This study introduces an innovative recurrent neural network called long short-term memory (LSTM) as a prediction model, which is used to predict angle-dependent reflectance distributions of colour samples with glossy and matte surfaces. A two-dimensional (2D) reflectance measurement system was developed to measure the angle-dependent reflectance in this study. Its structure mainly included a semicircular rotating mechanism, a high-resolution digital camera and a high-quality white light-emitting diode. A semicircular rotating mechanism was designed to rotate from 10 degrees to 170 degrees in the vertical direction. Two ColorGauge miniaturised colour charts with glossy and matte surfaces were selected as test chips. The test chips on ColorGauge miniaturised colour charts included fives colours of glossy white, glossy black, matte red, matte green and matte blue. The reflectance distributions of the test chips were measured by the 2D reflectance measurement system, and the measured reflectance data were used as training data in the LSTM model. In comparison with second- and third-order regressions, the mean CIE lightness difference (0.09) using the LSTM model was lower. Therefore, it was verified that the LSTM model performed well in predicting reflectance distributions. In addition, the LSTM model was also validated on the additional test samples (10 matte chromatic samples and five glossy achromatic samples). The maximum and minimum mean CIE lightness differences were 3.77 and 0.64 for matte chromatic samples, and 2.34 and 0.42 for glossy achromatic samples, respectively. The results of small prediction errors indicated that the LSTM model presents excellent prediction performance.

Tongue color is one of the important indices for tongue diagnosis in traditional Chinese medicine. This study aims to analyze tongue colors of computational tongue diagnosis in traditional Chinese medicine using scientific quantification and computational simulation. The tongue color data are established according to the experiment in which the doctors who use Chinese traditional medicine assessed standard Munsell color charts under the standard lighting environment. Tongue color is classified into six color names, which are pale red, light red, red, crimson, dark red, and purple. The doctors assessed Munsell color charts to find the corresponding color charts' distributions of each color name in tongue color. The hue-lightness-chroma data of the chosen Munsell color charts were transformed to CIE xyY using the look-up table computation, then further were converted to CIELAB values and sRGB data. Based on the 95% confidence ellipses formed on CIELAB (a*, b*) plane and CIELAB (C*, L*) plane, the comparisons between tongue colors and general colors were analyzed. The computational tongue image simulation combining the elements of color, texture, and moisture was successfully established. This computational simulation method could potentially become a useful tool for teaching and learning diagnoses in the education of Chinese medicine.

ETHNOPHARMACOLOGICAL RELEVANCE Most Aristolochiaceae plants are prohibited due to aristolochic acid nephropathy (AAN), except Xixin (Asarum spp.). Xixin contains trace amounts of aristolochic acid (AA) and is widely used in Traditional Chinese Medicine. Methylglyoxal and D-lactate are regarded as biomarkers for nephrotoxicity. AIM OF THE STUDY The use of Xixin (Asarum spp.) is essential and controversial. This study aimed to evaluate tubulointerstitial injury and interstitial renal fibrosis by determining urinary methylglyoxal and D-lactate after withdrawal of low-dose AA in a chronic mouse model. MATERIALS AND METHODS C3H/He mice in the AA group (n = 24/group) were given ad libitum access to distilled water containing 3 μg/mL AA (0.5 mg/kg/day) for 56 days and drinking water from days 57 to 84. The severity of tubulointerstitial injury and fibrosis were evaluated using the tubulointerstitial histological score (TIHS) and Masson's trichrome staining. Urinary and serum methylglyoxal were determined by high-performance liquid chromatography (HPLC); urinary D-lactate were determined by column-switching HPLC. RESULTS After AA withdrawal, serum methylglyoxal in the AA group increased from day 56 (429.4 ± 48.3 μg/L) to 84 (600.2 ± 99.9 μg/L), and peaked on day 70 (878.3 ± 171.8 μg/L; p < 0.05); TIHS and fibrosis exhibited similar patterns. Urinary methylglyoxal was high on day 56 (3.522 ± 1.061 μg), declined by day 70 (1.583 ± 0.437 μg) and increased by day 84 (2.390 ± 0.130 μg). Moreover, urinary D-lactate was elevated on day 56 (82.10±18.80 μg) and higher from day 70 (201.10 ± 90.82 μg) to 84 (193.28 ± 61.32 μg). CONCLUSIONS Methylglyoxal is induced after AA-induced tubulointerstitial injury, so methylglyoxal excretion and metabolism may be a detoxification and repair strategy. A low cumulative AA dose is the key factor that limits tubulointerstitial injury and helps to repair. Thus, AA-containing herbs, especially Xixin, should be used at low doses for short durations (less than one month).

