization of solar energy for electricity generation, a combination of solar energy with the traditional steam and gas turbine cycles can be highlighted. The power plants where solar energy is combined with conventional power cycles are named integrated solar combined cycle systems (ISCCS). In these systems, solar energy is used to produce heat and after that heat is used to generate mechanical work or electricity.

Combined cycle power plants (CCPP) show one of the highest energy efficiency among conventional power plants [10]. The modern cycles with high-temperature gas turbines have an efficiency up to 70% and even higher. In such cycles, the high-temperature gas turbines with the turbine inlet temperature (TIT) up to 1,600 °C are applied [11,12]. In the last years, a lot of various integrated solar combined cycle systems (ISCCS) were developed by various scientists and engineers. The main way to use solar energy in such cycles is a steam generation in CCPP [[13], [14], [15], [16]]. In other words, solar energy in such ISCCS is utilized as an energy source in a steam turbine cycle.

As per the company, traditional rovers may not be able to traverse everywhere and perform tasks like their drone-like hopper.

For decades, Earth’s natural satellite has been one of the most popular destinations for space exploration. The upcoming Artemis missions, along with the excitement on establishing a human settlement on the Moon, have collectively boosted the lunar economy market substantially in recent years.

Several startups have been preparing to offer their technological solutions to gain a better understanding of the valuable resources available and provide services to future astronauts.

The researchers suggest that a pervasive design perspective is driving the development of AI with increasingly human-like features. While this may be appealing in some contexts, it can also be problematic, particularly when it is unclear who you are communicating with. Ivarsson questions whether AI should have such human-like voices, as they create a sense of intimacy and lead people to form impressions based on the voice alone.

In the case of the would-be fraudster calling the “older man,” the scam is only exposed after a long time, which Lindwall and Ivarsson attribute to the believability of the human voice and the assumption that the confused behavior is due to age. Once an AI has a voice, we infer attributes such as gender, age, and socio-economic background, making it harder to identify that we are interacting with a computer.

The researchers propose creating AI with well-functioning and eloquent voices that are still clearly synthetic, increasing transparency.

In 2010 Prof. Shlomo Havlin and collaborators published an article in the journal Nature proposing that the abrupt electricity failure causing the famous 2003 Italy blackout was a consequence of the inter-dependency of two networks. According to Havlin’s theory the dependency between the power network and its communication system led to cascading failures and abrupt collapse. Havlin’s seminal work ignited a new field in statistical physics known as “network of networks” or “interdependent networks” and paved the way for understanding and predicting the effects of the interaction between networks.

The main novelty of Havlin’s model is the existence of two types of links that represent two qualitatively different kinds of interactions. Within networks, links between nodes describe connectivity such as or communication connections. Between networks, on the other hand, links describe dependency relationships in which the functionality of a node in one network depends on the functionality of a node in the other. The communication hubs need electricity and the electric power stations depend on communication control. This dependency leads to a cascading effect in which failure of a single node in one of the networks could lead to an abrupt breakdown of both networks.

Over the past decade or so since, Havlin, from the Department of Physics at Bar-Ilan University in Israel, and others have applied this concept to a variety of abstract systems, such as the internet, road traffic, the economy, infrastructure, and more. But being a theorist, Havlin was unable to manifest the hypothesis on real experimental physical systems and thus the theory couldn’t be confirmed in controlled experiments, nor could it be implemented for device-type applications.

At its I/O developer conference, the search giant needs to rethink its AI strategy if it wants to catch Microsoft. The missing element? Experimentation.

Google has had a rough six months. Since ChatGPT launched last November — followed by the new Bing in February and GPT-4 in March — the company has failed to establish its AI credentials. Its own offering, the “experimental” chatbot Bard, compares poorly to rivals, and insider reports have portrayed a company in panic and disarray. Today, at its annual I/O conference, the company needs to convince the public (and shareholders) that it has a meaningful response. But to do that, it needs a new playbook.


AI outputs are increasingly defining the cultural moment — just not Google’s.

