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Context. We have studied the dense gas morphology and kinematics towards the infrared dark cloud (IRDC) G034.77-00.55, shock-interacting with the SNR W44, to identify evidence of early-stage star formation induced by the shock. Aims. We used high angular resolution N₂H⁺(1−0) images across G034.77-00.55, obtained with the Atacama Large Millimeter/sub-Millimeter Array. N₂H⁺is a well-known tracer of dense and cold material, optimal for identifying gas that has the highest potential to harbour star formation. Methods. The N₂H⁺emission is distributed in two elongated structures, one towards the dense ridge at the edge of the source and one towards the inner cloud. Both elongations are spatially associated with well-defined mass-surface density features. The velocities of the gas in the two structures (i.e. 38–41 km s⁻¹and 41–43 km s⁻¹) are consistent with the lowest velocities of the J- and C-type parts, respectively, of the SNR-driven shock. A third velocity component is present at 43–45.5 km s^–1. The dense gas shows a fragmented morphology with core-like fragments at scales consistent with the Jeans lengths, masses of ~1–20 M_⊙, densities of (n(H₂)≥10⁵cm^–3) sufficient to host star formation in free-fall timescales (a few 10⁴yr), and with virial parameters that suggest a possible collapse. Results. The W44 driven shock may have swept up the encountered material, which is now seen as a dense ridge, almost detached from the main cloud, and an elongation within the inner cloud, well constrained in both N₂H⁺emission and mass surface density. This shock compressed material may have then fragmented into cores that are either in a starless or pre-stellar stage. Additional observations are needed to confirm this scenario and the nature of the cores. 

We report on a method for determining the absolute nuclear charge radius of high- $Z$elements using extreme-ultraviolet spectroscopy of highly charged Na-like ions in tandem with highly accurate atomic structure calculations of transition energy differences. The application of this method has reduced the nuclear charge radius uncertainty of ${}^{191}\mathrm{Ir}$by a factor of 8 from the currently accepted literature value, with a recently reported charge radius of 5.435(12) fm. The result reduces the charge radius uncertainty along the full Ir isotopic chain when combined with prior optical isotope shift measurements. The technique utilizes only a few million ions stored in an ion trap, which should apply to measurements with small quantities of radioactive nuclei. Published by the American Physical Society2025 

Context.Massive stars have an impact on their surroundings from early in their formation until the end of their lives. However, very little is known about their formation. Episodic accretion may play a crucial role in the process, but only a handful of observations have reported such events occurring in massive protostars. Aims.We aim to investigate the outburst event from the high-mass star-forming region S255IR where the protostar NIRS3 recently underwent an accretion outburst. We follow the evolution of this source both in photometry and morphology of its surroundings. Methods.We performed near infrared adaptive optics observations on the S255IR central region using the Large Binocular Telescope in theK_sbroadband as well as the H₂and Brγ narrow-band filters with an angular resolution of ~07″.06, close to the diffraction limit. Results.We discovered a new near infrared knot north-east of NIRS3 that we interpret as a jet knot that was ejected during the last accretion outburst and observed in the radio regime as part of a follow-up after the outburst. We measured a mean tangential velocity for this knot of 450 ± 50 km s⁻¹. We analysed the continuum-subtracted images from H₂, which traces jet-shocked emission, and Brγ, which traces scattered light from a combination of accretion activity and UV radiation from the central massive protostar. We observed a significant decrease in flux at the location of NIRS3, withK= 13.48 mag being the absolute minimum in the historic series. Conclusions.Our observations strongly suggest a scenario where the episodic accretion is followed by an episodic ejection response in the near infrared, as was seen in the earlier radio follow-up. The ~2 µm photometry from the past 30 yr suggests that NIRS3 might have undergone another outburst in the late 1980s, making it the first massive protostar with such evidence observed in the near infrared. 

Engineering in early education provides the foundation for the future of innovation. Reinforcing learning and engineering habits of mind (HoM) at an early age is crucial for expanding students’ higher order thinking, potential for lifelong learning, and sense of agency in their learning experiences. HoM is defined as a set of learned or internalized dispositions that inform an individual's behaviors when confronted with challenges. This study addressed two research questions: (1) Which HoM were articulated by children as they reflected upon their participation in a home-based engineering program? (2) What patterns of the children’s vocabulary align with the HoM framework? Observational methods were used to examine young children’s reflections upon the process of completing low-stakes engineering projects in their home. The participants were 23 children ranging from kindergarten to eighth grade. After they engaged in the ill-structured engineering tasks with family members at home, children joined an online show-and-tell meeting to show their prototype to others while answering various questions about their processes, frustrations, and successes. Findings revealed “Resourcefulness,” “Adapting/Improving,” and “Systems Thinking” as the most common HoM expressed by children through the show-and-tell meetings. Additional analysis also highlighted how children's articulation of learning and engineering habits of mind were logical (i.e., analytical), confident (i.e., clout), and impersonal. Moreover, children’s words were product oriented, predominantly focusing on the materials and tools utilized to create their prototype. The significance of this study highlights how engaging in hands-on engineering projects in the home has the potential to develop children’s dispositions and ways of thinking common to engineers. 

Implicit neural representations (INRs) have recently advanced numerous vision-related areas. INR performance depends strongly on the choice of activation function employed in its MLP network. A wide range of nonlinearities have been explored, but, unfortunately, current INRs designed to have high accuracy also suffer from poor robustness (to signal noise, parameter variation, etc.). Inspired by harmonic analysis, we develop a new, highly accurate and robust INR that does not exhibit this tradeoff. Our Wavelet Implicit neural REpresentation (WIRE) uses as its activation function the complex Gabor wavelet that is well-known to be optimally concentrated in space–frequency and to have excellent biases for representing images. A wide range of experiments (image denoising, image inpainting, super-resolution, computed tomography reconstruction, image overfitting, and novel view synthesis with neural radiance fields) demonstrate that WIRE defines the new state of the art in INR accuracy, training time, and robustness. 

Implicit neural representations (INRs) have recently advanced numerous vision-related areas. INR performance depends strongly on the choice of activation function employed in its MLP network. A wide range of nonlinearities have been explored, but, unfortunately, current INRs designed to have high accuracy also suffer from poor robustness (to signal noise, parameter variation, etc.). Inspired by harmonic analysis, we develop a new, highly accurate and robust INR that does not exhibit this tradeoff. Our Wavelet Implicit neural REpresentation (WIRE) uses as its activation function the complex Gabor wavelet that is well-known to be optimally concentrated in space–frequency and to have excellent biases for representing images. A wide range of experiments (image denoising, image inpainting, super-resolution, computed tomography reconstruction, image overfitting, and novel view synthesis with neural radiance fields) demonstrate that WIRE defines the new state of the art in INR accuracy, training time, and robustness.