Search Results (29)

This study evaluated if the material, the substrate, and the cement have no influence on the color of pre-shaded monolithic zirconia crowns. The specific effect of the cement over each substrate/brand group was also studied. Two commercial brands of zirconia, Amann Girrbach (AG) and Zirkonzahn (ZZ), were used to produce crowns that were placed over three substrates (natural tooth, zirconia, metal) using two different resin cements (Ivoclar AG (Shaan, Liechtenstein) Neutral and Light) or glycerol (as the control) (n = 10). Lightness (L*), chroma (C*), hue (h*), and color difference (ΔE) of each crown were measured using a VITA Easyshade V^® spectrophotometer (VITA Zahnfabrik, Bad Säckingen, Germany), following the standardized reference. Since normality was not verified by the Shapiro–Wilk test, data were statistically analyzed using the Kruskal–Wallis test for group comparisons and Tukey’s post-hoc test for multifactorial variance analysis (α = 0.05). ΔE medians ranged between 1.3 in the AG/zirconia substrate/glycerol group and 8.0 in the ZZ/metal substrate/light cement group. In general, lower values of ΔE were recorded in AG restorations compared to ZZ (p < 0.05), zirconia, and natural tooth substrates compared to metal (p < 0.001) and neutral compared to light cements (p < 0.05). Specifically, over the metal substrate, AG crowns with neutral cement and ZZ crowns with neutral cement and glycerol showed lower ΔE values (p < 0.05). Over the zirconia substrate, light cement presented higher ΔE values than glycerol in both brands but similar to neutral cement. Over the natural tooth, no significant differences were observed between cements (p > 0.05) in the AG brand, while in the ZZ group, light cement showed higher ΔE values (p < 0.05). The final color of the restorations was significantly influenced by the zirconia brand, substrate type, and resin cement. Light cement led to greater color variations, particularly in ZZ restorations. These findings highlight the importance of material selection in achieving esthetically pleasing zirconia restorations. Full article

The extraction of navigation lines is a crucial aspect in the field autopilot system for intelligent agricultural equipment. Given that soybean seedlings are small, and straw can be found in certain Northeast China soybean fields, accurately obtaining feature points and extracting navigation lines during the soybean seedling stage poses numerous challenges. To solve the above problems, this paper proposes a method of extracting navigation lines based on the average coordinate feature points of pixel points in the bean seedling belt according to the calculation of the average coordinate. In this study, the soybean seedling was chosen as the research subject, and the Hue, Saturation, Value (HSV) colour model was employed in conjunction with the maximum interclass variance (OTSU) method for RGB image segmentation. To extract soybean seedling bands, a novel approach of framing binarised image contours by drawing external rectangles and calculating average coordinates of white pixel points as feature points was proposed. The feature points were normalised, and then the improved adaptive DBSCAN clustering method was used to cluster the feature points. The least squares method was used to fit the centre line of the crops and the navigation line, and the results showed that the average distance deviation and the average angle deviation of the proposed algorithm were 7.38 and 0.32. The fitted navigation line achieved an accuracy of 96.77%, meeting the requirements for extracting navigation lines in intelligent agricultural machinery equipment for soybean inter-row cultivation. This provides a theoretical foundation for realising automatic driving of intelligent agricultural machinery in the field. Full article

As technology advances and cyber threats become increasingly sophisticated, the task of recognising and understanding malicious activities becomes more complex. This persistent issue is widely acknowledged and extensively documented within the cybersecurity community. Attack modelling techniques (AMTs), such as attack graphs, have emerged as valuable tools in aiding cyberattack perception. These visualisation tools offer crucial insights into the complex relationships between various components within a system or network, shedding light on potential attack paths and vulnerabilities. This paper proposes an attack graph visual syntax method to improve cyberattack perception among experts and non-experts. The proposed approach was developed to streamline complexity and enhance clarity, thus augmenting the interpretability for users by enhancing visual structural components, such as hue, chromaticity, and line parameters. The proposed attack graph (pag) was empirically evaluated against the adapted attack graph (aag) presented in the literature. The empirical evaluation (n = 83) was conducted through a 3 × 2 × 2 factorial design and two-way analysis of variance (ANOVA) with repeated measures. The participants were classified according to their respective background cohorts into expert and non-expert (expert n = 37, non-expert n = 46) and then grouped into two groups: proposed attack graph (pag) and adapted attack graph (aag) (pag n = 41, aag n = 42). The empirical results demonstrated that while the proposed attack graph (pag) implemented various visual modifications such as brighter hues, denser line structures, and varied shapes, these enhancements did not significantly improve the perception of cyberattacks among individuals who lack expertise in the field, including corporate executives. Moreover, the use of variables such as colour, tone, and line width/density/structure did not help objects in the graph be distinguished more effectively. This paper provides significant insights into the impact of visual enhancements on cyberattack perception, highlighting that visual enhancements alone may not be sufficient to improve cyberattack perception for individuals lacking expertise in the field. Full article

