Color Difference Research Articles

Resin infiltration versus fluoride varnish for visual improvement of white spot lesions during multibracket treatment. A randomized-controlled clinical trial

AimsThis study aimed to evaluate the visual improvement of resin infiltration of white spot lesions (WSL) during orthodontic treatment with the multibracket appliance (MBA) compared to fluoride varnish.MethodsPatients aged 12–17 years with at least one WSL with an International Caries Detection and Assessment System (ICDAS) score of 1–2 during an active MBA treatment were included and randomized to receive either resin infiltration (Icon) or fluoride application (Flairesse). Standardized digital images were obtained before, one-day, one-week, one-month, three-months and six-months after treatment using a DSLR camera and a matching polarization filter. A grey reference card was used for color standardization. A Matlab routine was used to measure the color difference between adjacent healthy enamel and treated WSL. The independent-samples t-test was used for intergroup and paired-samples t-test for intragroup comparison.ResultsImages of 116 teeth from 36 patients were analyzed. The ΔE for the “Icon” treated WSL was smaller (T1ICON = 5.0 ± 1.4) than in the fluoride group (T1Fluoride = 8.4 ± 3.2). Caries infiltration significantly improved the aesthetic appearance of WSL (p < 0.001), which remained satisfactory at six months (T5ICON = 5.2 ± 1.6).ConclusionWSL infiltration management during orthodontic treatment was superior to topical fluoridation in not only arresting the enamel lesions but also significantly improving the aesthetic appearance of demineralized regions around the brackets.Clinical relevanceWSL treatment in orthodontic patients is usually initiated after debonding. Research has shown that the earlier WSL is treated, the better the aesthetic outcome. There is limited data on the efficacy of resin infiltration of WSL during orthodontic treatment.

Physicochemical characterisation and impact of Gryllus bimaculatus addition on gluten‐free flour blends

SummaryGryllus bimaculatus (field cricket) powder is a prospect in enriching gluten‐free food products' protein and mineral contents. However, the technological impacts of replacing common gluten‐free cereal flours with G. bimaculatus powder are still incipient. This study aimed to characterise nutritional composition, particle morphology, and particle size distribution of G. bimaculatus powder and the gluten‐free flours (maize, rice, finger millet and proso millet). Additionally, it investigated the effects of substituting these gluten‐free flours with 5%, 10%, 15% and 20% G. bimaculatus powder on proximate composition, hydration and colour properties. G. bimaculatus powder showed significantly (P ≤ 0.05) high protein (44.8 g/100 g) content and essential minerals such as zinc (208.5 mg/kg) and iron (132.2 mg/kg). Micrographs of G. bimaculatus powder revealed compact and heterogenous particles while the flours' particles varied in sizes, and the starch granules had different shapes, sizes and arrangements. Flour particles exhibited bi‐and trimodal size distributions ranging from 1.5 μm to 1100 μm with minor peaks preceding major peaks. Finger millet flour had a greater span of 4.12, while proso millet flour had a lower span of 1.97. Particle size correlated negatively with water absorption capacity (WAC) (r = −0.938) and oil absorption capacity (OAC) (r = −0.955), respectively. G. bimaculatus powder addition significantly increased (P ≤ 0.05) fat, protein and fibre contents, decreased (P ≤ 0.05) nitrogen‐free extracts, but had no effect on ash content. Hydration properties differed significantly (P ≤ 0.05) except for WAC in proso millet blends. Samples exhibited significantly higher (P ≤ 0.05) WAC than OAC in exception of G. bimaculatus powder and showed no emulsifying activities. Addition of G. bimaculatus powder significantly (P ≤ 0.05) increased colour differences, reduced redness (a*), yellowness (b*) and lightness. The use of G. bimaculatus powder demonstrates the potential to enhance the nutritional properties and modify the colour and hydration of gluten‐free flours in the development of novel gluten‐free foods.

Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold

Out-of-distribution (OOD) detection is crucial for enhancing the reliability of machine learning models when confronted with data that differ from their training distribution. In the image domain, we hypothesize that images inhabit manifolds defined by latent properties such as color, position, and shape. Leveraging this intuition, we propose a novel approach to OOD detection using a diffusion model to discern images that deviate from the in-domain distribution. Our method involves training a diffusion model using in-domain images. At inference time, we lift an image from its original manifold using a masking process, and then apply a diffusion model to map it towards the in-domain manifold. We measure the distance between the original and mapped images, and identify those with a large distance as OOD. Our experiments encompass comprehensive evaluation across various datasets characterized by differences in color, semantics, and resolution. Our method demonstrates strong and consistent performance in detecting OOD images across the tested datasets, highlighting its effectiveness in handling images with diverse characteristics. Additionally, ablation studies confirm the significant contribution of each component in our framework to the overall performance.

Characterization of nanocomposite films based on tomato seed mucilage, gelatin and TiO2 nanoparticles

The aim of the present research was to investigate the interaction effect of incorporating titanium dioxide (TiO2) (0 %, 0.5 %, and 1 %) nanoparticles and manipulating the proportion of tomato seed mucilage (TSM) and gelatin (Ge) (1: 0, 0.33:0.67, 0.67:0.33, and 0:1) on the physical, mechanical, and microbial characteristics of the film. The findings indicated that the incorporation of TiO2 engendered an augmentation in the surface roughness of the film and an elevation in the film's thickness. The mechanical evaluation results revealed that the incorporation of TiO2 into the TSM-Ge films significantly enhanced (p˂0.05) the tensile strength (TS), (up to 300 %), an elevation of Young's modulus, while concurrently leading to a reduction in the elongation at break (EB). The incorporation of TiO2 resulted in a significant enhancement in various properties of the film (p˂0.05), including opacity, contact angle, oxygen permeability (OP), water vapor permeability (WVP), moisture absorption, moisture content, solubility, and swelling. The rise in the proportion of TSM resulted in a concomitant increase in the color differences (ΔE), and yellowness index (YI). Conversely, there was a decrease in the lightness (L*) and the whiteness index (WI). Additionally, an increase was found in opacity, solubility, moisture content, WVP, OP, swelling, and moisture absorption. It was observed that films without TiO2 exhibited no inhibitory effect. However, upon augmenting the concentration of TiO2 to 1 %, notable inhibitory and lethal effects were observed against various microorganisms, including Staphylococcus aureus, Escherichia coli, Aspergillus niger, and Candida glabrata. The results showed that the TSM-Ge composite film containing TiO2, exhibited potential as a viable choice for food packaging susceptible to microbial spoilage.

Experimental performance analysis of an infrared heating system for continuous applications of drying

One feasible approach for enhancing material quality and expediting the dehydrating procedure is using infrared radiation to provide heat. The impact of infrared power (0.130–0.341 W/cm2), airflow (0.5–1.5 m/s), and slice thickness (2–6 mm) on mass transfer, drying kinetics, colour, shrinkage, and rehydration ratio conditions. During the process, the dried samples' initial moisture content of 86.7 % was decreased to 11 % (w.b.). Eleven statistical factors were used to compare eleven alternative mathematical models. The results of regression analysis indicated that the Midilli et al. model best describes the drying behaviour in both techniques. The outcomes exhibited that the drying period rose at airflow and thickness but decreased with intensity. While the shrinkage ratio increased and declined with air velocity, the rehydration ratio grew and dropped with increasing infrared radiation intensity and airflow. As the intensity and airflow increased, there was a noticeable increase in the overall colour difference between slices of fresh and dry apples. The outcomes of this investigation will offer a further understanding of the ideal drying settings to create apple slices for snacking or other culinary purposes.