TerraPower, founded by billionaire and Microsoft co-founder Bill Gates in 2008, is opening a new nuclear power plant in Kemmerer, Wyoming. The plant will be the first of its kind, with the company hoping to revolutionize the nuclear energy industry in the U.S. to help fight climate change and support American energy independence.

“Nuclear energy, if we do it right, will help us solve our climate goals,” Gates told ABC News. “That is, get rid of the greenhouse gas emissions without making the electricity system far more expensive or less reliable.”

Gates met with ABC News’ chief business, economics, and technology correspondent Rebecca Jarvis in Kemmerer to talk about the project.

With all the controversy surrounding AI art, I’m surprised that NVIDIA is so rarely discussed. Unlike other AI art technologies, NVIDIA facilitates drawing landscapes in an interactive fashion. You sketch out rough blobs and then the AI converts your shapes into rocks, grasses, dirt, trees, and other selectable material types. I think that this kind of tool deserves much more attention since it empowers human artists to create with AI as a partner and gives us more creative control over the final result. Sure, NVIDIA itself is somewhat limited, but the principle of it is very compelling and I can easily envision people developing lots of improved versions that can draw more than just landscapes. I think it is surprising that this kind of approach has not caught on, but perhaps there are economic reasons that I’m not aware of which explain the relative lack of interactive AI art tools.


Use AI to Create Backgrounds Quickly, or Speed up your Concept Exploration.

Advancing Nuclear Energy Science And Technology For U.S. Energy, Environmental And Economic Needs — Dr. Katy Huff, Ph.D. — Assistant Secretary, U.S. Department of Energy Office of Nuclear Energy, U.S. Department of Energy.


Dr. Kathryn Huff, Ph.D. (https://www.energy.gov/ne/person/dr-kathryn-huff) is Assistant Secretary, Office of Nuclear Energy, U.S. Department of Energy, where she leads their strategic mission to advance nuclear energy science and technology to meet U.S. energy, environmental, and economic needs, both realizing the potential of advanced technology, and leveraging the unique role of the government in spurring innovation.

Prior to her current role, Dr. Huff served as a Senior Advisor in the Office of the Secretary and also led the office as the Principal Deputy Assistant Secretary for Nuclear Energy.

Before joining the Department of Energy, Dr. Huff was an Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign where she led the Advanced Reactors and Fuel Cycles Research Group. She was also a Blue Waters Assistant Professor with the National Center for Supercomputing Applications.

Dr. Huff was previously a Postdoctoral Fellow in both the Nuclear Science and Security Consortium and the Berkeley Institute for Data Science at the University of California — Berkeley. She received her PhD in Nuclear Engineering from the University of Wisconsin-Madison and her undergraduate degree in Physics from the University of Chicago. Her research focused on modeling and simulation of advanced nuclear reactors and fuel cycles.

Accelerating Breakthroughs in Critical and Emerging Technologies — Dr. Erwin Gianchandani, Ph.D. — Assistant Director for Technology, Innovation and Partnerships, U.S. National Science Foundation (NSF)


Dr. Erwin Gianchandani, Ph.D. is Assistant Director for Technology, Innovation and Partnerships, U.S. National Science Foundation, leading the newly established TIP Directorate (https://new.nsf.gov/tip/leadership).

The TIP Directorate is focused on harnessing the nation’s vast and diverse talent pool to advance critical and emerging technologies, addressing pressing societal and economic challenges, and accelerating the translation of research results from lab to market and society, ultimately improving U.S. competitiveness, growing the U.S. economy and training a diverse workforce for future, high-wage jobs.

Prior to becoming the Assistant Director for TIP, Dr. Gianchandani served as the senior advisor for Translation, Innovation and Partnerships, where he helped develop plans for the new TIP Directorate in collaboration with colleagues at NSF, other government agencies, industry, and academia.

During the previous six years, Dr. Gianchandani was the NSF deputy assistant director for Computer and Information Science and Engineering (CISE), twice serving as acting assistant director. His leadership and management of CISE included the formulation and implementation of the directorate’s $1 billion annual budget, strategic and human capital planning, and oversight of day-to-day operations for a team of over 130.