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Elaborate traits evolve via intense selective pressure, overpowering ecological constraints. Hindwing tails that thwart bat attack have repeatedly originated in moon moths (Saturniidae), with longer tails having greater anti-predator effect. Here, we take a macroevolutionary approach to evaluate the evolutionary balance between predation pressure and possible limiting environmental factors on tail elongation. To trace the evolution of tail length across time and space, we inferred a time-calibrated phylogeny of the entirely tailed moth group (Actias + Argema) and performed ancestral state reconstruction and biogeographical analyses. We generated metrics of predation via estimates of bat abundance from nearly 200 custom-built species distribution models and environmental metrics via estimates of bioclimatic variables associated with individual moth observations. To access community science data, we developed a novel method for measuring wing lengths from un-scaled photos. Integrating these data into phylogenetically informed mixed models, we find a positive association between bat predation pressure and moth tail length and body size, and a negative association between environmental factors and these morphological traits. Regions with more insectivorous bats and more consistent temperatures tend to host longer-tailed moths. Our study provides insight into tradeoffs between biotic selective pressures and abiotic constraints that shape elaborate traits across the tree of life. 

Significance: Laparoscopic surgery presents challenges in localizing oncological margins due to poor contrast between healthy and malignant tissues. Optical properties can uniquely identify various tissue types and disease states with high sensitivity and specificity, making it a promising tool for surgical guidance. Although spatial frequency domain imaging (SFDI) effectively measures quantitative optical properties, its deployment in laparoscopy is challenging due to the constrained imaging environment. Thus, there is a need for compact structured illumination techniques to enable accurate, quantitative endogenous contrast in minimally invasive surgery. Aim: We introduce a compact, two-camera laparoscope that incorporates both active stereo depth estimation and speckle-illumination SFDI (si-SFDI) to map profile-corrected, pixel-level absorption (μa), and reduced scattering (μ′s) optical properties in images of tissues with complex geometries. Approach: We used a multimode fiber-coupled 639-nm laser illumination to generate high-contrast speckle patterns on the object. These patterns were imaged through a modified commercial stereo laparoscope for optical property estimation via si-SFDI. Compared with the original si-SFDI work, which required ≥10 images of randomized speckle patterns for accurate optical property estimations, our approach approximates the DC response using a laser speckle reducer (LSR) and consequently requires only two images. In addition, we demonstrate 3D profilometry using active stereo from low-coherence RGB laser flood illumination. Sample topography was then used to correct for measured intensity variations caused by object height and surface angle differences with respect to a calibration phantom. The low-contrast RGB speckle pattern was blurred using an LSR to approximate incoherent white light illumination. We validated profile-corrected si-SFDI against conventional SFDI in phantoms with simple and complex geometries, as well as in a human finger in vivo time-series constriction study. Results: Laparoscopic si-SFDI optical property measurements agreed with conventional SFDI measurements when measuring flat tissue phantoms, exhibiting an error of 6.4% for absorption and 5.8% for reduced scattering. Profile-correction improved the accuracy for measurements of phantoms with complex geometries, particularly for absorption, where it reduced the error by 23.7%. An in vivo finger constriction study further validated laparoscopic si-SFDI, demonstrating an error of 8.2% for absorption and 5.8% for reduced scattering compared with conventional SFDI. Moreover, the observed trends in optical properties due to physiological changes were consistent with previous studies. Conclusions: Our stereo-laparoscopic implementation of si-SFDI provides a simple method to obtain accurate optical property maps through a laparoscope for flat and complex geometries. This has the potential to provide quantitative endogenous contrast for minimally invasive surgical guidance. 

Abstract Cobalt phthalocyanine (CoPc) is a promising molecular catalyst for aqueous electroreduction of CO₂, but its catalytic activity is limited by aggregation at high loadings. Codeposition of CoPc onto electrode surfaces with the coordinating polymer poly(4‐vinylpyridine) (P4VP) mitigates aggregation in addition to providing other catalytic enhancements. Transmission and diffuse reflectance UV–vis measurements demonstrate that a combination of axial coordination and π‐stacking effects from pyridyl moieties in P4VP serve to disperse cobalt phthalocyanine in deposition solutions and help prevent reaggregation in deposited films. Polymers lacking axial coordination, such as Nafion, are significantly less effective at cobalt phthalocyanine dispersion in both the deposition solution and in the deposited films. SEM images corroborate these findings through particle counts and morphological analysis. Electrochemical measurements show that CoPc codeposited with P4VPonto carbon electrode surfaces reduces CO₂with higher activity and selectivity compared to the catalyst codeposited with Nafion. 

