NPL collaborates with NVIDIA to use AI for automating quantum device calibration, improving qubit stability analysis and benchmarking methods.
The Individual Brain Charting (IBC) project has released its fifth and largest update of high-resolution fMRI data, adding a new set of cognitive tasks to one of the most detailed brain-mapping datasets available today. The dataset, which is openly accessible through EBRAINS, is described in a new publication in Nature Scientific Data.
The new release expands the dataset with 18 tasks collected from 11 participants under tightly controlled, standardised conditions – bringing many of them close to 40 hours of scanned data each.
The IBC project launched in 2014 and was funded by the Human Brain Project. It aims to map how individual brains respond across a wide range of cognitive functions. By repeatedly scanning the same participants with diverse tasks – from mathematics and spatial navigation to emotion recognition, reward processing, and working memory – the team is building an exceptionally rich resource for studying individual variability in brain organization.
Engineers have printed tiny, artificial neurons that can “talk” to mouse brain cells, and the development could pave the way to innovations in computing and medicine.
The work, published April 15 in the journal Nature Nanotechnology, adds to a growing field that aims to build computers that mimic the inner workings of the brain.
The Hashemite Kingdom of Jordan signed the Artemis Accords Thursday during a ceremony hosted by NASA at the agency’s headquarters in Washington, becoming the latest nation to commit to responsible space exploration to benefit humanity.
“It is my privilege to welcome Jordan as the newest signatory to the Artemis Accords,” said NASA Administrator Jared Isaacman. “By signing the accords today, Jordan brings valuable perspective and capabilities that will help expand the Golden Age of exploration for all mankind. They join at a pivotal moment, as we take the accords principles and put them into practice with humanity’s return to the Moon. Through Artemis, we’re going back to the lunar surface, with contributions from our international partners, to build a Moon Base and to stay.”
Ambassador Dina Kawar of Jordan signed the accords on behalf of the country. U.S. Department of State Acting Principal Deputy Assistant Secretary for Oceans and International Environmental and Scientific Affairs Ruth Perry also participated in the ceremony.
Researchers have uncovered new insights into the early development of baby stars. As published in The Astrophysical Journal Letters, a research team from Kyushu University and Kagawa University reports that during the early growth period of a baby star, the protostellar disk—the dense disk of gas and dust that surrounds the star—expels magnetic flux and forms a giant warm ring of gas about 1,000 au (astronomical units) in size. The research team explains that these “sneezes” of matter and magnetic energy help the baby star release excess energy, leading to proper star formation.
One of the many mysteries that the universe holds is how stars like our sun are born. Stars are born in areas of the cosmos called stellar nurseries, where gas and dust coalesce to form early stars called protostars. The best way to understand star formation is to observe these stellar nurseries. However, this can be difficult due to the aforementioned gas and dust obscuring the baby star.
“Thankfully, one of the most promising ways to get a clear view of protostars is to use the Atacama Large Millimeter/submillimeter Array (ALMA) in Chile,” explains Professor Masahiro N. Machida of Kyushu University’s Faculty of Science, who led the study. “This radio telescope lets us see the different materials that make up stellar nurseries.”
While technology has made the world “smaller,” it has also pulled individuals apart, thanks to mobile phones and other devices that command our attention. Cornell University researchers are using technology, in the form of a mirror-equipped robot, to help bring people together. Members of the Architectural Robotics Lab, led by Keith Evan Green, have built a four-foot-tall robot—dubbed MirrorBot—with dual mirrors that, when placed in front of a pair of strangers, let each participant see themself in one mirror and the other person in the other.
In a study involving participants in a waiting-room setting, MirrorBot spurred conversations, playful exchanges and other interactions between strangers. The findings suggest that robots can act not only as conversational partners, but also as spatial mediators. The research is published in the journal Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction.
“We weren’t just trying to trigger conversations, but to support the very first moment of social connection, which is the eye contact,” said Serena Guo, lead author of the paper.
By Chuck Brooks
Artificial intelligence has entered a new phase of strategic consequence, and executives, policymakers, and small business owners can no longer afford to treat it as a back-office technology decision. The central question is no longer whether an organization will use AI. It is how much of that AI the organization will actually own.