Botanical composition of pollen collected by Apis mellifera L. from Uludağ, northwest Türkiye

In recent years, the value of bee pollen has been recognised with the commercial value increasing. Determing the plant taxa that bees prefer as pollen sources and the floristic characteristics of the region is important for hive management and productivity. In this study, the botanical composition of bee pollen collected by Apis mellifera L. on the southern slopes of Uludağ (Bursa, Türkiye) was examined and the plant composition of the region, which is important for beekeeping, was evaluated. During the 2021 beekeeping period (between April and August), pollen loads were collected every two weeks. Colour differences of pollen loads were used to determine the botanical character of pollen samples. According to the data obtained from the analysis of pollen samples, 51 plant taxa belonging to 30 families visited by Apis mellifera L. were identified. Fabaceae (21.06%), Asteraceae (12.73%), Rosaceae (11.97%), and Brassicaceae (11.50%) were found to be the families containing the most preferred plants by honey bees. Herbaceous plants were visited by honey bees to collect pollen at the highest frequency of 77.60%, trees at 10.22%, and shrubs at 9.51% during the season. Tree forms were visited at a frequency of 5.25% in the second period of May, herbaceous forms were visited at a frequency of 20.50% in the first period of June, and shrub forms were visited at a frequency of 2.67% in the second period of June. These data demonstrate that the region has abundant resources for beekeeping, which contributes to the protection of the ecosystem and the economy.

Level of Agreement in Subjective Selection of Gingival Colour

Background and Objectives: Primary outcome: To assess the level of agreement between the objective and subjective methods for recording gingival colour in each area of the gingiva. Secondary outcome: To compare performance of the subjective visual method of gingival colour selection by a male observer and a female observer. Materials and Methods: A chromatic study was conducted on a total of 101 participants, in five gingival zones, from the free gingival margin to the mucogingival line, using a SpectroShade Micro spectrophotometer for the objective method and 21 ad hoc ceramic gingival shade tabs for the subjective method. A man and a woman of the same age, with the same amount of clinical experience in dentistry, selected the tab that most resembled the colour of participants’ gingiva. The “chromatic error” was then assessed by calculating the colour difference (using the Euclidean and CIEDE2000 formulae) between the CIELAB coordinates of the shade tab selected and the objective coordinates of the gingiva. The unweighted Kappa coefficient was used to calculate the level of agreement between observers. Results: For the male observer, the mean chromatic errors varied between ΔEab* 10.3 and 13.1 units, while for the female observer, the mean errors varied between ΔEab* 11.1 and 12.8: these differences were not statistically significant. Similarly, no statistically significant differences were found between the mean chromatic errors for the five gingival zones in either the male operator (p = 0.100) or the female operator (p = 0.093). The minimum level of agreement (unweighted Kappa) between the observers ranged from 0.1 to 0.4. Conclusions: Subjective selection of gingival colour was very inaccurate, by both the male observer and the female observer, for any area of the gingiva, with no differences identified between them. The level of agreement between the observers was low. These findings suggest that gingival colour should not be determined using solely subjective methods, given that the chromatic errors significantly exceeded the clinical acceptability threshold for gingiva (4.1 units for ΔEab* and 2.9 units for ΔE00). Both observers showed a tendency to select gingival shade tabs that were redder and bluer than the objective colours.

Color Differences of Polimerized Resin-Based Composites and Corresponding Shade Guides

Objective: The purpose of this study is to analyze and compare the colors (A2, A3 and A3.5) of polymerized resin-based composites (RBCs) with respect to the shade numbers within each product line and the VITAPAN Classical® shade guide they purported to represent. Methods: Three A-shades (A2, A3 and A3.5) from four RBC products (Harmonize®, Empress® Direct®, Grandio® and Filtek® 500) were compared within the VITAPAN Classical® shade guide and within their own commercial shade guide. Nine disk-shaped specimens, 6 mm in diameter and 2 mm thick, were prepared for each RBC color (three of each color). The color measurements were made according to the CIE L*a*b* color scale (quantifying L*c*h*a*b* values) using a Vita Easyshade Compact IV® digital spectrophotometer. We calculated the CIEDE2000 color differences between polymerized composites and shade guides, as well as between composites. The values obtained from composites and samples of the color guides in the CIE L*a*b* space were represented by ICC3D software (Version 1.2.9) Results: The ANOVA test verified the existence of statistically significant differences between composites for the same shades (p &lt; 0.05) except for shade A2. CIEDE2000 color differences between composites and the VITAPAN Classical® shade guide ranged from 3.5 to 13.1 depending on the composite and the shade. Conclusions: There were color differences among the polymerized resin-based composites, between these and their own shade guides/manufacturer’s commercial guides, and between the former and the corresponding samples of the VITAPAN Classical® shade guide. Clinical significance: Color selection when performing an aesthetic dental restoration is essential for the clinician and the patient to obtain an optimal result. Taking into account the color difference (∆E00) for each composite with the VITAPAN Classical® shade guide or with the manufacturers’ commercial guide allows for more precision with shade selection in aesthetic dentistry.

