A side-by-side comparison shows just how much Boston Dynamics’ bipedal robots improved in 10 years. The progress is astounding.
NASA has selected two cubesat missions to launch as part of the Artemis project to return humans to the moon.
Asia’s richest man announced his intention on Friday to ship 500,000 testing kits and 1 million masks to the U.S. in an effort to combat the coronavirus pandemic.
Jack Ma’s charitable foundation and his China-based company’s foundation, the Alibaba Foundation, have also sourced and donated supplies to other countries being hit by the virus, including Japan, Korea, Italy, Iran and Spain.
THIS!! 100%%!%%
And honestly the biggest one for me: many people with disabilities can work remotely and there should be more roles and opportunities offered to accommodate many mobility issues.
Researchers at the Paul Scherrer Institute PSI have developed a new method to analyse particulate matter more precisely than ever before. Using it, they disproved an established doctrine: that molecules in aerosols undergo no further chemical transformations because they are enclosed in other suspended particulate matter. In the smog chamber at PSI, they analysed chemical compounds directly in aerosols and observed how molecules dissociated and thus released gaseous formic acid into the atmosphere. These findings will help to improve the understanding of global processes involved in cloud formation and air pollution, and to refine the corresponding models. The results of this investigation are published today in the journal Science Advances.
The familiar scent of a pine forest is caused by α-pinene. This is one of the volatile organic compounds in the oils of conifer trees, and it also occurs in eucalyptus and rosemary. The smell triggers pleasant feelings in most people. Less pleasant is that under the influence of radicals, the compound changes into other compounds in the atmosphere, so-called highly oxidised organic molecules. Some of these are reactive and to some extent harmful substances. They have only recently come under scrutiny by atmospheric researchers, and their role in cloud formation is not yet understood.
These highly oxidized organic molecules are less volatile than the starting substance α-pinene and therefore condense easily. Together with dust particles and other solid and liquid substances in the air, they form what we call particulate matter or aerosols.
Simulating computationally complex many-body problems on a quantum simulator has great potential to deliver insights into physical, chemical and biological systems. Physicists had previously implemented Hamiltonian dynamics but the problem of initiating quantum simulators to a suitable quantum state remains unsolved. In a new report on Science Advances, Meghana Raghunandan and a research team at the institute for theoretical physics, QUEST institute and the Institute for quantum optics in Germany demonstrated a new approach. While the initialization protocol developed in the work was largely independent of the physical realization of the simulation device, the team provided an example of implementing a trapped ion quantum simulator.
Quantum simulation is an emergent technology aimed at solving important open problems relative to high-temperature superconductivity, interacting quantum field theories or many-body localization. A series of experiments have already demonstrated the successful implementation of Hamiltonian dynamics within a quantum simulator—however, the approach can become challenging across quantum phase transitions. In the new strategy, Raghunandan et al. overcame this problem by building on recent advances in the use of dissipative quantum systems to engineer interesting many-body states.
Almost all many-body Hamiltonians of interest remain outside a previously investigated class and therefore require generalization of the dissipative state preparation procedure. The research team therefore presented a previously unexplored paradigm for the dissipative initialization of a quantum simulator by coupling the many-body system performing the quantum simulation to a dissipatively driven auxiliary particle. They chose the energy splitting within the auxiliary particle to become resonant with the many-body excitation gap of the system of interest; described as the difference of the ground-state energy and the energy of the first excited state. During such conditions of resonance, the energy of the quantum simulator could be transferred efficiently to the auxiliary particle for the former to be cooled sympathetically, i.e., particles of one type, cooled particles of another type.
Our current, well-established understanding of phases of matter primarily relates to systems that are at or near thermal equilibrium. However, there is a rich world of systems that are not in a state of equilibrium, which could host new and fascinating phases of matter.
Recently, studies focusing on systems outside of thermal equilibrium have led to the discovery of new phases in periodically driven quantum systems, the most well-known of which is the discrete time crystal (DTC) phase. This unique phase is characterized by collective subharmonic oscillations arising from the interplay between many-body interactions and non-equilibrium driving, which leads to a loss of ergodicity.
Interestingly, subharmonic oscillations are also known to be a characteristic of dynamical systems, such as predator-prey models and parametric resonances. Some researchers have thus been exploring the possibility that these classical systems may exhibit similar features to those observed in the DTC phase.
Over the past decade or so, researchers worldwide have developed increasingly advanced techniques to enable robot navigation in a variety of environments, including on land, in the air, underwater or on particularly rough terrains. To be effective, these techniques should allow robots to move around in their surroundings both safely and efficiently, saving as much energy as possible.
Researchers at the Indian Institute of Technology Kharagpur in India have recently developed a new approach to achieve efficient path planning in mobile robots. Their method, presented in a paper published in Springer Link’s Nature-Inspired Computation in Navigation and Routine Problems, is based on the use of a flower pollination algorithm (FPA), a soft computing-based tool that can identify ideal solutions to a given problem by considering a number of factors and criteria.
“Flower pollination algorithms (FPAs) have shown their potential in various engineering fields,” Atul Mishra, one of the researchers who carried out the study, told TechXplore. “In our study, we used the algorithm to solve the problem of path planning for mobile robots. Our prime objective was to plan, in the least time possible, the most optimal path in terms of minimum path length and energy consumption, with maximum safety.”
A Washington State University research team has found that nanoscale particles of the most commonly used plastics tend to move through the water supply, especially in fresh water, or settle out in wastewater treatment plants, where they end up as sludge, in landfills, and often as fertilizer.
Neither scenario is good.
“We are drinking lots of plastics,” said Indranil Chowdhury, an assistant professor in WSU’s Department of Civil and Environmental Engineering, who led the research. “We are drinking almost a few grams of plastics every month or so. That is concerning because you don’t know what will happen after 20 years.”
