Lifeboat Foundation

With depression affecting around 1 in 10 of us at some point during our lives, the need for new and improved treatments is a top priority for researchers – and it appears that spinal cord stimulation could be one route for experts to investigate.

A team led by researchers at the University of Cincinnati College of Medicine devised a pilot clinical trial in which a little black box was placed on the spinal cord of 20 volunteers with depression, with one electrode on the back and one on the right shoulder.

The box then delivered a specially customized, low-level electric buzz to half of the volunteers, for three sessions per week over eight weeks. This was shown to have a greater effect on depressive symptoms than the different, ‘placebo’ charge administered to the other half of the volunteers.

After Artemis 2 launches and before the crew sets course for the Moon, the crew will spend a day or so carrying out systems checks in Earth orbit. During this stage, the crew will also test their ability to rendezvous with the SLS’s Interim Cryogenic Propulsion Stage, which will serve as valuable practice for future docking maneuvers needed in later Artemis missions. The spacecraft’s orbit around Earth will be highly elliptical, ranging in altitude from about 115 miles (185 kilometers) to 46,000 miles (74,000 km) above Earth’s surface.

Once they receive approval to set course for the Moon, the four members of the Artemis 2 crew will embark on humanity’s first trip to the Moon’s neighborhood since 1972.

Artemis 2 will not land on or orbit the Moon, but will instead use several lunar-destination burns and course corrections to achieve a so-called free-return trajectory. This approach will bring the craft to within about 6,400 miles (10,000 km) of the Moon’s farside — and allow it to return to Earth even if the craft experiences an engine failure. The free-return trajectory will form a figure-eight around Earth and the Moon, and the Artemis 2 mission is expected to last about 10 days.

Hospitals in four states, as well as Washington D.C., have brought in some form of mask-wearing requirements amid an uptick in cases.

Now, astronomers led by Northwestern University have pinpointed the extraordinary object’s birthplace — and it’s rather curious, indeed.

Using images from NASA ’s Hubble Space Telescope, the researchers traced the FRB back to not one galaxy but a group of at least seven galaxies. The galaxies in the collection appear to be interacting with one another — perhaps even on the path to a potential merger. Such groups of galaxies are rare and possibly led to conditions that triggered the FRB.

The unexpected finding might challenge scientific models of how FRBs are produced and what produces them.

What actually happens is much weirder, and may help us understand more about quantum mechanics.

The quantum Cheshire cat effect draws its name from the fictional Cheshire Cat in the Alice in Wonderland story. That cat was able to disappear, leaving only its grin behind. Similarly, in a 2013 paper, researchers claimed quantum particles are able to separate from their properties, with the properties traveling along paths the particle cannot. They named this the quantum Cheshire cat effect. Researchers since have claimed to extend this further, swapping disembodied properties between particles, disembodying multiple properties simultaneously, and even “separating the wave-particle duality” of a particle.

Contextuality in Quantum Mechanics.

Discovery could be useful in developing new therapies for multiple sclerosis, neurodegenerative conditions, and brain cancer.

New research from Oregon Health & Science University for the first time reveals the function of a little-understood junction between cells in the brain that could have important treatment implications for conditions ranging from multiple sclerosis to Alzheimer’s disease, to a type of brain cancer known as glioma.

The study will be published today (January 12) in the journal Nature Neuroscience.

Interactions between RNA and proteins are the cornerstone of many important biological processes from transcription and translation to gene regulation, yet little is known about the ancient origin of said interactions. We hypothesized that peptide amyloids played a role in the origin of life and that their repetitive structure lends itself to building interfaces with other polymers through avidity. Here, we report that short RNA with a minimum length of three nucleotides binds in a sequence-dependent manner to peptide amyloids. The 3′–5′ linked RNA backbone appears to be well-suited to support these interactions, with the phosphodiester backbone and nucleobases both contributing to the affinity. Sequence-specific RNA–peptide interactions of the kind identified here may provide a path to understanding one of the great mysteries rooted in the origin of life: the origin of the genetic code.