Polygonati rhizoma, known for its distinct yellow rhizomes, is a common therapeutic and culinary plant in Far East Asia. The hue of medicinal plants is closely tied to the flavonoid biosynthesis and content levels. In this research, the fibrous root and taproot of Polygonatum kingianum Coll.et Hemsl. were studied to explore the secondary metabolite expression and flavonoid biosynthesis mechanisms using transcriptomics and metabolomics. Metabolic analysis identified that the differentially accumulated metabolites (DAMs) in the fibrous root and taproot were predominantly flavonoids, steroids, alkaloids, and phenolic acids. Overall, 200 flavonoids were identified in P. kingianum Coll.et Hemsl., with 170 exhibiting variances between the fibrous root and taproot. The transcriptome analysis revealed that a total of 289 unigenes encoding 32 enzymes were annotated into four flavonoid biosynthesis pathways, which include phenylpropanoid biosynthesis pathway, flavonoid biosynthesis pathway, isoflavonoid biosynthesis pathway, and flavone and flavonol biosynthesis pathway. The integration of transcriptomic and metabolomic data elucidated that the 76 differentially expressed genes (DEGs) encoding 13 enzyme genes (HCT, CCOMT, C4H, C3′H, CHI, PGT1, FLS, F3′H, CHS, ANR, DFR, F3′5′H, and LAR) and 15 DAMs preferred to be regulated in the flavonoid biosynthesis pathway. The expression of 10 DEGs was validated by qRT-PCR, agreeing with the same results by RNA-Seq. These findings shed light into the biosynthesis of secondary metabolites in P. kingianum Coll.et Hemsl., offering valuable information for the sustainable utilization and enhancement of this plant species. Full article

This study assessed the masticatory function of participants wearing clear aligners in order to determine whether these devices can be worn even when eating and therefore worn to extend treatment time and boost treatment effectiveness. An intercontrol test was conducted on 20 patients who received Invisalign^® treatment. Each participant was instructed to chew two pieces of Hue-Check Gum^® chewing gum (one pink and the other blue) in 5, 10, and 20 cycles both with and without aligners. After being removed from the oral cavity, the gum was dried and pressed using a 1 × 50 × 50 mm model that was 3D printed with a transparent layer in between. After being scanned on both sides with a flatbed scanner at 600 dpi, the samples were saved as jpg files and subjected to an optoelectronic examination using ViewGum software. To validate the procedure, a control group from a different institution (University of Bern) was used. A statistical analysis of the data was carried out. The Shapiro–Wilk test was used to confirm the normality of the samples. A one-way ANOVA test, a homogeneity of variance test, and a t-test did not reveal statistically significant differences between the two control groups, thus validating the methodology employed. In summary, clear aligners do not radically change the masticatory function while they are worn. As a result, clinicians can exploit the aligners for chewing to obtain a better fit of the plastic material to the dental surface and to attachments. Treatment times for patients could also be shorter. Full article

The influence of feeding Atlantic salmon for 90 days on diets that excluded fishmeal (FM) and fish oil (FO) was examined for influence on various quality traits. In addition, the effect of adding krill meal (KM; 0%, 2.5%, and 5%), as a putative feed palatant was also examined. Total replacement of FM/FO had a limited effect on production characteristics, affecting percentage yields of headed and gutted control fish and their standard length (p < 0.05). Variances between dietary groups were observed for pigmentation, and plant protein-based KM-free-fed fish returned deeper hues across their belly, NQC (Norwegian Quality Cut), and back portions (p < 0.03). No differences were measured for relative fin condition. δ¹³C and δ¹⁵N concentrations were lower and higher, respectively (p < 0.05) for fish fed the FM/FO-based diet. δ¹³C:δ¹⁵N likewise differed between treatments with FM/FO-fed salmon expressing higher ratios. Fillet mechanical characteristics varied with fish fed on animal protein-based diets, without KM expressing higher springiness and resilience (p < 0.05). Fish fed plant-based diets were generally preferred by younger taste testers. The results from this trial illustrate that FM/FO can be completely removed from salmon diets without problematic effects on quality and palatability attributes. Full article

