Concept: RGB color model
A basic premise of the recently proffered color-in-context model is that the influence of color on psychological functioning varies as a function of the psychological context in which color is perceived. Some research has examined the appetitive and aversive implications of viewing the color red in romance- and achievement-relevant contexts, respectively, but in all existing empirical work approach and avoidance behavior has been studied in separate tasks and separate experiments. Research is needed to directly test whether red influences the same behavior differently depending entirely on psychological context.
With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on the detection accuracy, has not been addressed properly. In this context, this work develops a calibration strip for ICG assay photoelectric detection systems. An image of the test strip is captured by an image acquisition device, followed by performing a fuzzy c-means (FCM) clustering algorithm and maximin-distance algorithm for image segmentation. Additionally, experiments are conducted to find the best characteristic quantity. By analyzing the linear coefficient, an average value of hue (H) at 14 min is chosen as the characteristic quantity and the empirical formula between H and optical density (OD) value is established. Therefore, H, saturation (S), and value (V) are calculated by a number of selected OD values. Then, H, S, and V values are transferred to the RGB color space and a high-resolution printer is used to print the strip images on cellulose nitrate membranes. Finally, verification of the printed calibration strips is conducted by analyzing the linear correlation between OD and the spectral reflectance, which shows a good linear correlation (R² = 98.78%).
Electrochromic polymers (ECPs) have been shown to be synthetically tunable, producing a full palette of vibrantly colored to highly transmissive polymers. The development of these colored-to-transmissive ECPs employed synthetic design strategies for broad color targeting; however, due to the subtleties of color perception and the intricacies of polymer structure and color relationships, fine color control is difficult. In contrast, color mixing is a well-established practice in the printing industry. We have identified three colored-to-transmissive switching electrochromic polymers, referred to as ECP-Cyan (ECP-C), ECP-Magenta (ECP-M), and ECP-Yellow (ECP-Y), which, via the co-processing of multicomponent ECP mixtures, follow the CMY color mixing model. The presented work qualitatively assesses the thin film characteristics of solution co-processed ECP mixtures. To quantitatively determine the predictability of the color properties of ECP mixtures, we estimated mass extinction coefficients (εmass) from solution spectra of the CMY ECPs and compared the estimated and experimentally observed color values of blends via a calculated color difference (ΔEab). The values of ΔEab range from 8 to 26 across all mixture compositions, with an average value of 15, representing a reasonable degree of agreement between predicted and observed color values. We demonstrate here the ability to co-process ECP mixtures into vibrantly colored, visually continuous films and the ability to estimate the color properties produced in these mixed ECP films.
A simple method for quantification of contrast in a fingerprint is proposed. Contrast is defined as the average difference in intensity of pixels between valleys and ridges in a fingerprint. It is quantified from a scanner-acquired image of the fingerprint using a histogram function of Adobe Photoshop. The method was validated with black inked prints and marks developed with aluminum powder. Moreover, we tested resistance of the method to rater-dependent errors and dependence of the measurements on the resolution of an image and the model of the scanner. For both groups of fingerprints, the method gave coherent and easily interpretable quantitative values for contrast. There were no significant differences between measurements performed by different raters and by the same rater in a test-retest procedure. However, the method was found to be instrument dependent, as measurements were significantly affected by image resolution and the model of the scanner.
Background matching is an important way to camouflage and is widespread among animals. In the field, however, few studies have addressed background matching, and there has been no reported camouflage efficiency in freshwater turtles. Background matching and camouflage efficiency of the four-eyed turtle, Sacalia quadriocellata, among three microhabitat sections of Hezonggou stream were investigated by measuring carapace components of CIE L*a*b* (International Commission on Illumination; lightness, red/green and yellow/blue) color space, and scoring camouflage efficiency through the use of humans as predators. The results showed that the color difference (ΔE), lightness difference (ΔL(*)), and chroma difference (Δa(*)b(*)) between carapace and the substrate background in midstream were significantly lower than that upstream and downstream, indicating that the four-eyed turtle carapace color most closely matched the substrate of midstream. In line with these findings, the camouflage efficiency was the best for the turtles that inhabit midstream. These results suggest that the four-eyed turtles may enhance camouflage efficiency by selecting microhabitat that best match their carapace color. This finding may explain the high population density of the four-eyed turtle in the midstream section of Hezonggou stream. To the best of our knowledge, this study is among the first to quantify camouflage of freshwater turtles in the wild, laying the groundwork to further study the function and mechanisms of turtle camouflage.
This study demonstrates chromatic analysis based on a simple red green blue (RGB) color model for sensitive and selective determination of mercury(II). The analysis was performed by monitoring the color change of a microfluidic Paper-based Analytical Device (µPAD). The device was fabricated by using alkyl ketene dimer (AKD)-inkjet printing and doped with unmodified silver nanoparticles (AgNPs) which were disintegrated when being exposed to mercury(II). The color intensity was detected by using an apparatus consisting of a digital camera and a homemade light box generating constant light intensity. A progressive increase in color intensity of the tested area on the µPAD (3.0mm) was observed with increasing mercury(II) concentration. The developed system enabled quantification of mercury(II) at low concentration with the detection limit of 0.001mgL(-1) (3 SD blank/slope of the calibration curve) and small sample volume uptake (2µL). The linearity range of the calibration curve in this technique was demonstrated from 0.05 to 7mgL(-1) (r(2)=0.998) with good precision (RSD less than 4.1%). Greater selectivity towards mercury(II) compared with potential interference ions was also observed. Furthermore, the percentage recoveries of spiked water samples were in an acceptable range which was in agreement with the values obtained from the conventional method utilizing cold vapor atomic absorption spectrometer (CVAAS). The proposed technique allows a rapid, simple, sensitive and selective analysis of trace mercury(II) in water samples.