Visibility of esophageal squamous cell carcinoma under iodine staining on texture and color enhancement imaging

AbstractObjectiveIodine staining on white light imaging (WLI) is the gold standard for detecting and demarcating esophageal squamous cell carcinoma (ESCC). We examined the effects of texture and color enhancement imaging (TXI) on improving the endoscopic visibility of ESCC under iodine staining.MethodsTwenty ESCC lesions that underwent endoscopic submucosal dissection were retrospectively included. The color difference between ESCC and the surrounding mucosa (ΔEe) on WLI, TXI, and narrow‐band imaging was assessed, and ΔEe under 1% iodine staining on WLI and TXI. Furthermore, the visibility grade determined by endoscopists was evaluated on each imaging.ResultThe median ΔEe was greater on TXI than on WLI (14.53 vs. 10.71, respectively; p &lt; 0.005). Moreover, the median ΔEe on TXI under iodine staining was greater than the median ΔEe on TXI and narrow‐band imaging (39.20 vs. 14.53 vs. 16.42, respectively; p &lt; 0.005 for both). A positive correlation in ΔEe under iodine staining was found between TXI and WLI (correlation coefficient = 0.61, p &lt; 0.01). Moreover, ΔEe under iodine staining on TXI in each lesion was greater than the corresponding ΔEe on WLI. The visibility grade assessed by endoscopists on TXI was also significantly greater than that on WLI under iodine staining (p &lt; 0.01).ConclusionsThe visibility of ESCC after iodine staining was greater on TXI than on WLI.

Machine learning models to predict submucosal invasion in early gastric cancer based on endoscopy features and standardized color metrics

Conventional endoscopy is widely used in the diagnosis of early gastric cancers (EGCs), but the graphical features were loosely defined and dependent on endoscopists’ experience. We aim to establish a more accurate predictive model for infiltration depth of early gastric cancer including a standardized colorimetric system, which demonstrates promising clinical implication. A retrospective study of 718 EGC cases was performed. Clinical and pathological characteristics were included, and Commission Internationale de l’Eclariage (CIE) standard colorimetric system was used to evaluate the chromaticity of lesions. The predicting models were established in the derivation set using multivariate backward stepwise logistic regression, decision tree model, and random forest model. Logistic regression shows location, macroscopic type, length, marked margin elevation, WLI color difference and histological type are factors significantly independently associated with infiltration depth. In the decision tree model, margin elevation, lesion located in the lower 1/3 part, WLI a*color value, b*color value, and abnormal thickness in enhanced CT were selected, which achieved an AUROC of 0.810. A random forest model was established presenting the importance of each feature with an accuracy of 0.80, and an AUROC of 0.844. Quantified color metrics can improve the diagnostic precision in the invasion depth of EGC. We have developed a nomogram model using logistic regression and machine learning algorithms were also explored, which turned out to be helpful in decision-making progress.

Effect of different cooking conditions on the quality characteristics of chicken claws

AbstractChicken claw products with their unique texture are loved by consumers, and cooking is a key step to affect the taste of chicken claw consumption, through the moderate hydrolysis of proteins and a series of physicochemical changes, so that the chicken claw gets tender and presents a crispy taste, but the current research on the optimal cooking conditions for chicken claw is still relatively small. In the present work, combinations of time (11, 13, 15, 17, and 19 min) and temperature (82, 86, 90, 94, and 98°C) were applied to the cooking of chicken claws. The effects of different cooking conditions on the quality characteristics of chicken claws were investigated, with special emphasis on the cooking loss rate, color, texture properties, lipid oxidation, myofibrillar fragmentation index (MFI), and total sulfhydryl content. The results showed that the cooking loss rate, lipid oxidation, and MFI value of chicken claws gradually increased, and the total color difference (∆E), puncture force, shear force, and total sulfhydryl content gradually decreased with the increase of cooking temperature and cooking time. Overall, chicken claws cooked at 86, 90, and 94°C for 15 and 17 min had better texture and flavor.

