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Müllerian mimicry and the coloration patterns of sympatric coral snakes
Abstract Coral snakes in the genus Micrurus are venomous, aposematic organisms that signal danger to predators through vivid coloration. Previous studies found that they serve as models to several harmless species of Batesian mimics. However, the extent to which Micrurus species engage in Müllerian mimicry remains poorly understood. We integrate detailed morphological and geographical distribution data to investigate if coral snakes are Müllerian mimics. We found that coloration is spatially structured and that Micrurus species tend to be more similar where they co-occur. Though long supposed, we demonstrate for the first time that coral snakes might indeed be Müllerian mimics as they show some convergence in coloration patterns. Additionally, we found that the length of red-coloured rings in Micrurus is conserved, even at large geographic scales. This finding suggests that bright red rings may be under more substantial stabilizing selection than other aspects of coloration and probably function as a generalized signal for deterring predators.
Impact of Color Space and Color Resolution on Vehicle Recognition Models
In this study, we analyze both linear and nonlinear color mappings by training on versions of a curated dataset collected in a controlled campus environment. We experiment with color space and color resolution to assess model performance in vehicle recognition tasks. Color encodings can be designed in principle to highlight certain vehicle characteristics or compensate for lighting differences when assessing potential matches to previously encountered objects. The dataset used in this work includes imagery gathered under diverse environmental conditions, including daytime and nighttime lighting. Experimental results inform expectations for possible improvements with automatic color space selection through feature learning. Moreover, we find there is only a gradual decrease in model performance with degraded color resolution, which suggests the need for simplified data collection and processing. By focusing on the most critical features, we could see improved model generalization and robustness, as the model becomes less prone to overfitting to noise or irrelevant details in the data. Such a reduction in resolution will lower computational complexity, leading to quicker training and inference times.
Color–color diagrams as tools for assessment of the variable absorption in high mass X-ray binaries
High mass X-ray binaries hold the promise of allowing us to understand the structure of the winds of their supermassive companion stars by using the emission from the compact object as a backlight to evaluate the variable absorption in the structured stellar wind. The wind along the line of sight can change on timescales as short as minutes and below. However, such short timescales are not available for the direct measurement of absorption through X-ray spectroscopy with the current generation of X-ray telescopes. In this paper, we demonstrate the usability of color–color diagrams for assessing the variable absorption in wind accreting high mass X-ray binary systems. Furthermore, we employ partial covering models to describe the spectral shape of high mass X-ray binaries and assess the implication of different absorbers and their variability on the shape of color–color tracks. We show that in taking into account, the ionization of the absorber, and in particular accounting for the variation of ionization with absorption depth, is crucial to describe the observed behavior well.
Viability, behavior, and color expression in the offspring of matings between common wall lizard Podarcis muralis color morphs
Abstract Color polymorphisms are widely studied to identify the mechanisms responsible for the origin and maintenance of phenotypic variability in nature. Two of the mechanisms of balancing selection currently thought to explain the long-term persistence of polymorphisms are the evolution of alternative phenotypic optima through correlational selection on suites of traits including color and heterosis. Both of these mechanisms can generate differences in offspring viability and fitness arising from different morph combinations. Here, we examined the effect of parental morph combination on fertilization success, embryonic viability, newborn quality, antipredator, and foraging behavior, as well as inter-annual survival by conducting controlled matings in a polymorphic lacertid Podarcis muralis, where color morphs are frequently assumed to reflect alternative phenotypic optima (e.g., alternative reproductive strategies). Juveniles were kept in outdoor tubs for a year in order to study inter-annual growth, survival, and morph inheritance. In agreement with a previous genome-wide association analysis, morph frequencies in the year-old juveniles matched the frequencies expected if orange and yellow expressions depended on recessive homozygosity at 2 separate loci. Our findings also agree with previous literature reporting higher reproductive output of heavy females and the higher overall viability of heavy newborn lizards, but we found no evidence for the existence of alternative breeding investment strategies in female morphs, or morph-combination effects on offspring viability and behavior. We conclude that inter-morph breeding remains entirely viable and genetic incompatibilities are of little significance for the maintenance of discrete color morphs in P. muralis from the Pyrenees.
