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The algorithms spot and classify synthetic-material objects based on the distinctive manner in which they reflect polarized light. Polarized light reflected from human-made objects often differs from natural objects, such as vegetation, soil, and rocks.

The researchers tested such a camera, both on the ground and from a US Coast Guard helicopter, which was flying at the altitude at which the polarimetric-camera-equipped drones will fly.

Once fully operational, data collected by the drone-based machine learning system will be used to make maps that show where marine debris is concentrated along the coast to guide rapid response and removal efforts. The researchers will provide NOAA Marine Debris Program staff with training in the use of the new system, along with standard operating procedures manual.

Farmers struggling to adapt to rising temperatures in tropical regions can unleash the benefits of natural cooling, alongside a host of other wins, simply by dotting more trees across their pasturelands. For the first time, a study led by the University of Washington puts tangible numbers to the cooling effects of this practice.

Researchers at the UW and The Nature Conservancy, along with Duke University, the University of California San Diego and Stony Brook University Hospital, find that adding trees to pastureland, technically known as silvopasture, can cool local temperatures by up to 2.4 C (4.3 F) for every 10 metric tons of woody material added per hectare (about 4 tons per acre) depending on the density of trees, while also delivering a range of other benefits for humans and wildlife.

The paper was published Feb. 4 in Nature Communications.

Quantum computing and machine learning are two of the most exciting technologies that can transform businesses. We can only imagine how powerful it can be if we can combine the power of both of these technologies. When we can integrate quantum algorithms in programs based on machine learning, that is called quantum machine learning. This fascinating area has been a major area of tech firms, and they have brought out tools and platforms to deploy such algorithms effectively. Some of these include TensorFlow Quantum from Google, Quantum Machine Learning (QML) library from Microsoft, QC Ware Forge built on Amazon Braket, etc.

Students skilled in working with quantum machine learning algorithms can be in great demand due to the opportunities the field holds. Let us have a look at a few online courses one can use to learn quantum machine learning.

In this course, the students will start with quantum computing and quantum machine learning basics. The course will also cover topics on building Qnodes and Customised Templates. It also teaches students to calculate Autograd and Loss Function with quantum computing using Pennylane and to develop with the Pennylane.ai API. The students will also learn how to build their own Pennylane Plugin and turn Quantum Nodes into Tensorflow Keras Layers.

Could a laser send a spacecraft to Mars? That’s a proposed mission from a group at McGill University, designed to meet a solicitation from NASA. The laser, a 10-meter wide array on Earth, would heat hydrogen plasma in a chamber behind the spacecraft, producing thrust from hydrogen gas and sending it to Mars in only 45 days. There, it would aerobrake in Mars’ atmosphere, shuttling supplies to human colonists or, someday perhaps, even humans themselves.

Transistors based on semiconductor materials are widely used electronic components with many remarkable properties. For instance, they have a nonreciprocal electrical response, which means that they can isolate two parts of a circuit in such a way that one of the parts (the input section) can influence the other part (the output section), but not the other way around. In addition, transistors can amplify voltage signals, and thereby can supply energy to a system. Non-energy conserving interactions are usually referred to as “non-Hermitian.”

Researchers from Instituto de Telecomunicações at the University of Coimbra and University of Lisbon have recently introduced a new class of bulk materials that draws inspiration from the non-reciprocal and non-Hermitian responses of conventional semiconductor-based transistors. They presented these transistor-like three-dimensional (3D) bulk metamaterials in a paper published in Physical Review Letters.

Mário Silveirinha, one of the researchers who carried out the study, told Phys.org, “The ideas developed in our paper were mostly driven by the question: Would it be possible to somehow imitate the response of standard transistors in a bulk metamaterial? We were intrigued if it would be feasible to have a bulk material which, when suitably biased, could manipulate electromagnetic waves in the same way as a transistor manipulates a voltage signal.”

Can you crumple up two sheets of paper the exact same way? Probably not—the very flexibility that lets flexible structures from paper to biopolymers and membranes undergo many types of large deformations makes them notoriously difficult to control. Researchers from the Georgia Institute of Technology, Universiteit van Amsterdam, and Universiteit Leiden have shed new light on this fundamental challenge, demonstrating that new physical theories provide precise predictions of the deformations of certain structures, as recently published in Nature Communications.

In the paper, Michael Czajkowski and D. Zeb Rocklin from Georgia Tech, Corentin Coulais from Universiteit van Amsterdam, and Martin van Hecke of AMOLF and Universiteit Leiden approach a highly studied exotic elastic material, uncover an intuitive geometrical description of the pronounced—or nonlinear—soft deformations, and show how to activate any of these deformations on-demand with minimal inputs. This new theory reveals that a flexible mechanical structure is governed by some of the same math as electromagnetic waves, phase transitions, and even black holes.

“So many other systems struggle with how to be strong and solid in some ways but flexible and compliant in others, from the human body and micro-organisms to clothing and industrial robots,” said Rocklin. “These structures solve that problem in an incredibly elegant way that permits a single folding mechanism to generate a wide family of deformations. We’ve shown that a single folding mode can transform a structure into an infinite family of shapes.”

One year after winter storms crippled Texas’s electricity grid, contributing to more than 200 deaths, a Cornell University-led analysis recommends contracting improvements to reduce decentralized energy markets’ vulnerability to rare events.

Such “energy-only” markets rely on investors to anticipate demand for all conditions and build appropriate resiliency into the system. They allow prices to soar during extreme events to incentivize preparedness.

But in Texas, where Winter Storm Uri caused catastrophic blackouts over five consecutive days of frigid temperatures, the crisis revealed the market’s failure to manage risk as designed, says Jacob Mays, assistant professor in the School of Civil and Environmental Engineering at Cornell. Winterization investment fell short, he said, because the payoff proved too distant and uncertain.

Researchers at École Polytechnique Fédérale de Lausanne (EPFL) and the Hitachi Cambridge Laboratory have recently designed an integrated circuit (IC) that integrates silicon quantum dots with conventional readout electronics. This chip, introduced in a paper published in Nature Electronics, is based on a 40-nm cryogenic complementary metal-oxide semiconductor (CMOS) technology that is readily and commercially available.

“Our recent paper builds on the expertise of the two groups involved,” Andrea Ruffino, one of the researchers at EPFL who carried out the study, told TechXplore. “The goal of our group was to build cryogenic (Bi)CMOS integrated circuits for readout and control of quantum computers, to be co-packaged or co-integrated in the final stage with silicon quantum processors. On the other hand, the team at the Hitachi Cambridge Laboratory have been studying silicon quantum devices for many years.”

Ruffino and his colleagues at EPFL joined forces with the team at the Hitachi Cambridge Laboratory with the common goal of uniting classical circuits and quantum devices on a single chip. Their paper builds on some of their previous efforts, including the proposal of cryogenic CMOS ICs for quantum computing, as well as the realization of fast-sensing and time-multiplexed sensing of silicon quantum devices.

Malware families are making use of PrivateLoader’s pay-per-install service in order to expand their victim list.

A detailed examination of a Pay-per-install (PPI) malware service called PrivateLoader has revealed its crucial role in the delivery of a variety of malware such as SmokeLoader, RedLine Stealer, Vidar, Raccoon, and GCleaner since at least May 2021.