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Although Bayesian Optimization (BO) has been employed for accelerating materials design in computational materials engineering, existing works are restricted to problems with quantitative variables. However, real designs of materials systems involve both qualitative and quantitative design variables representing material compositions, microstructure morphology, and processing conditions. For mixed-variable problems, existing Bayesian Optimization (BO) approaches represent qualitative factors by dummy variables first and then fit a standard Gaussian process (GP) model with numerical variables as the surrogate model. This approach is restrictive theoretically and fails to capture complex correlations between qualitative levels. We present in this paper the integration of a novel latent-variable (LV) approach for mixed-variable GP modeling with the BO framework for materials design. LVGP is a fundamentally different approach that maps qualitative design variables to underlying numerical LV in GP, which has strong physical justification. It provides flexible parameterization and representation of qualitative factors and shows superior modeling accuracy compared to the existing methods. We demonstrate our approach through testing with numerical examples and materials design examples. It is found that in all test examples the mapped LVs provide intuitive visualization and substantial insight into the nature and effects of the qualitative factors. Though materials designs are used as examples, the method presented is generic and can be utilized for other mixed variable design optimization problems that involve expensive physics-based simulations.

In the future, patients may no longer need to have a tube fed down their throat into their stomach. Instead they could simply swallow an ingestible device in the form of a pill. Engineers at Massachusetts Institute of Technology (MIT) have invented exactly this. It's made from a jelly-like substance: a combination of water and polymers. Inspired by the pufferfish, the team of researchers realised that in order for any edible pill to remain in the stomach once it has passed down the oesophagus, and not then pass out through the pylorus, it needed to be inflated.

Waste management is one of the world's most pressing issues, however Peruza and Dots, two Latvian companies, have created a prototype through the use of AI to increase the efficiency of plastic waste. Peruza, an equipment manufacturing and process engineering company, has collaborated with Dots, a technology company also based in Latvia, to create a prototype system which is able to recognize and collects various types of packaging materials in an effort to contribute to the EU's upcoming single plastic directive. Peruza had stated that 10 countries within Europe have already implemented deposit return schemes and that we should expect more to come in the future. This is in line with the EU's goal for 2030 for all packaging used in the market to be recyclable or reusable. Robert Dlohi, CEO of Peruza, stated, "The problem of existing devices is that they can collect individual types of packaging. They use a barcode for recognition. Our system can currently recognize, collect and sort 5.0 liter and/or 1.5 liter Pet bottles, and 5 liter plastic bottles, 1.5 liter plastic canisters, as well as aluminum cans, cardboard Tetra Pak, glass bottles and jars."

Mining companies from around the world have begun using artificial intelligence in their operations. From safety and maintenance, to exploration and autonomous vehicles, and drills, AI is being used to navigate efficiencies and speed. With this new technology, however, comes an ever-growing need for a workforce who can navigate these new systems. Thanks to a $1.25 million grant from the National Institute for Occupational Safety and Health, an interdisciplinary team at the University of Nevada, Reno, has committed to graduating six doctoral and four master's degree students who will address several challenges related to major safety and health issues in mining operations. "Future mine engineers need to understand emerging technology like AI, drones and big data," Javad Sattarvand, University College of Science assistant professor of mining engineering and the project's principal investigator, said.

Over the past few decades, the mining industry has been mired in a productivity slump of sorts. On the whole, production efficiency is down and costs are up. Mining companies have naturally looked for ways to turn this around, and digitalization has been one of the chief approaches these companies have followed. Mining companies have a lot of data at their disposal. Sensors are seemingly everywhere in their underground operations. But thus far it has been very hard for mining companies to capitalize on all their data because of the difficulty in making sense of it all.

Dr. Benji Maruyama is a Principal Materials Research Engineer in the Air Force Research Laboratory, Materials & Manufacturing Directorate. He is the Leader of the Flexible Materials and Processes Research Team, and leads research on the synthesis and processing science of carbon nanotubes. Dr. Maruyama created and is developing a new method research: Autonomous Research Systems for Materials Development. He is also the point of contact for carbon materials for the Materials and Manufacturing Directorate. His background and interests include carbon nanomaterials, energy storage, field emission, carbon, polymer and metal matrix composites, imaging of complex 3D microstructures and combinatorial experimentation.

Just like the air people breathe, some of the most important things in life are invisible. Now, can you imagine your company's supply chain becoming just as invisible as the air around us? We envision the supply chain of the future in the chemical industry will be self-driving, self-maneuvering and self-correcting, resulting in a seamless fulfillment capability that delivers chemicals at the right time, to the right place and with right quality--without manual human interaction. While leading retail giants invest in emerging technologies as a matter of course, historically this has not been the case for most chemical companies. However, the benefits of doing so are tremendous.

In May of last year, after a 13-month slumber, the ground beneath Washington's Puget Sound rumbled to life. The quake began more than 20 miles below the Olympic mountains and, over the course of a few weeks, drifted northwest, reaching Canada's Vancouver Island. It then briefly reversed course, migrating back across the US border before going silent again. All told, the monthlong earthquake likely released enough energy to register as a magnitude 6. By the time it was done, the southern tip of Vancouver Island had been thrust a centimeter or so closer to the Pacific Ocean.

A detailed study accumulated to offer Latest insights about acute features of the LegalTech Artificial Intelligence market. The report contains different market predictions related to market size, revenue, production, CAGR, Consumption, gross margin, price, and other substantial factors. The report also offers a complete study of the future trends and developments of the market. It also examines the role of the leading market players involved in the industry including their corporate overview, financial summary and SWOT analysis. Legal technology, also known as Legal Tech, refers to the use of technology and software to provide legal services.