Structural color from a coupled nanowire pair beyond the bonding and antibonding model
Optical resonances in nanostructures can be harnessed to produce a wide range of structural colors. Conversely, the analysis of structural colors has been used to clarify the nature of optical resonances. Here, we show that silicon nanowire (NW) pairs can display a wide range of structural colors by controlling their radiative coupling. This is accomplished by exciting a series of Fabry–Pérot-like modes where light is repeatedly scattered between two NWs. These modes are beyond the expectation from the conventional chemical bonding model under a quasi-electrostatic approximation, in which only bonding and antibonding modes can be formed in a pair system through modal hybridization. The additional eigenmodes found in a two-resonator system originate from the nonlinear, frequency-dependent coupling strength derived from the radiative nature of low- Q resonators. The Fabry–Pérot modes can be tuned across the entire visible frequency range by varying the distance between two NWs, leading to what we believe is a new type of universal building blocks that can provide structural color within a subwavelength footprint. The presented results pave the way toward the design and usage of highly tunable resonances that exploit the radiative coupling of high-index nanostructures.
A Challenge for Discrimination of Color-Singlet versus Color-Octet Quarkonium Production
The precise mechanism for production of quarkonium at hadron colliders is still an open question. Within non-relativistic quantum chromodynamics, quarkonium production cross sections can be factorized into short-distance, perturbative contributions and universal, non-perturbative, long-distance matrix elements, and then summed over quantum numbers of the heavy quark pair. In principle, at short-distances, the heavy quark pair can be either in a color-singlet or color-octet state, and it is desirable to establish the relative contributions to compare with data and to make predictions in different experimental environments. From the explicit form of the lowest-order perturbative matrix elements for color-singlet and color-octet production, we show that the structure of the optimal observable for discrimination on phase space, the likelihood ratio, has strong dependence on the angular momentum state of the heavy quark pair. This presents an obstruction for construction of a single, robust discrimination observable that can be applied to production of an arbitrary quarkonium state.
Correlating dynamic microstructure to observed color in electrophoretic displays via in situ small-angle x-ray scattering
Electrophoretic deposition (EPD) is an industrially relevant and scalable technique used to form particle deposits from colloidal suspensions. Highly concentrated particle suspensions generally prevent real-time in situ microscopy observations which limit the characterization of EPD films to ex situ, or postprocessed, laboratory techniques. For dynamic systems, such as tunable amorphous photonic crystals (APCs), only reversible deposits are formed during the EPD process. Since reversible deposits cannot be characterized with standard ex situ methods, the particle-particle and particle-field interactions that govern the displayed color and crystallinity of these systems are not well understood. In this paper, we present in situ small-angle x-ray scattering and UV-Vis techniques for measuring both the structural and optical response of an APC under applied electric fields. Furthermore, we also develop a computational model based on colloidal interactions to explain the observed change in the interparticle spacing of APCs due to the applied electric field which correlates to displayed color. Ultimately, this work provides a new in situ characterization method that could be expanded for other dynamic, tunable colloidal systems.
A solvent-free solid catalyst for the selective and color-indicating ambient-air removal of sulfur mustard
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Where’s Swimmy?: Mining unique color features buried in galaxies by deep anomaly detection using Subaru Hyper Suprime-Cam data
Abstract We present the Swimmy (Subaru WIde-field Machine-learning anoMalY) survey program, a deep-learning-based search for unique sources using multicolored (grizy) imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). This program aims to detect unexpected, novel, and rare populations and phenomena, by utilizing the deep imaging data acquired from the wide-field coverage of the HSC-SSP. This article, as the first paper in the Swimmy series, describes an anomaly detection technique to select unique populations as “outliers” from the data-set. The model was tested with known extreme emission-line galaxies (XELGs) and quasars, which consequently confirmed that the proposed method successfully selected $\sim\!\! 60\%$–$70\%$ of the quasars and $60\%$ of the XELGs without labeled training data. In reference to the spectral information of local galaxies at z = 0.05–0.2 obtained from the Sloan Digital Sky Survey, we investigated the physical properties of the selected anomalies and compared them based on the significance of their outlier values. The results revealed that XELGs constitute notable fractions of the most anomalous galaxies, and certain galaxies manifest unique morphological features. In summary, deep anomaly detection is an effective tool that can search rare objects, and, ultimately, unknown unknowns with large data-sets. Further development of the proposed model and selection process can promote the practical applications required to achieve specific scientific goals.
