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The small bodies in the Kuiper Belt region of the distant Solar System are leftovers from planet formation. Their orbital distribution today tells us about how giant planets migrated, while their surface properties, shapes, and sizes tell us about formation processes and collision rates. Probing these intrinsic properties requires a careful understanding of the observational biases that are a part of any telescopic survey that discovers small bodies. While many of the details of giant planet migration are now understood due to careful comparison between de-biased discoveries in the Kuiper Belt and computational simulations, some discoveries have orbits that are still not easy to explain. Upcoming surveys such as the planned survey on Vera Rubin Observatory will help us to leverage the Kuiper Belt and refine our knowledge about the formation and dynamical history of our own Solar System., Comment: Preprint of a chapter for the 'Encyclopedia of Astrophysics' (Editor-in-Chief Ilya Mandel, Section Editor Dimitri Veras) to be published by Elsevier as a Reference Module

We measure the response of open-cell polyurethane foams filled with a dense suspension of fumed silica particles in polyethylene glycol at compression speeds spanning several orders of magnitude. The gradual compressive stress increase of the composite material indicates the existence of shear rate gradients in the interstitial suspension caused by wide distributions in pore sizes in the disordered foam network. The energy dissipated during compression scales with an effective internal shear rate, allowing for the collapse of three data sets for different pore-size foams. When scaled by this effective shear rate, the most pronounced energy increase coincides with the effective shear rate corresponding to the onset of shear thickening in our bulk suspension. Optical measurements of the radial deformation of the foam network and of the suspension flow under compression provide additional insight into the interaction between shear thickening fluid and foam. This optical data, combined with a simple model of a spring submerged in viscous flow, illustrates the dynamic interaction of viscous drag with foam elasticity as a function of compression rate, and identifies the foam pore size distribution as a critically important model parameter. Taken together, the stress measurements, dissipated energy, and relative motion of the fluid and the foam can be rationalized by knowing the pore size distribution and the average pore size of the foam.

Decentralized diagnostic testing that is accurate, portable, quantitative, and capable of making multiple simultaneous measurements of different biomarkers at the point-of-need remains an important unmet need in the post-pandemic world. Resonator-based biosensors using silicon photonic integrated circuits are a promising technology to meet this need, as they can leverage (1) semiconductor manufacturing economies of scale, (2) exquisite optical sensitivity, and (3) the ability to integrate tens to hundreds of sensors on a millimeter-scale photonic chip. However, their application to decentralized testing has historically been limited by the expensive, bulky tunable lasers and alignment optics required for their readout. In this work, we introduce a segmented sensor architecture that addresses this important challenge by facilitating resonance-tracking readout using a fixed-wavelength laser. The architecture incorporates an in-resonator phase shifter modulated by CMOS drivers to periodically sweep and acquire the resonance peak shifts as well as a distinct high-sensitivity sensing region, maintaining high performance at a fraction of the cost and size. We show, for the first time, that fixed-wavelength sensor readout can offer similar performance to traditional tunable laser readout, demonstrating a system limit of detection of 6.1 x 10-5 RIU as well as immunoassay-based detection of the SARS-CoV-2 spike protein. We anticipate that this sensor architecture will open the door to a new data-rich class of portable, accurate, multiplexed diagnostics for decentralized testing.

Globally, vector-borne diseases are increasing in distribution and frequency, affecting humans, domestic animals and livestock, and wildlife. Science-based management and prevention of these diseases requires a sound understanding of the distribution and environmental requirements of the vectors and hosts involved in disease transmission. Integrated Species Distribution Models (ISDM) account for diverse data types through hierarchical modeling and represent a significant advancement in species distribution modeling that have not yet been leveraged in disease ecology. We used this approach, as implemented in the recently developed R package RISDM, to assess the distribution of the soft tick subspecies Ornithodoros turicata americanus. We created an ISDM for O. t. americanus, using systematically collected field data and historical records of this tick species in the southeastern US, to predict its distribution and assess potential correlations with environmental variables. Given the novelty of this method, we compared the results to a conventional Maxent SDM and validated the results through data partitioning using true skills statistics (TSS), sensitivity, and area under the ROC curve (AUC) metrics. We found that a combination of climatic variables describing seasonality and temperature extremes, along with the amount of sand in the soil, determined the predicted intensity of occurrence of this tick species. When projected in geographic space, this distribution model predicted 62% of Florida as suitable habitat for this tick species. The ISDM presented a higher TSS and AUC than the Maxent conventional model, while sensitivity was similar between both models. Our case example shows the utility of ISDMs in disease ecology studies and highlights the broad range of geographic suitability for this important disease vector.