Grenache wines from the Central Coast of California were subjected to different alcoholic fermentation temperature regimes (Cold, Cold/Hot, Hot) and cap management protocols, namely, punch down (PD), or no punch down (No PD), to determine the effect of these practices on the color, aroma, and the retronasal and mouthfeel sensory characteristics of the resulting wines. Descriptive analysis (n = 8, line scale rating 0–15) results indicated that the combination of a hot fermentation temperature and no punch downs led to a significantly higher intensity in perceived color saturation (7.89) and purple hue (8.62). A two-way analysis of variance (ANOVA) showed that cap management was significantly more impactful on the perception of orthonasal aromas than fermentation temperature. The reduction aroma was significantly higher in No PD wines (5.02) compared to PD wines (3.50), while rose and hot aromas had significantly higher intensity perception for PD wines (5.18, 6.80) than for No PD wines (6.80, 6.14). Conversely, analysis of selected volatile compounds indicated that fermentation temperature was more impactful than cap management regime. Cold/Hot wines had higher concentrations of important esters such as ethyl hexanoate (650 µg/L) and isoamyl acetate (992 µg/L). Cold wines had a higher concentration of β-damascenone (0.719 µg/L). TCATA evaluation (n = 8) indicated that Cold/Hot PD wines had a significantly higher citation proportion of fruit flavor (1.0) and velvet astringency perception (0.80) without significant reduction flavors. Finally, the present study represents a contribution with the main volatile compounds (e.g., β-damascenone and esters in the Cold and Cold/Hot fermented wines, respectively; hexanol in PD wines, which may be potentially responsible for a hot mouthfeel), and sensory characteristics (red fruit, tropical fruit, white pepper, and rose) of Grenache wines grown in the Mediterranean climate of the Central Coast of California. Full article

The target region and diameter of maize stems are important phenotyping parameters for evaluating crop vitality and estimating crop biomass. To address the issue that the target region and diameter of maize stems obtained after transplantation may not accurately reflect the true growth conditions of maize, a phenotyping monitoring technology based on an internal gradient algorithm is proposed for acquiring the target region and diameter of maize stems. Observations were conducted during the small bell stage of maize. First, color images of maize plants were captured by an Intel RealSense D435i camera. The color information in the color image was extracted by the hue saturation value (HSV) color space model. The maximum between-class variance (Otsu) algorithm was applied for image threshold segmentation to obtain the main stem of maize. Median filtering, image binarization, and morphological opening operations were then utilized to remove noise from the images. Subsequently, the morphological gradient algorithm was applied to acquire the target region of maize stems. The similarity between the three types of gradient images and the manually segmented image was evaluated by pixel ratio extraction and image quality assessment indicators. Evaluation results indicated that the internal gradient algorithm could more accurately obtain the target region of maize stems. Finally, a checkerboard was employed as a reference for measurement assistance, and the stem diameter of maize was calculated by the pinhole imaging principle. The mean absolute error of stem diameter was 1.92 mm, the mean absolute percentage error (MAPE) was 5.16%, and the root mean square error (RMSE) was 2.25 mm. The R² value was 0.79. With an R² greater than 0.7 and a MAPE within 6%, the phenotyping monitoring technology based on the internal gradient algorithm was proven to accurately measure the diameter of maize stems. The application of phenotyping monitoring technology based on the internal gradient algorithm in field conditions provides technological support for smart agriculture. Full article

