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Abstract Developing algorithms to search through data efficiently is a challenging part of searching for signs of technology beyond our solar system. We have built a digital signal processing system and computer cluster on the backend of the Karl G. Jansky Very Large Array (VLA) in New Mexico in order to search for signals throughout the Galaxy consistent with our understanding of artificial radio emissions. In our first paper, we described the system design and software pipelines. In this paper, we describe a postprocessing pipeline to identify persistent sources of interference, filter out false positives, and search for signals not immediately identifiable as anthropogenic radio frequency interference during the VLA Sky Survey. As of 2024 September 1, the Commensal Open-source Multi-mode Interferometric Cluster had observed more than 950,000 unique pointings. This paper presents the strategy we employ when commensally observing during the VLA Sky Survey and a postprocessing strategy for the data collected during the survey. To test this postprocessing pipeline, we searched toward 511 stars from the Gaia catalog with coherent beams. This represents about 30 minutes of observation during the VLA Sky Survey, where we typically observe about 2000 sources hr^–1in the coherent beamforming mode. We did not detect any unidentifiable signals, setting isotropic power limits ranging from 10¹¹to 10¹⁶W. 

The dynamics of a soft particle suspended in a viscous fluid can be changed by the presence of an elastic boundary. Understanding the mechanisms and dynamics of soft–soft surface interactions can provide valuable insights into many important research fields, including biomedical engineering, soft robotics development, and materials science. This work investigates the anomalous transport properties of a soft nanoparticle near a visco-elastic interface, where the particle consists of a polymer assembly in the form of a micelle and the interface is represented by a lipid bilayer membrane. Mesoscopic simulations using a dissipative particle dynamics model are performed to examine the impact of micelle’s proximity to the membrane on its Brownian motion. Two different sizes are considered, which correspond to ≈10−20nm in physical units. The wavelengths typically seen by the largest micelle fall within the range of wavenumbers where the Helfrich model captures fairly well the bilayer mechanical properties. Several independent simulations allowed us to compute the micelle trajectories during an observation time smaller than the diffusive time scale (whose order of magnitude is similar to the membrane relaxation time of the largest wavelengths), this time scale being hardly accessible by experiments. From the probability density function of the micelle normal position with respect to the membrane, it is observed that the position remains close to the starting position during ≈0.05τd (where τd corresponds to the diffusion time), which allowed us to compare the negative excess of mean-square displacement (MSD) to existing theories. In that time range, the MSD exhibits different behaviors along parallel and perpendicular directions. When the micelle is sufficiently close to the bilayer (its initial distance from the bilayer equals approximately twice its gyration radius), the micelle motion becomes quickly subdiffusive in the normal direction. Moreover, the temporal evolution of the micelle MSD excess in the perpendicular direction follows that of a nanoparticle near an elastic membrane. However, in the parallel direction, the MSD excess is rather similar to that of a nanoparticle near a liquid interface. 

Designing alloys for additive manufacturing (AM) presents significant opportunities. Still, the chemical composition and processing conditions required for printability (ie., their suitability for fabrication via AM) are challenging to explore using solely experimental means. In this work, we develop a high-throughput (HTP) computational framework to guide the search for highly printable alloys and appropriate processing parameters. The framework uses material properties from stateof- the-art databases, processing parameters, and simulated melt pool profiles to predict processinduced defects, such as lack-of-fusion, keyholing, and balling. We accelerate the printability assessment using a deep learning surrogate for a thermal model, enabling a 1,000-fold acceleration in assessing the printability of a given alloy at no loss in accuracy when compared with conventional physics-based thermal models. We verify and validate the framework by constructing printability maps for the CoCrFeMnNi Cantor alloy system and comparing our predictions to an exhaustive ’in-house’ database. The framework enables the systematic investigation of the printability of a wide range of alloys in the broader Co-Cr-Fe-Mn-Ni HEA system. We identified the most promising alloys that were suitable for high-temperature applications and had the narrowest solidification ranges, and that was the least susceptible to balling, hot-cracking, and the formation of macroscopic printing defects. A new metric for the global printability of an alloy is constructed and is further used for the ranking of candidate alloys. The proposed framework is expected to be integrated into ICME approaches to accelerate the discovery and optimization of novel high-performance, printable alloys. 

A broad spectrum of well-graded, coarse-grained soils are commonly present in natural deposits, though characterization of these materials has been approximated using sand-based engineering methods in liquefaction evaluations. Through combined results of 31 constant stress direct simple shear and drained triaxial compression tests, this study experimentally investigates the effect of mean grain size (D50) and gradation (Cu) on the drained monotonic strength and stress-dilatancy of poorly- to well-graded, coarse-grained soils. Coarse-grained mixtures of varying D50 and gradations were prepared to relative densities of 20%–75% and tested under a range of overburden stresses. Results are analyzed in terms of the frictional resistance and dilative contributions to the shear strength of soils with varying gradations, as compared to clean sands, using different shearing modes. It is shown that (1) increased gradation of soils increases the peak shear strength and frictional resistance due to a greater initial rate of dilation exhibited in well-graded, coarse-grained soils; and (2) current stress-dilatancy relationships underestimate the dilative behavior of well-graded test materials.