SRMA: a dual-branch parallel multi-scale attention network for remote sensing images sea-land segmentation

ABSTRACT The use of deep learning-based high resolution remote sensing image sea and land segmentation method has become prevalent in various fields such as environmental monitoring, resource assessment, and urban planning. However, the segmentation process faces challenges due to the complex coastline and the similarity in spectral colour difference between the sea and land in certain areas. The remote sensing images obtained from satellites often exhibit unclear boundaries between the sea and land, as well as intricate coastlines. Consequently, the segmentation of sea and land becomes a difficult task. The existing sea-land segmentation methods have limitations in accurately segmenting long and narrow waters, as well as areas with low differentiation between sea and land. In this paper, we propose a new sea-land segmentation method called SRMA (Swin-Res-Multi-Attention). SRMA performs parallel feature extraction using a dual-branch parallel: Swin-Transformer branch and ResNet branch. The combination of Swin-Transformer’s self-attention and ResNet’s residual design helps reduce the loss of feature information, thereby avoiding incorrect segmentation in regions with low distinctness. To improve overall stability, we introduce the MCA (Multiscale channel attention module) module, which combines feature information from different scales. The multi-scale pyramid design of MCA module ensures stability and improves segmentation accuracy in narrow waters. Experimental results on a public dataset demonstrate that our model outperforms existing methods. Additionally, we evaluate the model’s performance in complex scenarios by creating a new dataset that includes a complex urban water body and cloud interference. The results showcase the robustness and superiority of our model.

Paper and nylon based optical tongues with poly(p-phenyleneethynylene)-fluorophores efficiently discriminate nitroarene-based explosives and pollutants

Discrimination of nitroarenes with hydrophobic dyes in a polar (H2O) environment is difficult but possible via a lab-on-chip, with polymeric dyes immobilized on paper or nylon membranes. Here arrays of 12 hydrophobic poly(p-phenyleneethynylene)s (PPEs), are assembled into a chemical tongue to detect/discriminate nitroarenes in water. The changes in fluorescence image of the PPEs when interacting with solutions of the nitroarenes were recorded and converted into color difference maps, followed by cluster analysis methods. The variable selection method for both paper and nylon devices selects a handful of PPEs at different pH-values that discriminate nitroaromatics reliably. The paper-based chemical tongue could accurately discriminate all studied nitroarenes whereas the nylon-based devices represented distinguishable optical signature for picric acid and 2,4,6-trinitrotoluene (TNT) with high accuracy.

Synthesis and characterization of Cu(II) complexes supported by a pyridylamide ligand

In our effort to understand the impact of ligand platforms on the structure diversity and chemical properties of copper clusters, a tripod pyridylamide ligand H3tpmbc was used in this work. Two one-dimensional polymeric Cu(II) complexes [Cu(H3tpmbc)Cl2]n (1) and [Cu2(H3tpmbc)Cl4]n (2) were isolated and characterized. X-ray crystallography analysis showed that both structures have a similar one-dimensional backbone. The main structure difference of the two complexes is the presence of a second Cu(II) site in complex 2. Hirshfeld analysis revealed the presence of interesting C–H⋅⋅⋅π and π⋅⋅⋅π interaction networks in both complexes. Spectroscopic characterization of both complexes and [CuPyCl2] suggests the source of the color difference between the two polymers at the solid state. Computational studies based on the X-ray crystal structures were performed and the results provided a deeper understanding of the electronic structures of the Cu(II) site(s) in both complexes. Thermal gravimetric analysis (TGA) demonstrated that the two complexes have the similar thermal behavior, and this could be attributed to the similar one-dimensional backbone structure.