Solving the problem of the stem contour extraction of maize is difficult under open field conditions, and the stem diameter cannot be measured quickly and nondestructively. In this paper, maize at the small and large bell stages was the object of study. An adaptive threshold segmentation algorithm based on the color space model was proposed to obtain the stem contour and stem diameter of maize in the field. Firstly, 2D images of the maize stem in the field were captured with an RGB-D camera. Then, the images were processed by hue saturation value (HSV) color space. Next, the stem contour of the maize was extracted by maximum between-class variance (Otsu). Finally, the reference method was used to obtain the stem diameter of the maize. Scatter plots and Dice coefficients were used to compare the contour extraction effects of the HSV + fixed threshold algorithm, the HSV + Otsu algorithm, and the HSV + K-means algorithm. The results showed that the HSV + Otsu algorithm is the optimal choice for extracting the maize stem contour. The mean absolute error, mean absolute percentage error (MAPE), and root mean square error (RMSE) of the maize stem diameter at the small bell stage were 4.30 mm, 10.76%, and 5.29 mm, respectively. The mean absolute error, MAPE, and RMSE of the stem diameter of the maize at the large bell stage were 4.78 mm, 12.82%, and 5.48 mm, respectively. The MAPE was within 10–20%. The results showed that the HSV + Otsu algorithm could meet the requirements for stem diameter measurement and provide a reference for the acquisition of maize phenotypic parameters in the field. In the meantime, the acquisition of maize phenotypic parameters under open field conditions provides technical and data support for precision farming and plant breeding. Full article

The color appearance of residential carpets under different illuminants can influence the purchase decisions of consumers, visual merchandisers, and interior designers. This study was designed to investigate and characterize the color appearance of residential carpets under average Noon Daylight (D65), Incandescent (A), and Cool White Fluorescent (F02) illuminants commonly used in retail and household settings. The objective of this study was to identify the key features significantly affecting the apparent color of the carpets under those three illuminants. Four different carpets were dyed with light, medium, and dark shades of red and green colors to identify the difference in color perception when illuminated by different lighting arrangements. A spectrophotometer was used to measure the lightness, chroma, and hue of the carpets via the CIELAB scale developed by Commission Internationale de l’Eclairage (CIE). Statistically significant differences among the L*, a*, and b* values of the carpets were evaluated using Analysis of Variance (ANOVA). Regression analyses were carried out to identify key parameters affecting the L*, a* and b* values. Multiple linear regression (MLR) was applied to generate equations to predict L*, a* and b* values under different illuminant for different carpet features. A decreasing trend in the L*, a*, and b* values have been observed from lighter to darker shades under the illuminants for all the carpets. The deposition of dye molecules over the carpet surface had significant effects on the CIELAB values, and the distribution of dye molecules over the carpet surface was influenced by the constructional parameters of the carpets. The study provides an overview of the effects of carpet structures on color perception under different illuminants, which could help the researcher to determine the apparent color of different carpets under various illuminants. Full article

In this study, we propose a tomato maturity estimation approach based on a deep neural network. Tomato images were obtained using an RGB camera installed on a monitoring robot and samples were cropped to generate a dataset with which to train the classification model. The classification model is trained using cross-entropy loss and mean–variance loss, which can implicitly provide label distribution knowledge. For continuous maturity estimation in the test stage, the output probability distribution of four maturity classes is calculated as an expected (normalized) value. Our results demonstrate that the F1 score was approximately 0.91 on average, with a range of 0.85–0.97. Furthermore, comparison with the hue value—which is correlated with tomato growth—showed no significant differences between estimated maturity and hue values, except in the pink stage. From the overall results, we found that our approach can not only classify the discrete maturation stages of tomatoes but can also continuously estimate their maturity. Furthermore, it is expected that with higher accuracy data labeling, more precise classification and higher accuracy may be achieved. Full article

Harvesting seasons are crucial for the physicochemical qualities of large-leaf-variety black tea. To investigate the effect of harvesting seasons on physicochemical qualities, the color and sensory characteristics of black tea produced from “Yinghong 9” (Yh) and its mutant “Huangyu” (Hy) leaves were analyzed. The results demonstrated that Hy had better chemical qualities and sensory characteristics, on average, such as a higher content of tea polyphenols, free amino acids, caffeine, galloylated catechins (GaCs) and non-galloylated catechins (NGaCs), while the hue of the tea brew (ΔE*ab and Δb*) increased, which meant that the tea brew was yellower and redder. Moreover, the data showed that the physicochemical qualities of SpHy (Hy processed in spring) were superior to those of SuHy (Hy processed in summer) and AuHy (Hy processed in autumn), and 92.6% of the total variance in PCA score plots effectively explained the separation of the physicochemical qualities of Yh and Hy processed in different harvesting seasons. In summary, Hy processed in spring was superior in its physicochemical qualities. The current results will provide scientific guidance for the production of high-quality large-leaf-variety black tea in South China. Full article