Two machine learning models, including the polynomial regression model and artificial neural network, are proposed based on the result of a visual perception experiment of fluorescent samples. The results indicate that both two models can ideally predict the visual color appearance of fluorescent samples under various lighting conditions with high R-squared, acceptable RMSE, and MAE values.

In the study, two machine learning models including the polynomial regression model and artificial neural network are proposed based on the result of a visual perception experiment for the application of a user interface. The results indicate that both two models can ideally predict the visual color difference of fluorescent samples under various lighting conditions with high R-squared and acceptable RMSE values by applying CLELAB color space and CIE 1976 color difference as the inputs.

This paper evaluates the gamut expansion ratio on a six-primary display by conducting a psychophysical experiment involving real objects. However, no six-primary display was used in this article; it was based on the simulated and virtual RGBCMY display. We first introduce the algorithm for simulating the six-primary display that consists of three stages: (1) colour separation, (2) code condensation, and (3) white point estimation. To ensure that we identify the most suitable gamut expansion ratio for the human perception of the colours of objects, our experiments featured pineapple, loquat, wax apple, peach, plum, carambola, and guava fruits through saturated colours on a monitor. Subjects were asked to identify their preferences for the colours that they observed. Our results show that the most suitable perception range for real objects is from 1.2 to 1.4.

The objective of this study was to investigate the agreement between multiangle appearance data obtained from multiangle measurements and the rating scores given by observers in terms of sparkle and coarseness. The metallic emotional equation for coloured metallic paints was developed on the basis of two experimental results. Experiment 1 involved measuring metallic paint appearance, and a multiangle spectrophotometer was used for measuring the appearance parameters of metallic coating samples under multiple measuring angles. In Experiment 2, observers were asked to visually assess coloured metallic samples under directional and diffuse light conditions. The observers assessed the test samples, illuminated from the top, from three observation angles. Principal component analysis was performed to analyse the observers’ emotional responses. Finally, the metallic emotional models consisting of the expensiveness model and fashion model were constructed.

Aristolochic acid (AA) causes interstitial renal fibrosis, called aristolochic acid nephropathy (AAN). There is no specific indicator for diagnosing AAN, so this study aimed to investigate the biomarkers for AAN using a proteomics method. The C3H/He female mice were given ad libitum AA-distilled water (0.5 mg/kg/day) and distilled water for 56 days in the AA and normal groups, respectively. The AA-induced proteins in the kidney were investigated using a proteomics study, including fluorogenic derivatization with 7-chloro-N-[2-(dimethylamino)ethyl]-2,1,3-benzoxadiazole-4-sulfonamide, followed by high-performance liquid chromatography analysis and liquid chromatography tandem mass spectrometry with a MASCOT database searching system. There were two altered proteins, thrombospondin type 1 (TSP1) and G protein-coupled receptor 87 (GPR87), in the kidney of AA-group mice on day 56. GPR87, a tumorigenesis-related protein, is reported for the first time in the current study. The renal interstitial fibrosis was certainly induced in the AA-group mice under histological examination. Based on the results of histological examination and the proteomics study, this model might be applied to AAN studies in the future. TSP1 might be a novel biomarker for AAN, and the further role of GPR87 leading to AA-induced tumorigenesis should be researched in future studies.

Autostereoscopic displays are likely to become widely used products in the future. However, certain physiological factors, especially visual comfort, limit their development. In this study, four observational parameters – ambient illuminance, image content, scaling ratio, and horizontal distance between major and minor objects – were evaluated to determine the degree of visual comfort offered by 3D computer‐generated images on an autostereoscopic display. Visual comfort score with the range of 0–1 is designed to represent the degree of visual comfort for the 3D images with different manipulations of ambient illuminance, image content, scaling ratio, and horizontal distance between major and minor objects in this study. Subjects were asked to indicate images that produced discomfort. The proportion of images for each condition where participants indicated that viewing the image was comfortable was computed. Images receiving a proportion of 0.5 or greater were classified as acceptable. The disparity ranges over which acceptable images were attained for each participant and for each condition were analyzed with analysis of variance. The analytical results indicate that ambient illuminance and image content have a significant effect on the acceptable disparity range, while scaling ratio and horizontal distance between major and minor objects did not.

