Lifeboat Foundation

“Every mission is contributing back to the other missions and future missions in terms of new tools and techniques to develop,” said Dr. Fred Calef III. “It’s not just you working on something. It’s being able to share data between people… getting a higher order of science.”

As NASA’s Perseverance rover continues to explore the surface of Mars, an open-source, online mapping software known as Multi-Mission Geographic Information System (MMGIS) has been instrumental in determining the best routes for the car-sized rover and landing sites for its Ingenuity helicopter prior to the latter’s “retirement” but is also available for the public to follow the mission, as well. This software holds the potential to help both scientists and the public explore Mars in new and exciting ways for years to come.

“Maps and images are a common language between different people — scientists, engineers, and management,” said Dr. Nathan Williams, who is a mapping specialist at NASA JPL and was a key player in selecting Jezero Crater as the landing site for the Perseverance rover. “They help make sure everyone’s on the same page moving forward, in a united front to achieve the best science that we can.”

Continue reading “MMGIS: Open-Source Mapping Interface for Mars Exploration” »

With the pending arrival of AI agents, we will even more effectively join the always-on interconnected world, both for personal use and for work. In this way, we will increasingly dialog and interact with digital intelligence everywhere.

The path to AGI and superintelligence remains shrouded in uncertainty, with experts divided on its feasibility and timeline. However, the rapid evolution of AI technologies is undeniable, promising transformative advancements. As businesses and individuals navigate this rapidly changing landscape, the potential for AI-driven innovation and improvement remains vast. The journey ahead is as exciting as it is unpredictable, with the boundaries between human and artificial intelligence continuing to blur.

By mapping out proactive steps now to invest and engage in AI, upskill our workforce and attend to ethical considerations, businesses and individuals can position themselves to thrive in the AI-driven future.

Organic electrochemical artificial neurons (OANs) are the latest entry of building blocks, with a few different approaches for circuit realization. OANs possess the remarkable capability to realistically mimic biological phenomena by responding to key biological information carriers, including alkaline ions, noise in the electrolyte, and biological conditions. An organic artificial neuron with a cascade-like topology made of OECT inverters has shown basic (regular) firing behavior and firing frequency that is responsive to the concentration of ionic species (Na⁺, K⁺) of the host liquid electrolyte³³. An organic artificial neuron consisting of a non-linear building block that displays S-shape negative differential resistance (S-NDR) has also been recently demonstrated³⁴. Due to the realization of the non-linear circuit theory with OECTs and the sharp threshold for oscillations, this artificial neuron displays biorealistic firing properties and neuronal excitability that can be found in the biological domain such as input voltage-induced regular and irregular firing, ion and neurotransmitter-induced excitability and ion-specific oscillations. Biohybrid devices comprising artificial neurons and biological membranes have also shown to operate synergistically, with membrane impedance state modulating the firing properties of the biohybrid in situ. More recently, a circuit leveraging the non-linear properties of antiambipolar OMIECs, which exhibit negative differential transconductance, has been realized³⁵. These neurons show biorealistic properties such as various firing modes and responsivity to biologically relevant ions and neurotransmitters. With this neuron, ex-situ electrical stimulation has been shown in a living biological model. Therefore, the class of OANs perfectly complements the broad range of features already demonstrated by solid-state spiking circuits (Supplementary Table 1), offering opportunities for both hybrid interfacing between these technologies and new developments in neuromorphic bioelectronics.

Despite the promising recent realizations of organic artificial neurons, all approaches still remain in the qualitative demonstration domain and a rigorous investigation of circuit operation is still missing. Indeed, quantitative models exist only for inorganic, solid-state artificial neurons without the inclusion of physical soft-matter parameters and the biological wetware (i.e., aqueous electrolytes, alkaline ions, biomembranes)^36,37. This gap in knowledge significantly impedes the simulation of larger-scale functional circuits, and therefore the design and development of integrated organic neuromorphic electronics, biohybrids, OAN-based neural networks, and intelligent bioelectronics.

In this work, we unravel the operation of organic artificial neurons that display non-linear phenomena such as S-shape negative differential resistance (S-NDR). By combining experiments, numerical simulations of non-linear iontronic circuits, and newly developed analytical expressions, we investigate, reproduce, rationalize, and design the wide biorealistic repertoire of organic electrochemical artificial neurons including their firing properties, neuronal excitability, wetware operation, and biohybrid formation. The OAN operation is efficiently rationalized to include how neuronal dynamics are probed by biochemical stimuli in the electrolyte medium. The OAN behavior is also extended on the biohybrid formation, with a solid rationale of the in situ interaction of OANs with biomembranes. Non-linear simulations of OANs are rooted in a physics-based framework, considering ion type, ion concentration, organic mixed ionic–electronic parameters, and biomembrane properties. The derived analytical expressions establish a direct link between OAN spiking features and its physical parameters and therefore provide a mapping between neuronal behavior and materials/device parameters. The proposed approach open opportunities for the design and engineering of advanced biorealistic OAN systems, establishing essential knowledge and tools for the development of neuromorphic bioelectronics, in-liquid neural networks, biohybrids, and biorobotics.

