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People with Alzheimer’s disease may retain their ability to empathize, despite declines in other social abilities, finds a new study led by University College London (UCL) researchers.

The researchers found that people with Alzheimer’s disease scored slightly higher on a measure of empathy than peers of the same age with mild cognitive impairment, despite scoring worse on other measures of such as recognizing facial emotions and understanding the thoughts of others.

The authors of the study, published in Alzheimer’s & Dementia, say this may be the first time a cognitive domain has been found to improve in dementia.

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1 State Key Laboratory of Systems Medicine for Cancer, Renji-Med-X Stem Cell Research Center, Department of Urology, Renji Hospital, Shanghai Cancer Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

2Department of Emergency Medicine, Shanghai Seventh People’s Hospital, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.

3Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.

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We have investigated the rich dynamics of complex wave packets composed of multiple high-lying Rydberg states in He. A quantitative agreement is found between theory and time-resolved photoelectron spectroscopy experiments. We show that the intricate time dependence of such wave packets can be used for investigating quantum defects and performing artifact-free timekeeping. The latter relies on the unique fingerprint that is created by the time-dependent photoionization of these complex wave packets. These fingerprints determine how much time has passed since the wave packet was formed and provide an assurance that the measured time is correct. Unlike any other clock, this quantum watch does not utilize a counter and is fully quantum mechanical in its nature.

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Over the past decades, electronics engineers developed increasingly small, flexible and sophisticated sensors that can pick up a wide range of signals, ranging from human motions to heartrate and other biological signals. These sensors have in turn enabled the development of new electronics, including smartwatches, biomedical devices that can help monitor the health of users over time and other wearable or implantable systems.

Strain , which are designed to convert mechanical force into , are among the most widely used sensing devices within the , as they can be valuable for tracking both human movements and health-related biological signals. While these sensors are already embedded in many electronic devices, most existing solutions are only able to track movements in one direction.

Sensors that can accurately pick up movements and forces in multiple directions could be highly advantageous, as they could be applied to a wider range of scenarios. In addition, these sensors could be embedded in existing electronic devices to broaden their functions or enhance their capabilities.

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A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of stronger, more reliable materials for high-stress environments, such as combustion engines. A paper describing their novel machine learning method was recently published in Nature Computational Materials.

“Using simulations, we were not only able to predict abnormal grain growth, but we were able to predict it far in advance of when that growth happens,” says Brian Y. Chen, an associate professor of computer science and engineering in Lehigh’s P.C. Rossin College of Engineering and Applied Science and a co-author of the study. “In 86% of the cases we observed, we were able to predict within the first 20% of the lifetime of that material whether a particular grain will become abnormal or not.”

When metals and ceramics are exposed to continuous heat—like the temperatures generated by rocket or airplane engines, for example—they can fail. Such materials are made of crystals, or grains, and when they’re heated, atoms can move, causing the crystals to grow or shrink. When a few grains grow abnormally large relative to their neighbors, the resulting change can alter the material’s properties. A material that previously had some flexibility, for instance, may become brittle.

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Thermoelectric materials enable the direct conversion of heat into electrical energy. This makes them particularly attractive for the emerging Internet of Things. For example, for the autonomous energy supply of microsensors and other tiny electronic components.

In order to make the materials more efficient, at the same time, heat transport via the must be suppressed and the mobility of the electrons increased—a hurdle that has often hindered research until now.

An international team led by Fabian Garmroudi has now succeeded in using a new method to develop hybrid materials that achieve both goals—reduced coherence of the lattice vibrations and increased mobility of the charge carriers. The key: a mixture of two materials with fundamentally different mechanical but similar electronic properties.

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