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Nearly half a century ago, two papers postulated the likelihood of lunar lava tube caves using mathematical models. Today, armed with an array of orbiting and fly-by satellites and survey instrumentation, we have now acquired cave data across our solar system-including the identification of potential cave entrances on the Moon, Mars, and at least nine other planetary bodies. These discoveries gave rise to the study of planetary caves. To help advance this field, we leveraged the expertise of an interdisciplinary group to identify a strategy to explore caves beyond Earth. Focusing primarily on astrobiology, the cave environment, geology, robotics, instrumentation, and human exploration, our goal was to produce a framework to guide this subdiscipline through at least the next decade. To do this, we first assembled a list of 198 science and engineering questions. Then, through a series of social surveys, 114 scientists and engineers winnowed down the list to the top 53 highest priority questions. This exercise resulted in identifying emerging and crucial research areas that require robust development to ultimately support a robotic mission to a planetary cave-principally the Moon and/or Mars. With the necessary financial investment and institutional support, the research and technological development required to achieve these necessary advancements over the next decade are attainable. Subsequently, we will be positioned to robotically examine lunar caves and search for evidence of life within Martian caves; in turn, this will set the stage for human exploration and potential habitation of both the lunar and Martian subsurface.
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http://dx.doi.org/10.1029/2022JE007194 | DOI Listing |
Crit Rev Immunol
January 2025
Department of Pharmacy, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Dist. Medchal,500078, Telangana State, India.
Caseinolytic protease P (ClpP) is a highly conserved serine protease that plays a pivotal role in protein homeostasis and quality control in bacteria, mitochondria of mammalian cells, and plant chloroplasts. As the proteolytic core of the ATP-dependent Clp protease complex, ClpP partners with regulatory ATPases (e.g.
View Article and Find Full Text PDFCrit Rev Immunol
January 2025
Department of Pharmacy, Birla Institute of Technology and Science (BITS) Pilani, Hyderabad Campus, Dist. Medchal,500078, Telangana State, India.
IL-2 agonists significantly modulate T cell regulation, impacting activation, proliferation, differentiation, and immune homeostasis. Interleukin-2 (IL-2) is crucial for T cell growth and function, binding to the IL-2 receptor to trigger signaling pathways that balance immune responses. IL-2 promotes the expansion of effector T cells and enhances regulatory T cells (Tregs), preventing autoimmune responses.
View Article and Find Full Text PDFCrit Rev Ther Drug Carrier Syst
January 2025
The emergence of messenger ribonucleic acid (mRNA) vaccines as an alternative platform to traditional vaccines has been accompanied by advances in nanobiotechnology, which have improved the stability and delivery of these vaccines through novel nanoparticles (NPs). Specifically, the development of NPs for mRNA delivery has facilitated the loading, protection and release of mRNA in the biological microenvironment, leading to the stimulation of mRNA translation for effective intervention strategies. Intriguingly, two mRNA vaccines, BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna), have been permitted for emergency usage authorization to prevent COVID-19 infection by USFDA.
View Article and Find Full Text PDFNeural Netw
September 2025
School of Mathematics and Information Science, Guangxi University, Nanning, 530004, China. Electronic address:
This study presents a novel variable gain intermittent boundary control (VGIBC) approach for stabilizing delayed stochastic reaction-diffusion Cohen-Grossberg neural networks (SRDCGNN). In contrast to traditional constant gain intermittent boundary control (CGIBC) methods, the proposed VGIBC framework dynamically adjusts the control gain based on the operational duration within each control cycle, thereby improving adaptability to variations in work interval lengths. The time-varying control gain is designed using a piecewise interpolation method across work intervals, defined by a finite set of static gain matrices.
View Article and Find Full Text PDFNeural Netw
September 2025
School of Electronic Science and Engineering, Nanjing University, China. Electronic address:
The Segment Anything Model (SAM) is a cornerstone of image segmentation, demonstrating exceptional performance across various applications, particularly in autonomous driving and medical imaging, where precise segmentation is crucial. However, SAM is vulnerable to adversarial attacks that can significantly impair its functionality through minor input perturbations. Traditional techniques, such as FGSM and PGD, are often ineffective in segmentation tasks due to their reliance on global perturbations that overlook spatial nuances.
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