Display technologies are used in various industries. However, few studies on color vision testing using self-luminous displays are reported. In this study, a screen-based color vision test, termed the digital color vision test (DCVT), is developed on a color-calibrated monitor. A control bar is adjusted by the observer to build just noticeable chromatic difference ellipses in CIE u'v' chromaticity diagram, which indicate the capabilities of subjects' color visions. Ten color-normal observers and 13 deutan observers participated in the psychophysical experiments. The observers also performed the other two typical diagnostic tests (D-15 and anomaloscope). Results from the experiment using the adjustment psychophysical method for digital quantification of deutan color vision defects are presented. It is found that the diagnosis accuracy of the DCVT is approximately equivalent to those of D-15 and anomaloscope tests.

Keywords: Museum lightingKruithof's ruleEmotional response modelPerception zone mapArt conservationAccelerated aging

The present study evaluated the state‐of‐the‐art RGBW and quantum dot LCD technologies in both objective and subjective ways. The results show that the new technologies really improve the image qualities of LCDs in many different aspects. The drawback of RGBW LCD is seems to be overcome by a color recovery algorithm and the unevenly gamut expansion of quantum dot LCDs are acceptable to observers.

The effect of cross-regional or cross-cultural differences on color appearance ratings and memory colors of familiar objects was investigated in seven different countries/regions - Belgium, Hungary, Brazil, Colombia, Taiwan, China and Iran. In each region the familiar objects were presented on a calibrated monitor in over 100 different colors to a test panel of observers that were asked to rate the similarity of the presented object color with respect to what they thought the object looks like in reality (memory color). For each object and region the mean observer ratings were modeled by a bivariate Gaussian function. A statistical analysis showed significant (p < 0.001) differences between the region average observers and the global average observer obtained by pooling the data from all regions. However, the effect size of geographical region or culture was found to be small. In fact, the differences between the region average observers and the global average observer were found to of the same magnitude or smaller than the typical within region inter-observer variability. Thus, although statistical differences in color appearance ratings and memory between regions were found, regional impact is not likely to be of practical importance.

In the highly competitive display market, manufacturers continuously develop new technologies to improve the image quality of displays. However, color measurement and visual assessment are time‐consuming to production lines. A new method to measure and improve color quality of the displays automatically therefore, is urgently needed to the manufacturers. This article proposes a familiar color correction strategy to optimize the colors of different displays by means of creating an image‐based color palette which enables color correction for familiar objects (e.g., facial skin, blue sky, or green grass) in the multidisplay systems. To produce the image‐based color palette, the 8‐bit RGB value of each pixel in an image is transformed to L*d*n* (lightness/dominant color/nondominant color) color channels, and the dominant‐color regions in an image are subsequently extracted from the dominant color (d*) channel. The memory color data of familiar objects can be set in reference monitor in advance to determine the dominant color (d*) channel. Then a series of palette colors are generated around a displayed image. The color palette will be displayed as a target for two‐dimensional colorimeter shooting to obtain the measured color data. The familiar color correction model was established based on a first‐order polynomial regression to achieve a polynomial fit between the measured color data and the reference color data on the color palette. The proposed method provides a solution to correct familiar colors on a displayed image, and maintains the original color gamut and tone characteristic in the multidisplay systems simultaneously. It is possible to achieve the preferred intent of the displayed images by using the proposed familiar color correction method. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 154–168, 2014

It is essential to understand preferred skin colors for color reproduction in the display industry. This article presents three psychophysical experiments that were conducted to determine the preferred skin color ranges of East Asian women by East Asian observers on the chromatic and lightness components of CIELAB color space displayed on a standard sRGB-gamut display. In the first experiment, the preferred skin color was searched using various settings of correlated color temperatures (CCTs) and luminance levels on the screen. The results indicate that the most preferred skin color on a display had small differences between various images varying in CCT and luminance level. In the second experiment, a more precise preferred skin color center was produced. The preference scores were analyzed, and the preference map of skin colors was presented on the CIELAB a* b* plane. The final experiment examined the relationship between the lightness of facial skin color and the perceived preference on a display. It was conducted to examine the effect of the lightness component on the preference of facial skin color. It was found that the (C*(ab), h(ab)) value of the most preferred skin colors of East Asian women is (25.4, 50.5), with an L* value of 65. (C) 2013 Society for Imaging Science and Technology.