NASA’s Webb reveals the wild weather of a mysterious world 20 light-years away - Science Daily

We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply. AbstractSewing is one of the established methods used to fabricate and assemble multilayer insulation (MLI) blankets for aerospace applications, yet the resulting effective flexural behavior remains insufficiently understood. This study investigates the room-temperature, quasi-static flexural behavior of MLI blankets composed of aluminized BoPET radiation shields and polyester net spacers across structural configurations of 2, 6, 12, and 24 layers. A full factorial design was employed to evaluate the influence of the number of layers, stitch density, needle thread tension, and needle foot force. Statistical analyses demonstrated that the number of layers is the dominant factor governing flexural response. Among the sewing parameters, needle thread tension was associated with modifications in bending length, while needle foot force primarily affected local compaction.

IntroductionBirds rely on a collection of behavioural, physiological, and chemical defences to mitigate the constant threat posed by pathogens and parasites in their environment1. Preen oil from the uropygial gland (UG) is a key component of avian integumentary immunity, supporting feather maintenance and waterproofing, while the UG is also known to harbour diverse microbes, including γ- and α-Pseudomonadota and Actinomycetota, that contribute to feather defense2,3. We recently exemplified a case of the bacterial isolate Amycolatopsis sp. PS_44_ISF1 derived from the UG of the toxic bird Pachycephala schlegelii that can directly contribute to the bird’s chemical defence system, by producing bioactive metabolites such as the antifungal macrolactam ciromicin A3,4, the co-secreted tensioactive lipopeptide family pachycephalamides, and a highly modified hexapeptide, named demiguisin A (1) (Fig. 1). The chemical structure of 1, caught our interest, as it contains non-proteinogenic piperazic acid (hexahydropyridazine-3-carboxylic acid, Piz) residues within the sequence Gly–β,γ-OH-Piz–Leu–Piz–DHPA–γ-c-Pro (Fig. 1)3,5.

The ocean beneath Saturn's moon Enceladus lies under kilometers of ice, but some of its contents do reach the surface. Jets near the south pole spray out water vapor and icy particles, offering a way to investigate the hidden ocean without drilling down to it.

AcknowledgementsWe thank the Saban SC2 core for the 10X single nuclei Multiome analysis and Cellular Imaging core. We also thank Dr. Stanislao Travisano, Dr. Sunhye Lee, Dr. David Wong and Dr. David Cobrinik for helpful discussion and suggestions, and Ms. Kimberly Luna and Dr. Michael Harrison for technical support. We acknowledge the support of The Saban Research Institute at CHLA and its Core Pilot Program for the use of the Spatial Biology & Genomics Core. FundingThis study is supported by fellowship from CIRM Scholar Award  (EDUC4-18082) (XF) and The Heart Ambassadors Intramural Grant (XF), NIH (NHLBI) grant 1R01HL148706 (CL), Alfred E. Mann Cell and Gene Therapy Research Fund (CL), Saban Core Pilot Award, Saban Intramural 2nd R01 award (CL) and R35HL150713 (KDP). Author informationAuthor notesThese authors contributed equally: Hui-Yu Chen, Yuhan Sun.

The successful Antares launch restored U.S. cargo ship redundancy for NASA space station crews.

We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply. AbstractSuicidal ideation (SI) fluctuates rapidly within individuals, but standard ecological momentary assessment (EMA) uses fixed schedules that miss critical risk windows. We present ARES-SI (Adaptive Reinforcement-Enhanced Sampling for Suicidal Ideation), a reinforcement learning system that personalizes EMA timing to individual risk patterns. ARES-SI combines random forest models to predict active SI probability and non-response likelihood with a Q-learning algorithm to determine optimal assessment intervals (30 min for high-risk states, 3 h for low-risk states, and next day to reduce burden). We trained the system using EMA data from 98 participants across three studies with varied sampling frequencies (4–15 assessments per day; 2359 positive active SI responses) over 28-day protocols.