We present a unifying framework that allows us to study the mixed crystalline-electromagnetic responses of topological semimetals in spatial dimensions up to $D=3$through dimensional augmentation and reduction procedures. We show how this framework illuminates relations between the previously known topological semimetals and use it to identify a new class of quadrupolar nodal line semimetals for which we construct a lattice tight-binding Hamiltonian. We further utilize this framework to quantify a variety of mixed crystalline-electromagnetic responses, including several that have not previously been explored in existing literature, and show that the corresponding coefficients are universally proportional to weighted momentum-energy multipole moments of the nodal points (or lines) of the semimetal. We introduce lattice gauge fields that couple to the crystal momentum and describe how tools including the gradient expansion procedure, dimensional reduction, compactification, and the Kubo formula can be used to systematically derive these responses and their coefficients. We further substantiate these findings through analytical physical arguments, microscopic calculations, and explicit numerical simulations employing tight-binding models. Published by the American Physical Society2024 

ABSTRACT Chromosomal inversions are an important class of genetic variation that link multiple alleles together into a single inherited block that can have important effects on fitness. To study the role of large inversions in the massive evolutionary radiation of Lake Malawi cichlids, we used long-read technologies to identify four single and two tandem inversions that span half of each respective chromosome, and which together encompass over 10% of the genome. Each inversion is fixed in one of the two states within the seven major ecogroups, suggesting they played a role in the separation of the major lake lineages into specific lake habitats. One exception is within the benthic sub-radiation, where both inverted and non-inverted alleles continue to segregate within the group. The evolutionary histories of three of the six inversions suggest they transferred from the pelagic Diplotaxodon group into benthic ancestors at the time the benthic sub-radiation was seeded. The remaining three inversions are found in a subset of benthic species living in deep waters. We show that some of these inversions are used as XY sex-determination systems but are also likely limited to a subset of total lake species. Our work suggests that inversions have been under both sexual and natural selection in Lake Malawi cichlids and that they will be important to understanding how this adaptive radiation evolved. 

Quantum computation shows promise for addressing numerous classically intractable problems, such as optimization tasks. Many optimization problems are NP-hard, meaning that they scale exponentially with problem size and thus cannot be addressed at scale by traditional computing paradigms. The recently proposed quantum algorithm arXiv:2206.14999 addresses this challenge for some NP-hard problems, and is based on classical semidefinite programming (SDP). In this manuscript, we generalize the SDP-inspired quantum algorithm to sum-of-squares programming, which targets a broader problem set. Our proposed algorithm addresses degree- polynomial optimization problems with variables (which are representative of many NP-hard problems) using qubits, quantum measurements, and classical calculations. We apply the proposed algorithm to the prototypical Max-SAT problem and compare its performance against classical sum-of-squares, state-of-the-art heuristic solvers, and random guessing. Simulations show that the performance of our algorithm surpasses that of classical sum-of-squares after rounding. Our results further demonstrate that our algorithm is suitable for large problems and approximates the best known classical heuristics, while also providing a more generalizable approach compared to problem-specific heuristics. 

We introduce a quantum information theory-inspired method to improve the characterization of many-body Hamiltonians on near-term quantum devices. We design a new class of similarity transformations that, when applied as a preprocessing step, can substantially simplify a Hamiltonian for subsequent analysis on quantum hardware. By design, these transformations can be identified and applied efficiently using purely classical resources. In practice, these transformations allow us to shorten requisite physical circuit-depths, overcoming constraints imposed by imperfect near-term hardware. Importantly, the quality of our transformations is $tunable$: we define a 'ladder' of transformations that yields increasingly simple Hamiltonians at the cost of more classical computation. Using quantum chemistry as a benchmark application, we demonstrate that our protocol leads to significant performance improvements for zero and finite temperature free energy calculations on both digital and analog quantum hardware. Specifically, our energy estimates not only outperform traditional Hartree-Fock solutions, but this performance gap also consistently widens as we tune up the quality of our transformations. In short, our quantum information-based approach opens promising new pathways to realizing useful and feasible quantum chemistry algorithms on near-term hardware.