(1) The article presents a new technique to interpret biomedical data (EEG) to assess cortical responses to continuous color/hue variations. We propose an alternative approach to analyze EEG activity evoked by visual stimulation. This approach may augment the traditional VEP analysis. (2) Considering ensembles of EEG epochs as multidimensional spatial vectors evolving over time (rather than collections of time-domain signals) and evaluating the similarity between such vectors across different EEG epochs may result in a more accurate detection of colors that evoke greater responses of the visual system. To demonstrate its suitability, the developed analysis technique was applied to the EEG data that we previously collected from 19 participants with normal color vision, while exposing them to stimuli of continuously varying hue. (3) Orange/yellow and dark blue/violet colors generally aroused better-pronounced cortical responses. The selection of EEG channels allowed for assessing the activity that predominantly originates from specific cortical regions. With such channel selection, the strongest response to the hue was observed from Parieto-Temporal region of the right hemisphere. The statistical test—Kruskal–Wallis one-way analysis of variance—indicates that the distance evaluated for spatial EEG vectors at different post-stimulus latencies generally originate from different statistical distributions with a probability exceeding 99.9% (α = 0.001). Full article

Morinda officinalis How is well-known as a valuable medicinal plant found in some regions of Vietnam. This species is mainly used for treating male impotence, irregular menstruation, and rheumatoid arthritis. This study aimed to identify the species of and genetic diversity in three M. officinalis populations: one each in Quang Binh (QB), Thua Thien Hue (TTH), and Quang Nam (QN). In this study, four DNA barcoding markers (ITS1, ITS2, matK, and rbcL) were used to identify the species and 22 microsatellite markers were applied for population structure and diversity analyses. The results showed that the sequences of gene regions studied in M. officinalis had a high similarity (>95%) to the ITS1, ITS2, matK, and rbcL sequences of M. officinalis on BLAST. Of the four DNA barcoding markers used, ITS1 and ITS2 showed higher efficiency in DNA amplification of M. officinalis. From this study, 27 GenBank codes were published on BLAST. The results also revealed high levels of genetic diversity in populations. The average observed and expected heterozygosity values were H_O = 0.513 and H_E = 0.612, respectively. The average F_ST value was 0.206. Analysis of molecular variance (AMOVA) showed 70% variation within populations and 30% among populations. The population structure of M. officinalis inferred in STRUCTURE revealed that the optimum number of genetic groups for the admixture model was K = 2. These findings provided vital background information for future studies in the conservation of M. officinalis in both ex situ and in situ plans. Full article

To improve and enrich the wheat growth information, visible and thermal infrared (TIR) remote sensing images were simultaneously acquired by an unmanned aerial vehicle (UAV). A novel algorithm was proposed for fusing the visible and TIR images combing the intensity hue saturation (IHS) transform and regional variance matching (RVM). After registering the two images, IHS transform was first conducted to derive the Intensities of two images. Wavelet transform was then applied to the Intensities for obtaining the coefficients of low- and high-frequency sub-bands. The fusion rules of the fused image were developed based on regional correlation of wavelet decomposition coefficients. More specifically, the coefficients of low-frequency sub-bands were calculated by averaging the coefficients of two images. Regional variance was used to generate the coefficients of high-frequency sub-bands using the weighted template of a 3 × 3 pixel window. The inverse wavelet transform was used to create the new Intensity for the fused image using the low- and high-frequency coefficients. Finally, the inverse IHS transform consisting of the new Intensity, the Hue of visible image, and the Saturation of TIR image was adopted to change the IHS space to red–green–blue (RGB) color space. The fusion effects were validated by the visible and TIR images of winter wheat at the jointing stage and the middle and late grain-filling stage. Meanwhile, IHS and RV were also comparatively evaluated for validating our proposed method. The proposed algorithm can fully consider the correlation of wavelet coefficients in local regions. It overcomes the shortcomings (e.g., block phenomenon, color distortion) of traditional image fusion methods to obtain smooth, detailed and high-resolution images. Full article