Axions are a well-motivated dark matter candidate particle. Haloscopes aim to detect axions in the galactic halo by measuring the photon signal resulting from axions interacting with a strong magnetic field. Existing haloscopes are primarily targeting axion masses which produce microwave-range photons and rely on microwave resonators to enhance the signal power. Only a limited subset of resonator modes are useful for this process, and current cylindrical-style cavities suffer from mode mixing and crowding from other fundamental modes. The majority of these modes can be eliminated by using photonic band gap (PBG) resonators. The band gap behavior of these structures allows for a resonator with mode selectivity based on frequency. We present results from the first tunable PBG resonator, a proof-of-concept design with a footprint compatible with axion haloscopes. We have thoroughly characterized the tuning range of two versions of the structure and report the successful confinement of the operating TM$_{010}$ mode and the elimination of all TE modes within the tuning range., Comment: 7 pages, 8 figures

Identifying areas in a landscape where individuals have higher probability of becoming infected with a pathogen is a crucial step towards disease management. We perform a novel epidemiological tomography for the estimation of landscape propensity to disease infection, using GPS animal tracks in a manner analogous to tomographic techniques in Positron Emission Tomography. Our study data consists of individual tracks of white-tailed deer (Odocoileus virginianus) and three exotic Cervidae species moving freely in a high-fenced game preserve over given time periods. A serological test was performed on each individual to measure antibody concentration of epizootic hemorrhagic disease viruses (EHDV) at the beginning and at the end of each tracking period. EHDV is a vector-borne viral disease indirectly transmitted between ruminant hosts by biting midges. We model the data as a binomial linear inverse problem, where spatial coherence is enforced with a total variation regularization. The smoothness of the reconstructed propensity map is selected by the quantile universal threshold, which can also test the null hypothesis that the propensity map is spatially constant. We apply our method to simulated and real data, showing good statistical properties during simulations and consistent results and interpretations compared to intensive field estimations.

On 8 April 2024, tens of millions of people across North America will be able to view a total solar eclipse. Such astronomical events have been important throughout history, but with nearly 10,000 satellites in orbit, we question whether total eclipses will now reveal a sky full of satellites, fundamentally changing this experience for humanity. Using the current population of Starlink satellites, we find that the brightest satellites would be naked-eye visible in dark skies, but the high sky brightness during totality will make them undetectable to the unaided eye. Our model does not take into account the effects of chance reflections from large, flat surfaces like solar panels, which we expect will cause glints and flares that could be visible from large satellites and abandoned rocket bodies. Time-lapse all-sky imaging might reveal satellites during the eclipse., Comment: submitted to RNAAS

Newborn animals have advanced perceptual skills at birth, but the nature of this initial knowledge is unknown. Is initial knowledge flexible, continuously adapting to the statistics of experience? Or can initial knowledge be rigid and robust to change, even in the face of opposing evidence? We address this question through controlled-rearing experiments on newborn chicks. First, we reared chicks in an impoverished virtual world, where objects never occluded one another, and found that chicks still succeed on object permanence tasks. Second, we reared chicks in a virtual world in which objects teleported from one location to another while out of view: an unnatural event that violates the continuity of object motion. Despite seeing thousands of these violations of object permanence, and not a single non-violation, the chicks behaved as if object permanence were true, exhibiting the same behavior as chicks reared with natural object permanence events. We conclude that object permanence develops prenatally and is robust to change from opposing evidence., Comment: 10 pages, 4 figures