Sovereign AI—the end-to-end ownership of the data, the model, and the interaction layer that connects them to the people who depend on them—is rapidly moving from a geopolitical discussion into a board-level and Main Street requirement.
Sovereign AI has largely been framed as a national concern, but that framing is incomplete. The same logic that compels a nation to own its AI stack compels a hospital system, a regional bank, a defense supplier, and a mid-sized manufacturer to do the same.
The fundamental quantum postulates on the existence of a wave function, its propagation with the Schrödinger equation in theorem 3.2 and the wave collapse at a measurement in lemma 3.3 are derived from the classical theorem 2.4. Furthermore, analytic computations of the classical action are simpler than solving the Feynman path integral and potentially easier than solving the Schrödinger equation directly. In addition, theorem 3.2 is a multi-particle result.
The J classical multipaths in theorem 3.2 and lemma 3.3 are strictly determined by the initial and final conditions. In the double slit experiment, the probabilistic quantum observation results from the non-Lipschitz constraint force in the slit. For the harmonic oscillator, the Coulomb wave, the particle in the box, or the spinning particle, the initial probabilistic density distribution is classically propagated forward in time. In the EPR experiment [64,65], theorem 2.4 determines a constant angular momentum χo↑,χo↓ over time, and lemma 3.3 in turn allows a classical interpretation that the decision which spin correlation is sensed behind the filters is already taken when the particles separate.
💬 Editorial: A sixth-generation high-sensitivity cardiac troponin T assay could allow clinicians to reassure more emergency department patients they are not having a myocardial infarction at presentation, but further study is needed to optimize clinical application.
In 2008, Roche Diagnostics introduced a high-sensitivity version of their cardiac troponin T assay (hs-cTnT), a fifth-generation assay. Researchers quickly deduced that by using the assay’s limit of detection (LoD) of 5 ng/L (to convert to micrograms per liter, multiply by 0.001) as a cutoff, many patients could safely be classified as very low-risk for myocardial infarction (MI).1,2 Researchers gathered data across multiple institutions, and a 9241-patient meta-analysis demonstrated a pooled sensitivity for the LoD of 98.7%.3 Outside the US, on presentation (0-hour) concentrations less than LoD became guideline recommended, reassuring patients quickly and reducing time spent in busy emergency departments (EDs). Once US Food and Drug Administration (FDA) approval was obtained in the US, a similar risk-stratification approach became possible, though using a threshold of 6 ng/L because the FDA mandated that exact concentrations below the limit of quantitation (LoQ) be not reported. In the meantime, troponin I assay manufacturers brought to market high-sensitivity cardiac troponin I (hs-cTnI) assays. Low-risk thresholds were derived for these that were above the LoD and LoQ by identifying the concentration that gave a minimum prespecified statistical performance. Most often these minimums are greater than or equal to 99% sensitivity4 and greater than or equal to 99.5% negative predictive value (NPV). Roche Diagnostics has now placed in the hands of researchers a sixth-generation cTnT assay. Already this has been established as high sensitivity, with very low LoD and LoQ and well-defined sex-specific upper-reference levels.5 This will allow, for the first time with hs-cTnT, the derivation of single-sample, very low-risk thresholds likely usable across institutions. In this issue of JAMA Cardiol ogy, Thurston and colleagues6 present the first such derivation of a single-sample, very low-risk threshold for the Roche sixth-generation hs-cTnT assay.
In a prospective cohort study of 987 patients, blood was drawn at multiple time points from ED presentation. cTnT concentrations were measured on the same analyzer with both the fifth-and sixth-generation assays. This allowed derivation of a sixth-generation single-sample very low-risk threshold, a comparison of the performance of that threshold with the fifth-generation LoD, and determination of the performance of the High-Sensitivity Troponin in the Evaluation of Patients With Suspected Acute Coronary Syndrome (High-STEACS) early rule-out pathway. External validation used stored samples from the Advantageous Predictors of Acute Coronary Events (APACE) study. The primary outcome was an index or subsequent MI (types 1, 4b, or 4c) or cardiac death within 30 days. The prespecified goal was to determine the highest troponin threshold with statistical metrics NPV greater than or equal to 99.5% and sensitivity greater than or equal to 99%.