- PDA journal of pharmaceutical science and technology / PDA
- Published almost 5 years ago
In the biotechnology industry, a visual method is most commonly utilized for color characterization of liquid drug protein solutions. The color testing method is used for both batch release and on stability testing for quality control. Using that method, an analyst visually determines the color of the sample by choosing the closest matching European Pharmacopeia (Ph. Eur.) reference color solution. The requirement to judge the best match makes it a subjective method. Furthermore, the visual method does not capture data on hue or chroma that would allow for improved product characterization and the ability to detect subtle differences between samples. To overcome these challenges, we describe a quantitative method for color determination that greatly reduces the variability in measuring color and allows for a more precise understanding of color differences. Following color industry standards established by International Commission on Illumination, this method converts a protein solution’s visible absorption spectra to L*a*b* color space. Color matching is achieved within the L*a*b* color space, a practice that is already widely used in other industries. The work performed here is to facilitate the adoption and transition for the traditional visual assessment method to a quantitative spectral method. We describe here the algorithm used such that the quantitative spectral method correlates with the currently used visual method. In addition, we provide the L*a*b* values for the Ph. Eur. reference color solutions required for the quantitative method. We have determined these L*a*b* values by gravimetrically preparing and measuring multiple lots of the reference color solutions. We demonstrate that the visual assessment and the quantitative spectral method are comparable using both low and high concentration antibody solutions and solutions with varying turbidity.
A prediction method for color changes based on the time-temperature superposition principle (TTSP) was developed for acetaminophen solution. Color changes of acetaminophen solution are caused by the degradation of acetaminophen, such as hydrolysis and oxidation. In principle, the TTSP can be applied to only thermal aging. Therefore, the impact of oxidation on the color changes of acetaminophen solution was verified. The results of our experiment suggested that the oxidation products enhanced the color changes in acetaminophen solution. Next, the color changes of acetaminophen solution samples of the same head space volume after accelerated aging at various temperatures were investigated using the Commission Internationale de l'Eclairage (CIE) LAB color space (a*, b*, L* and ΔE*ab), following which the TTSP was adopted to kinetic analysis of the color changes. The apparent activation energies using the time-temperature shift factor of a*, b*, L* and ΔE*ab were calculated as 72.4, 69.2, 72.3 and 70.9 (kJ/mol), respectively, which are similar to the values for acetaminophen hydrolysis reported in the literature. The predicted values of a*, b*, L* and ΔE*ab at 40 °C were obtained by calculation using Arrhenius plots. A comparison between the experimental and predicted values for each color parameter revealed sufficiently high R(2) values (>0.98), suggesting the high reliability of the prediction. The kinetic analysis using TTSP was successfully applied to predicting the color changes under the controlled oxygen amount at any temperature and for any length of time.
- IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
- Published about 3 years ago
Emerging sensor designs increasingly rely on novel color filter arrays (CFAs) to sample the incident spectrum in unconventional ways. In particular, capturing a near-infrared (NIR) channel along with conventional RGB color is an exciting new imaging modality. RGB+NIR sensing has broad applications in computational photography, such as low-light denoising, it has applications in computer vision, such as facial recognition and tracking, and it paves the way toward low-cost single-sensor RGB and depth imaging using structured illumination. However, cost-effective commercial CFAs suffer from severe spectral cross talk. This cross talk represents a major challenge in high-quality RGB+NIR imaging, rendering existing spatially multiplexed sensor designs impractical. In this work, we introduce a new approach to RGB+NIR image reconstruction using learned convolutional sparse priors. We demonstrate high-quality color and NIR imaging for challenging scenes, even including high-frequency structured NIR illumination. The effectiveness of the proposed method is validated on a large data set of experimental captures, and simulated benchmark results which demonstrate that this work achieves unprecedented reconstruction quality.
cAMP is a common second messenger that is involved in various physiological processes. To expand the colour palette of available cAMP indicators, we developed a red cAMP indicator named “Pink Flamindo” (Pink Fluorescent cAMP indicator). The fluorescence intensity of Pink Flamindo increases 4.2-fold in the presence of a saturating dose of cAMP, with excitation and emission peaks at 567 nm and 590 nm, respectively. Live-cell imaging revealed that Pink Flamindo is effective for monitoring the spatio-temporal dynamics of intracellular cAMP generated by photoactivated adenylyl cyclase in response to blue light, and in dual-colour imaging studies using a green Ca(2+) indicator (G-GECO). Furthermore, we successfully monitored the elevation of cAMP levels in vivo in cerebral cortical astrocytes by two-photon imaging. We propose that Pink Flamindo will facilitate future in vivo, optogenetic studies of cell signalling and cAMP dynamics.