The Hunting Outbursting Young Stars (HOYS) project performs long-term, optical, multi-filter, high cadence monitoring of 25 nearby young clusters and star forming regions. Utilising Gaia DR3 data we have identified about 17000 potential young stellar members in 45 coherent astrometric groups in these fields. Twenty one of them are clear young groups or clusters of stars within one kiloparsec and they contain 9143 Gaia selected potential members. The cluster distances, proper motions and membership numbers are determined. We analyse long term (about 7yr) V, R, and I-band light curves from HOYS for 1687 of the potential cluster members. One quarter of the stars are variable in all three optical filters, and two thirds of these have light curves that are symmetric around the mean. Light curves affected by obscuration from circumstellar materials are more common than those affected by accretion bursts, by a factor of 2-4. The variability fraction in the clusters ranges from 10 to almost 100 percent, and correlates positively with the fraction of stars with detectable inner disks, indicating that a lot of variability is driven by the disk. About one in six variables shows detectable periodicity, mostly caused by magnetic spots. Two thirds of the periodic variables with disk excess emission are slow rotators, and amongst the stars without disk excess two thirds are fast rotators - in agreement with rotation being slowed down by the presence of a disk., Comment: accepted for publication in MNRAS, 1 table, 9 figures

Vision transformers (ViTs) are top performing models on many computer vision benchmarks and can accurately predict human behavior on object recognition tasks. However, researchers question the value of using ViTs as models of biological learning because ViTs are thought to be more data hungry than brains, with ViTs requiring more training data to reach similar levels of performance. To test this assumption, we directly compared the learning abilities of ViTs and animals, by performing parallel controlled rearing experiments on ViTs and newborn chicks. We first raised chicks in impoverished visual environments containing a single object, then simulated the training data available in those environments by building virtual animal chambers in a video game engine. We recorded the first-person images acquired by agents moving through the virtual chambers and used those images to train self supervised ViTs that leverage time as a teaching signal, akin to biological visual systems. When ViTs were trained through the eyes of newborn chicks, the ViTs solved the same view invariant object recognition tasks as the chicks. Thus, ViTs were not more data hungry than newborn visual systems: both learned view invariant object representations in impoverished visual environments. The flexible and generic attention based learning mechanism in ViTs combined with the embodied data streams available to newborn animals appears sufficient to drive the development of animal-like object recognition., Comment: Accepted in Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)

Throughout the history of electron microscopy, ribosomes have served as an ideal subject for imaging and technological development, which in turn has driven our understanding of ribosomal biology. Here, we provide a historical perspective at the intersection of electron microscopy technology development and ribosome biology and reflect on how this technique has shed light on each stage of the life cycle of this dynamic macromolecular machine. With an emphasis on prokaryotic systems, we specifically describe how pairing cryo-EM with clever experimental design, time-resolved techniques, and next-generation heterogeneous structural analysis has afforded insights into the modular nature of assembly, the roles of the many transient biogenesis and translation co-factors, and the subtle variations in structure and function between strains and species. The work concludes with a prospective outlook on the field, highlighting the pivotal role cryogenic electron tomography is playing in adding cellular context to our understanding of ribosomal life cycles, and noting how this exciting technology promises to bridge the gap between cellular and structural biology., Comment: 15 pages, 6 figures

Recent progress in artificial intelligence has renewed interest in building machines that learn like animals. Almost all of the work comparing learning across biological and artificial systems comes from studies where animals and machines received different training data, obscuring whether differences between animals and machines emerged from differences in learning mechanisms versus training data. We present an experimental approach-a "newborn embodied Turing Test"-that allows newborn animals and machines to be raised in the same environments and tested with the same tasks, permitting direct comparison of their learning abilities. To make this platform, we first collected controlled-rearing data from newborn chicks, then performed "digital twin" experiments in which machines were raised in virtual environments that mimicked the rearing conditions of the chicks. We found that (1) machines (deep reinforcement learning agents with intrinsic motivation) can spontaneously develop visually guided preference behavior, akin to imprinting in newborn chicks, and (2) machines are still far from newborn-level performance on object recognition tasks. Almost all of the chicks developed view-invariant object recognition, whereas the machines tended to develop view-dependent recognition. The learning outcomes were also far more constrained in the chicks versus machines. Ultimately, we anticipate that this approach will help researchers develop embodied AI systems that learn like newborn animals., Comment: 7 Pages. 4 figures, 1 table. This paper was accepted to the CogSci 2023 Conference. (https://cognitivesciencesociety.org/)