A new study by Brown University researchers may help redefine how scientists map the surface of the Moon, making the process more streamlined and precise than ever before.

Published in the Planetary Science Journal, the research by Brown scholars Benjamin Boatwright and James Head describes enhancements to a mapping technique called shape-from-shading. The technique is used to create detailed models of lunar terrain, outlining craters, ridges, slopes and other surface hazards. By analyzing the way light hits different surfaces of the Moon, it allows researchers to estimate the three-dimensional shape of an object or surface from composites of two-dimensional images.

Accurate maps can help lunar mission planners to identify safe landing spots and areas of scientific interest, making mission operations smoother and more successful.

A new analysis of data collected on Venus more than 30 years ago suggests the planet may currently be volcanically active.

A research group from Italy led by David Sulcanese of the Università d’Annunzio in Pescara, Italy, has used data from a radar mapping of Venus’s surface taken in the early 1990s to search for volcanic lava flow, finding it in two regions.

The discovery suggests that volcanic activity may be currently active and more widespread than was previously thought, supporting previous indirect evidence that there is volcanic activity on Venus.

Groundbreaking maps reveal the complex gene regulation in brains with and without mental disorders, enhancing the understanding of mental illnesses and potential treatments.

A consortium of researchers has produced the largest and most advanced multidimensional maps of gene regulation networks in the brains of people with and without mental disorders. These maps detail the many regulatory elements that coordinate the brain’s biological pathways and cellular functions. The research, supported by the National Institutes of Health (NIH), used postmortem brain tissue from over 2,500 donors to map gene regulation networks across different stages of brain development and multiple brain-related disorders.

“These groundbreaking findings advance our understanding of where, how, and when genetic risk contributes to mental disorders such as schizophrenia, post-traumatic stress disorder, and depression,” said Joshua A. Gordon, M.D., Ph.D., director of NIH’s National Institute of Mental Health (NIMH). “Moreover, the critical resources, shared freely, will help researchers pinpoint genetic variants that are likely to play a causal role in mental illnesses and identify potential molecular targets for new therapeutics.”

One of the main scientific objectives of next-generation observatories (like the James Webb Space Telescope) has been to observe the first galaxies in the Universe – those that existed at Cosmic Dawn. This period is when the first stars, galaxies, and black holes in our Universe formed, roughly 50 million to 1 billion years after the Big Bang. By examining how these galaxies formed and evolved during the earliest cosmological periods, astronomers will have a complete picture of how the Universe has changed with time.

As addressed in previous articles, the results of Webb’s most distant observations have turned up a few surprises. In addition to revealing that galaxies formed rapidly in the early Universe, astronomers also noticed these galaxies had particularly massive supermassive black holes (SMBH) at their centers. This was particularly confounding since, according to conventional models, these galaxies and black holes didn’t have enough time to form. In a recent study, a team led by Penn State astronomers has developed a model that could explain how SMBHs grew so quickly in the early Universe.

The research team was led by W. Niel Brandt, the Eberly Family Chair Professor of Astronomy and Astrophysics at Penn State’s Eberly College of Science. Their research is described in two papers presented at the 244th meeting of the American Astronomical Society (AAS224), which took place from June 9th to June 13th in Madison, Wisconsin. Their first paper, “Mapping the Growth of Supermassive Black Holes as a Function of Galaxy Stellar Mass and Redshift,” appeared on March 29th in The Astrophysical Journal, while the second is pending publication. Fan Zou, an Eberly College graduate student, was the lead author of both papers.

In 2024, extensive flooding in southern Brazil caused significant damage, particularly in Rio Grande do Sul. Maps showing floodwater depths were vital for disaster response and economic damage assessments, supported by data from NASA and other scientific sources.

Storms and torrential rain battered southern Brazil beginning in late April 2024, causing deadly, destructive flooding that persisted through much of May. Toward the end of the month, parts of Rio Grande do Sul state remained underwater, and the scope of the damage became increasingly evident.

Maps of floodwater extent are one way to assess a flooding event. But information about the depth of that water is also useful, potentially aiding rescue and relief operations, informing decisions about road closures and accessibility, and contributing to analyses of damage and flood risk.

Hong Kong (CNN) — Tesla is one step closer to launching full-self driving (FSD) technology in China after it clinched an agreement with Baidu to upgrade its mapping software.

The Chinese tech giant said Saturday that it was providing lane-level navigation services for Tesla cars. Baidu (BIDU) says this level of navigation can provide drivers with detailed information, including making lane recommendations ahead of upcoming turns, to enhance safety.