On top of this, the use of quantification has significantly increased over the last decades with the inflation of metrics, indicators, and scores to rank and benchmark options (Muller, 2018). The case of energy policy making in the European Union is again an effective example. The European Union’s recent energy strategy has been underpinned by the Clean Energy for all Europeans packages, which are in turn supported by a number of individual directives, each one characterized by a series of quantitative goals (European Commission, 2023). The quantification of the impact (impact assessment) is customarily required to successfully promote new political measures (European Commission, 2015a) and is in turn based on quantification, often from mathematical models (Saltelli et al., 2023). The emphasis on producing exact figures to assess the contribution of a new technology, political or economic measure has put many models and their users into contexts of decision-making that at times extends beyond their original intent (Saltelli, Bammer et al., 2020). At the same time, the efforts to retrospectively assess the performance of energy models have been extremely limited, one example being the Energy Modeling Forum in the United States (Huntington et al., 1982). In spite of this, retrospective assessments can be very helpful in understanding the sources of mismatch between a forecast and the actual figures reported a posteriori (Koomey et al., 2003). For example, long-range forecast models are typically based on the assumption of gradual structural changes, which are at stake with the disruptive events and discontinuities occurring in the real world (Craig et al., 2002). This dimension is especially important in terms of the nature and pace of technology change (Bistline et al., 2023 ; Weyant & Olavson, 1999). A further critical element in this approach is the cognitive bias in scenario analysis that naturally leads to overconfidence in the option being explored and results in an underestimate of the ranges of possible outcomes (Morgan & Keith, 2008).

Additionally, in their quest for capturing the features of the energy systems represented, models have increased their complicatedness and/or complexity. In this context, the need to appraise model uncertainty has become of paramount importance, especially considering the uncertainty due to propagation errors caused by model complexification (Puy et al., 2022). In ecology, this is known as the O’Neil conjecture, which posits a principle of decreasing returns for model complexity when uncertainties come to dominate the output (O’Neill, 1989 ; Turner & Gardner, 2015). Capturing and apportioning uncertainty is crucial for a healthy interaction at the science–policy interface, including energy policy making, because it promotes better informed decision-making. Yet Yue et al. (2018) found that only about 5% of the studies covering energy system optimization models have included some form of assessment of stochastic uncertainty, which is the part of uncertainty that can be fully quantified (Walker et al., 2003). When it comes to adequately apportioning this uncertainty onto the input parameters and hypotheses through sensitivity analysis, the situation is even more critical: Only very few papers in the energy field have made the use of state-of-the-art approaches (Lo Piano & Benini, 2022 ; Saltelli et al., 2019). Further to that, the epistemic part of uncertainty, the one that arises due to imperfect knowledge and problem framing, has been largely ignored in the energy modeling literature (Pye et al., 2018). For instance, important sources of uncertainties associated with regulatory lag and public acceptance have typically been overlooked. 1

In this contribution, we discuss three approaches to deal with the challenges of non-neutrality and uncertainty in models: The numerical unit spread assessment pedigree (NUSAP) method, diagnostic diagrams, and sensitivity auditing (SAUD). These challenges are especially critical when only one (set of) model(s) has been selected to contribute to decision-making. One practical case is used to showcase in retrospective the relevance of the issue and the associated problems: the International Institute for Applied Systems Analysis (IIASA) global modeling in the 1980s.

Department of Energy user facility helps probe questions from changes in the structure of nuclei to nuclear reactions that shape the Universe.

The Facility for Rare Isotope Beams (FRIB) enables discoveries in the science of atomic nuclei, their role in the cosmos, and the fundamental symmetries of nature. This accelerator facility uses beams of short-lived nuclei not available elsewhere. Results from FRIB address questions such as the limits of the nuclear chart, the origin of the elements, and the reason for why there is more matter than antimatter in our Universe.

In FRIB’s first year, its measurements tackled the changes in the structure of the shortest-lived nuclei, exotic decay modes, nuclear reactions that affect cosmic events such as X-ray bursts, and processes in the crusts of neutron stars.