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The number of electric vehicles (EVs) exported from Germany rose sharply in 2023, meaning that EVs accounted for about one quarter of all car exports that year, the country’s statistical office Destatis has said.

The country exported about 786,000 fully electric cars for a total value of roughly €36 billion ($A61.8 billion) – an increase of 58 per cent compared to 2022.

The most important destinations for EVs produced in Germany were the Netherlands, the UK and Belgium, Destatis added. Imports of EVs to Germany climbed about 23 percent to 446,000 units, with more than a quarter coming from China.

Warren Buffett addressed Tesla’s Full Self-Driving over the weekend.

Neurons are important, but they are not everything. Indeed, it is “cartilage,” in the form of clusters of extracellular matrix molecules called chondroitin sulfates, located in the outside nerve cells, that plays a crucial role in the brain’s ability to acquire and store information.

Citri, A., Malenka, R. Synaptic Plasticity: Multiple Forms, Functions, and Mechanisms. Neuropsychopharmacol 33, 18–41 (2008). https://doi.org/10.1038/sj.npp.

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Some problems of the very intuitive evolutionary emergentist paradigm trying to explain consciousness from neurons, thanks to Andrés Gómez Emilsson and Chris Percy at Qualia Research Institute:

The “Slicing Problem” is a thought experiment that raises questions for substrate-neutral computational theories of consciousness, particularly, in functionalist approaches.

The thought experiment uses water-based logic gates to construct a computer in a way that permits cleanly slicing each gate and connection in half, creating two identical computers each instantiating the same computation. The slicing can be reversed and repeated via an on/off switch, without changing the amount of matter in the system.

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Most currently used quantum neural network architectures have little-to-no inductive biases, leading to trainability and generalization issues. Inspired by a similar problem, recent breakthroughs in classical machine learning address this crux by creating models encoding the symmetries of the learning task. This is materialized through the usage of equivariant neural networks whose action commutes with that of the symmetry.

In this work, we import these ideas to the quantum realm by presenting a general theoretical framework to understand, classify, design, and implement equivariant quantum neural networks. As a special implementation, we show how standard quantum convolutional neural networks (QCNN) can be generalized to group-equivariant QCNNs where both the convolutional and pooling layers are equivariant under the relevant symmetry group.

Ever since superconductivity was discovered in the early 1900s, it has both captivated and mystified scientists. Superconductors conduct electricity with virtually zero resistance, allowing for highly efficient transmission of electrical currents. Among other uses, they create the strong magnetic fields we depend on for medical imaging with MRI machines.

The first known superconductor, mercury, only works when the temperature dips just below-450 F. Copper-containing materials called cuprates were found in the ’80s to become superconductors at warmer temperatures, though still inconveniently cold — closer to-200 F. Understanding how these so-called high-temperature superconductors work could eventually lead to ones that can operate in less frigid conditions.

One potential hallmark of high-temperature superconductors has remained purely theoretical, until now. A team of scientists, including several from the U.S. Department of Energy’s (DOE) Argonne National Laboratory, has observed an elusive state of matter called quantum spin nematic. The study, which was published in the journal Nature (“Quantum spin nematic phase in a square-lattice iridate”), used the Advanced Photon Source (APS), a DOE Office of Science user facility at Argonne that also happens to use superconductors. The results lend insight on both high-temperature superconductivity and some of the physics involved in quantum computing.

Dementia has become rampant among human beings who are pushed into a deep mental abyss, devoid of memories and remembrance.

It has been termed as “the long goodbye”. Even though the person remains alive, memories fade away slowly and irreversibly due to dementia.

Dementia eventually snatches away the ability of a person to communicate, eat and drink on their own, recognise family members and understand where they are.