Why Black Flowers? An Extreme Environment and Molecular Perspective of Black Color Accumulation in the Ornamental and Food Crops
Pollinators are attracted to vibrant flower colors. That is why flower color is the key agent to allow successful fruit set in food or ornamental crops. However, black flower color is the least attractive to pollinators, although a number of plant species produce black flowers. Cyanidin-based anthocyanins are thought to be the key agents to induce black color in the ornamental and fruit crops. R2R3-MYB transcription factors (TFs) play key roles for the tissue-specific accumulation of anthocyanin. MYB1 and MYB11 are the key TFs regulating the expression of anthocyanin biosynthesis genes for black color accumulation. Post-transcriptional silencing of flavone synthase II ( FNS ) gene is the technological method to stimulate the accumulation of cyanidin-based anthocyanins in black cultivars. Type 1 promoter of DvIVS takes the advantage of FNS silencing to produce large amounts of black anthocyanins. Exogenous ethylene application triggers anthocyanin accumulation in the fruit skin at ripening. Environment cues have been the pivotal regulators to allow differential accumulation of anthocyanins to regulate black color. Heat stress is one of the most important environmental stimulus that regulates concentration gradient of anthocyanins in various plant parts, thereby affecting the color pattern of flowers. Stability of black anthocyanins in the extreme environments can save the damage, especially in fruits, caused by abiotic stress. White flowers without anthocyanin face more damages from abiotic stress than dark color flowers. The intensity and pattern of flower color accumulation determine the overall fruit set, thereby controlling crop yield and human food needs. This review paper presents comprehensive knowledge of black flower regulation as affected by high temperature stress, and the molecular regulators of anthocyanin for black color in ornamental and food crops. It also discusses the black color-pollination interaction pattern affected by heat stress for food and ornamental crops.
Gauge invariance and color charge fluctuations
The nature of confinement is connected with color charge. Unfortunately, the color charge densities in QCD, the Noether charge densities associated with the global color invariance, are not invariant under local color rotations. This implies that the expectation values of the net color charge in any region of any physical state in QCD—states that satisfy the color Gauss law—are automatically zero for all components of color. In this Letter, it is shown that the expectation value of the square of the net color charge in a region—a measure of the color charge fluctuations—is necessarily nonzero when evaluated in physical states and the result, while depending on the scheme and scale by which the theory is regulated, is gauge invariant. This holds despite the formal lack of gauge invariance of the operator. Moreover, there is a particular combination of the color charge fluctuations for the vacuum and for a system describable by a nontrivial density matrix that is independent that has a well-defined continuum limit.
Mechanism of structural colors in binary mixtures of nanoparticle-based supraballs
Inspired by structural colors in avian species, various synthetic strategies have been developed to produce noniridescent, saturated colors using nanoparticle assemblies. Nanoparticle mixtures varying in particle chemistry and size have additional emergent properties that affect the color produced. For complex multicomponent systems, understanding the assembled structure and a robust optical modeling tool can empower scientists to identify structure-color relationships and fabricate designer materials with tailored color. Here, we demonstrate how we can reconstruct the assembled structure from small-angle scattering measurements using the computational reverse-engineering analysis for scattering experiments method and use the reconstructed structure in finite-difference time-domain calculations to predict color. We successfully, quantitatively predict experimentally observed color in mixtures containing strongly absorbing nanoparticles and demonstrate the influence of a single layer of segregated nanoparticles on color produced. The versatile computational approach that we present is useful for engineering synthetic materials with desired colors without laborious trial-and-error experiments.
Reconfigurable Grating Diffraction Structural Color in Self-Assembled Colloidal Crystals
Self-assembled colloidal crystals display structural colors due to light diffracted from their microscale, ordered structure. This color arises due to Bragg reflection (BR) or grating diffraction (GD); the latter mechanism is much less explored than the former. Here the design space for generating GD structural color is identified and its relative advantages are demonstrated. Electrophoretic deposition is used to self-assemble crystals with fine crystal grains from colloids of diameter 1.0 µm. The structural color in transmission is tunable across the full visible spectrum. The optimum optical response—represented by both color intensity and saturation—is observed at low layer number (≤5 layers). The spectral response is well predicted by Mie scattering of the crystals. Taken together, the experimental and theoretical results demonstrate that vivid grating colors with high color saturation can be produced from thin layers of micron-sized colloids. These colloidal crystals extend the potential of artificial structural color materials.
