Lifeboat Foundation

The field of supercapacitors consistently focuses on research and challenges to improve energy efficiency, capacitance, flexibility, and stability. Low-cost laser-induced graphene (LIG) offers a promising alternative to commercially available graphene for next-generation wearable and portable devices, thanks to its remarkable specific surface area, excellent mechanical flexibility, and exceptional electrical properties. We report on the development of LIG-based flexible supercapacitors with optimized geometries, which demonstrate high capacitance and energy density while maintaining flexibility and stability. Three-dimensional porous graphene films were synthesized, and devices with optimized parameters were fabricated and tested. One type of device utilized LIG, while two other types were fabricated on LIG by coating multi-walled carbon nanotubes (MWCNT) at varying concentrations.

Monolithic 3D integration of electronics based on fully 2D materials is demonstrated in the performance of artificial intelligence tasks.

An international team of researchers has used time-resolved ultrafast crystallography to follow the progress of DNA repair by a photolyase enzyme. The work is ‘the first structural characterisation of a full enzyme reaction cycle,’ says Manuel Maestre-Reyna, who led the research.

Photolyases repair DNA damage caused by ultraviolet light in bacteria, fungi, plants and some animals including marsupials. Humans and other mammals don’t contain these enzymes, but we too incur light-induced damage. One common outcome is the formation of cyclobutane pyrimidine dimers (CPDs), where two adjacent pyrimidine bases (thymine or cytosine) fuse together via a four-membered cyclobutane ring. ‘CPD formation is the main cause of skin cancer, and sunburnt skin always contains CPD lesions’, says Maestre-Reyna, a biochemist at the Institute of Biological Chemistry in Taipei, Taiwan.

A new study, published in PLOS ONE, has uncovered a remarkable connection between individuals’ musical preferences and their moral values, shedding new light on the profound influence that music can have on our moral compass.

The research, conducted by a team of scientists at Queen Mary University of London and ISI Foundation in Turin, Italy, employed machine learning techniques to analyze the lyrics and audio features of individuals’ favorite songs, revealing a complex interplay between music and morality.

“Our study provides compelling evidence that music preferences can serve as a window into an individual’s moral values,” stated Dr. Charalampos Saitis, one of the senior authors of the study and Lecturer in Digital Music Processing at Queen Mary University of London’s School of Electronic Engineering and Computer Science.

If we lived in a cosmic area with below average density, it would explain recent contradictory measurements of the universe’s expansion.

BMIs using intracortical electrodes, such as Utah arrays, are particularly adept at sensing fast changing (millisecond-scale) neural activity from spatially localized regions (1 cm) during behavior or stimulation that is correlated to activity in such spatially specific regions, for example, M1 for motor and V1 for vision. Intracortical electrodes, however, struggle to track individual neurons over longer periods of time, for example, between subsequent recording sessions^15,16. Consequently, decoders are typically retrained every day¹⁵. A similar neural population identification problem is also present with an ultrasound device, including from shifts in the field of view between experiment sessions. In the current study, we demonstrated an alignment method that stabilizes image-based BMIs across more than a month and decodes from the same neurovascular populations with minimal, if any, retraining. This is a critical development that enables easy alignment of a previous days’ models to a new day’s data and allows decoding to begin with minimal to no new training data. Much effort has focused on ways to recalibrate intracortical BMIs across days that do not require extensive new data^{18,19,20,21,22,23}. Most of these methods require identification of manifolds and/or latent dynamical parameters and collecting new neural and behavioral data to align to these manifolds/parameters. These techniques are, to date, tailored to each research group’s specific applications with varying requirements, such as hyperparameter tuning of the model²³ or a consistent temporal structure of data²². They are also susceptible to changes in function in addition to anatomy. For example, ‘out-of-manifold’ learning/plasticity alters the manifold²⁴ in ways that many alignment techniques struggle to address. Finally, some of the algorithms are computationally expensive and/or difficult to implement in online use²².

Contrasting these manifold-based methods, our decoder alignment algorithm leverages the intrinsic spatial resolution and field of view provided by fUS neuroimaging to perform decoder stabilization in a way that is intuitive, repeatable and performant. We used a single fUS frame (∼ 500 ms) to generate an image of the current session’s anatomy and aligned a previous session’s field of view to this single image. Notably, this did not require any additional behavior for the alignment. Because we only relied upon the anatomy, our decoder alignment is robust, can use any off-the-shelf alignment tool and is a valid technique so long as the anatomy and mesoscopic encoding of relevant variables do not change drastically between sessions.

It remains an open question as to how much the precise positioning of the ultrasound transducer during each session matters for decoder performance, especially out-of-plane shifts or rotations. In these current experiments, we used linear decoders that assumed a given image pixel is the same brain voxel across all aligned data sessions. To minimize disruptions to this pixel–voxel relationship, we performed image alignment within the 2D plane. As we could only image a 2D recording plane, we did not correct for any out-of-plane brain shifts between sessions that would have disrupted the pixel–voxel mapping assumption. Future fUS-BMI decoders may benefit from three-dimensional (3D) models of the neurovasculature, such as registering the 2D field of view to a 3D volume^25,26,27 to better maintain a consistent pixel–voxel mapping.

A recent study discovered that for individuals who often feel lonely, the distinction between actual friends and beloved fictional characters gets blurred in the part of the brain that is active when thinking about others, a new study found.

The study involved brain scans of “Game of Thrones” enthusiasts as they reflected on different characters from the series and their real-life friends. Prior to the study, all participants had undergone a loneliness assessment.

The difference between those who scored highest on loneliness and those who scored lowest was stark, said Dylan Wagner, co-author of the study and associate professor of psychology at The Ohio State University.

OAK RIDGE, Tenn. — At Oak Ridge National Laboratory, the government-funded science research facility nestled between Tennessee’s Great Smoky Mountains and Cumberland Plateau that is perhaps best known for its role in the Manhattan Project, two supercomputers are currently rattling away, speedily making calculations meant to help tackle some of the biggest problems facing humanity.

You wouldn’t be able to tell from looking at them. A supercomputer called Summit mostly comprises hundreds of black cabinets filled with cords, flashing lights and powerful graphics processing units, or GPUs. The sound of tens of thousands of spinning disks on the computer’s file systems, and air cooling technology for ancillary equipment, make the device sound somewhat like a wind turbine — and, at least to the naked eye, the contraption doesn’t look much different from any other corporate data center. Its next-door neighbor, Frontier, is set up in a similar manner across the hall, though it’s a little quieter and the cabinets have a different design.

Yet inside those arrays of cabinets are powerful specialty chips and components capable of, collectively, training some of the largest AI models known. Frontier is currently the world’s fastest supercomputer, and Summit is the world’s seventh-fastest supercomputer, according to rankings published earlier this month. Now, as the Biden administration boosts its focus on artificial intelligence and touts a new executive order for the technology, there’s growing interest in using these supercomputers to their full AI potential.

Whole-genome alignment of 239 primate species reveals noncoding regulatory elements that are under selective constraint in primates but not in other placental mammals, that are enriched for variants that affect human gene expression and complex traits in diseases.