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Abstract The testing and quality assurance of cryogenic superconducting detectors is a time- and labor-intensive process. As experiments deploy increasingly larger arrays of detectors, new methods are needed for performing this testing quickly. Here, we propose a process for flagging under-performing detector wafers before they are ever tested cryogenically. Detectors are imaged under an optical microscope, and computer vision techniques are used to analyze the images, searching for visual defects and other predictors of poor performance. Pipeline performance is verified via a suite of images with simulated defects, yielding a detection accuracy of 98.6%. Lastly, results from running the pipeline on prototype microwave kinetic inductance detectors from the planned SPT-3G+ experiment are presented. 

The Cornell Agricultural Systems Testbed and Demonstration site (CAST) for the Farm of the Future is a testbed and demonstration site for data-driven technologies and management practices where coordinated technology development, testing, demonstration, systematic integration of data, and exchanges of physical materials and ideas are shaping the Farm of the Future. CAST is a cluster of three farms in NY State that hosts data-driven research, extension, and education for crops and dairy production under the aegis of the Cornell Institute for Digital Agriculture. CAST advances climate-smart data-driven solutions for food systems, integrating commercially available and in-the-pipeline technologies and transformative practices. 

The Cornell Agricultural Systems Testbed and Demonstration site (CAST) for the Farm of the Future is a testbed and demonstration site for data-driven technologies and management practices where coordinated technology development, testing, demonstration, systematic integration of data, and exchanges of physical materials and ideas are shaping the Farm of the Future. CAST is a cluster of three farms in NY State that hosts data-driven research, extension, and education for crops and dairy production under the aegis of the Cornell Institute for Digital Agriculture. CAST advances climate-smart data-driven solutions for food systems, integrating commercially available and in-the-pipeline technologies and transformative practices. 

Sea turtles are one taxon of high conservation concern that encounter many pathogens, but their disease ecology is understudied, hindering our ability to predict impacts of disease on population viability. Fibropapillomatosis (FP) is a neoplastic tumor-forming disease that has been documented in all sea turtle species, with an especially high prevalence in green turtlesChelonia mydas.Here, we use Hawaiian green turtles (honu) as a study system to examine the roles of immunogenetic diversity and transcriptional modulation in sea turtle disease responses. Specifically, we quantified gene expression profiles associated with FP and characterized host diversity of major histocompatibility complex class I (MHCI) immune loci. We found 65 genes differentially expressed in blood between clinically healthy (n = 5) and FP-afflicted turtles (n = 5) with enriched biological processes of the innate immune system, aligned with expectations of reptilian immune systems and active disease resistance. Our results also suggest a role for disease tolerance in response to FP, as evidenced by enriched biological processes related to regulation of immune and metabolic homeostasis, increase in cellular detoxification, and increased tissue repair mechanisms. Honu (n = 89) had 23 unique MHCI alleles belonging to 3 distinct functional supertypes, but none were significantly associated with FP; this could be a result of intrinsic demographic properties of the population or reflect a lesser/differing role of the reptilian adaptive immune system. Our study advances the understanding of reptilian disease response and evolutionary mechanisms underlying immunogenetic diversity, both of which are important for promoting the adaptive potential of species vulnerable to extinction. 

Global climate change phenomena are amplified in Arctic regions, driving rapid changes in the biota. Here, we examine changes in plant community structure over more than 30 years at two sites in arctic Alaska, USA, Imnavait Creek and Toolik Lake, to understand long-term trends in tundra response to changing climate. Vegetation cover was sampled every 4-7 years on permanent 1 m2 plots spanning a 1 km2 grid using a point-frame. The vascular plant canopies progressively closed at both locations. Canopy cover, defined here as an encounter of a vascular plant above the ground surface, increased from 63% to 91% at Imnavait Creek and from 63% to 89% at Toolik Lake. Both sites showed steady increases in maximum canopy height, increasing by approximately 50% (8 cm). While cover and height increased to some extent for all vascular plant growth forms, deciduous shrubs and graminoids changed the most. For example, at Imnavait Creek the cover of graminoids more than tripled (particularly in wet meadow plots), increasing by 237%. At Toolik Lake the cover of deciduous shrubs more than doubled (particularly in moist acidic plots), increasing by 145%. Despite the steady closing of the plant canopy, cryptogams (lichens and mosses) persisted; in fact, the cover of lichens increased. These results call into question the dominant dogma that cryptogams will decline with increases in vascular plant abundance and demonstrate the resilience of these understory plants. In addition to overall cover, the diversity of vascular plants increased at one site (Imnavait Creek). In contrast to much of the Arctic, summer air temperatures in the Toolik Lake region have not significantly increased over the 30+ year sampling period; however, winter temperatures increased substantially. Changes in vegetation community structure at Imnavait Creek and Toolik Lake are likely the result of winter warming.