van der Waals Semiconductor Empowered Vertical Color Sensor
We report biomimetic artificial vision is receiving significant attention nowadays, particularly for the development of neuromorphic electronic devices, artificial intelligence, and microrobotics. Nevertheless, color recognition, the most critical vision function, is missed in the current research due to the difficulty of downscaling of the prevailing color sensing devices. Conventional color sensors typically adopt a lateral color sensing channel layout and consume a large amount of physical space, whereas compact designs suffer from an unsatisfactory color detection accuracy. In this work, we report a van der Waals semiconductor-empowered vertical color sensing structure with the emphasis on compact device profile and precise color recognition capability. More attractive, we endow color sensor hardware with the function of chromatic aberration correction, which can simplify the design of an optical lens system and, in turn, further downscales the artificial vision systems. Also, the dimension of a multiple pixel prototype device in our study confirms the scalability and practical potentials of our developed device architecture toward the above applications.
Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing
A coloring of a graph is an assignment of colors to vertices such that no two neighboring vertices have the same color. The need for memory-efficient coloring algorithms is motivated by their application in computing clique partitions of graphs arising in quantum computations where the objective is to map a large set of Pauli strings into a compact set of unitaries. We present Picasso, a randomized memory-efficient iterative parallel graph coloring algorithm with theoretical sublinear space guarantees under practical assumptions. The parameters of our algorithm provide a trade-off between coloring quality and resource consumption. To assist the user, we also propose a machine learning model to predict the coloring algorithm’s parameters considering these trade-offs. We provide a sequential and a parallel implementation of the proposed algorithm. We perform an experimental evaluation on a 64-core AMD CPU equipped with 512 GB of memory and an Nvidia A100 GPU with 40GB of memory. For a small dataset where existing coloring algorithms can be executed within the 512 GB memory budget, we show up to 68× memory savings. On massive datasets we demonstrate that GPU-accelerated Picasso can process inputs with 49.5× more Pauli strings (vertex set in our graph) and 2,478× more edges than state-of-the-art parallel approaches.
Experimental validation of color rendition specification criteria based on ANSI/IES TM-30-18
An experiment was conducted to examine color preference specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied color rendition conditions designed to meet or not meet previously proposed color preference specification criteria using ANSI/IES TM-30-18 Rf, Rcs,h1, and Rg. The color rendition conditions did not meet the criterion for none, one, two, or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects’ color appearance on eight-point scales for saturated-dull, normal-shifted, and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that color preference criteria could be adjusted slightly to improve performance, with Tier A having Rf = 78, Rg = 95, and -1% = Rcs,h1 = 15%, Tier B having Rf = 74, Rg = 92, and -7% = Rcs,h1 = 19%, and Tier C having Rf = 70, Rg = 89, -12% = Rcs,h1 = 23%. A companion regression analysis shows models based on Rf, Rg, and Rcs,h1 were superior in predicting color preference compared to those using other measures of color rendition.
Dual-Image Color Normalization to Enable High-Performance Concentrating Solar Optical Metrology
Concentrating Solar Power (CSP) requires precision mirrors, and these in turn require metrology systems to measure their optical slope. In this project we studied a color-based approach to the correspondence problem, which is the association of points on an optical target with their corresponding points seen in a reflection. This is a core problem in deflectometry-based metrology, and a color solution would enable important new capabilities. We modeled color as a vector in the [R,G,B] space measured by a digital camera, and explored a dual-image approach to compensate for inevitable changes in illumination color. Through a series of experiments including color target design and dual-image setups both indoors and outdoors, we collected reference/measurement image pairs for a variety of configurations and light conditions. We then analyzed the resulting image pairs by selecting example [R,G,B] pixels in the reference image, and seeking matching [R,G,B] pixels in the measurement image. Modulating a tolerance threshold enabled us to assess both match reliability and match ambiguity, and for some configurations, orthorectification enabled us to assess match accuracy. Using direct-direct imaging, we demonstrated color correspondence achieving average match accuracy values of 0.004 h, where h is the height of the color pattern. We found that wide-area two-dimensional and linear one-dimensional color targets outperformed hybrid linear/lateral gradient targets in the cases studied. Introducing a mirror degraded performance under our current techniques, and we did not have time to evaluate whether matches could be reliably achieved despite varying light conditions. Nonetheless, our results thus far are promising.