Scalable hierarchical BayeSN inference: Investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift

Abstract We apply the hierarchical probabilistic SED model BayeSN to analyse a sample of 475 SNe Ia (0.015 &amp;lt; z &amp;lt; 0.4) from Foundation, DES3YR and PS1MD to investigate the properties of dust in their host galaxies. We jointly infer the dust law RV population distributions at the SED level in high- and low-mass galaxies simultaneously with dust-independent, intrinsic differences. We find an intrinsic mass step of −0.049 ± 0.016 mag, at a significance of 3.1σ, when allowing for a constant intrinsic, achromatic magnitude offset. We additionally apply a model allowing for time- and wavelength-dependent intrinsic differences between SNe Ia in different mass bins, finding ∼2σ differences in magnitude and colour around peak and 4.5σ differences at later times. These intrinsic differences are inferred simultaneously with a difference in population mean RV of ∼2σ significance, demonstrating that both intrinsic and extrinsic differences may play a role in causing the host galaxy mass step. We also consider a model which allows the mean of the RV distribution to linearly evolve with redshift but find no evidence for any evolution - we infer the gradient of this relation ηR = −0.38 ± 0.70. In addition, we discuss in brief a new, GPU-accelerated Python implementation of BayeSN suitable for application to large surveys which is publicly available and can be used for future cosmological analyses; this code can be found here: https://github.com/bayesn/bayesn.

Preparation of Yellowing-Resistant Waterborne Polyurethane Modified with Disulfide Bonds.

Waterborne polyurethane, renowned for its lightweight properties, excellent insulation capabilities, and corrosion resistance, has found extensive application in fields such as construction, automotive, leather, and thermal insulation. Nevertheless, during operational usage, waterborne polyurethane materials, akin to other polymeric substances, are susceptible to oxidative aging manifestations like yellowing, cracking, and diminished mechanical performance, significantly curtailing their utility. Consequently, the synthesis of yellowing-resistant polyurethane assumes pivotal significance. This study integrates dynamic reversible reactions into the synthesis process of polyurethane by introducing the dynamic reversible compound 2-hydroxyethyl disulfide as a chain extender, alongside the incorporation of a UV absorber to enhance the polyurethane's resistance to yellowing. When the disulfide bonds absorb heat, they undergo cleavage, yielding thiols that spontaneously recombine into disulfide bonds at ambient temperatures, allowing for the continuous breaking and reformation of disulfide bonds to absorb heat. Concurrently, in collaboration with the UV absorber, the detrimental effects of ultraviolet radiation on the polyurethane material are mitigated, thereby augmenting its resistance to yellowing. This study scrutinizes the positioning of UV absorber addition, the quantity of UV absorber, and the molar ratio of 1,4-butanediol to 2-hydroxyethyl disulfide, characterizing the functional groups of polyurethane through infrared and Raman spectroscopy. It is observed that the successful preparation of yellowing-resistant polyurethane is achieved, and evaluations on the modified polyurethane through color difference, tensile, and centrifugal tests reveal that the optimal yellowing resistance is attained by adding a UV absorber at a mass fraction of 1% to 3% prior to chain extension, resulting in a color change grade of 2, denoting slight discoloration. Simultaneously, the other properties of polyurethane exhibit relative stability. Notably, when the molar ratio of 1,4-butanediol to 2-hydroxyethyl disulfide is 3:2, the overall performance of the polyurethane remains stable, with exceptional yellowing resistance capabilities attaining a color change grade of 2.

Characterization of Red Cabbage Extracts incorporated in Green Based Gelatin Active Films

This study aimed to assess red cabbage extracts obtained using solvents with different pH levels and alcohol concentrations, comparing their phytochemical quantities and functional characteristics. Solvents—purified water (PW, pH 7), 70% and 99% ethanol (70%E and 99%E, pH 6.5), and acidified ethanol (AE, pH 2)—were employed for extraction. When the different pH solutions were applied to the red cabbage extracts, they altered the extract's color, ranging from pink to yellow, influenced by various anthocyanin forms responsive to pH levels. The AE-extracted red cabbage displayed the highest UV and visible light barrier and total phenolic content (TPC). Then, the AE extract was used to formulate the green-based gelatin active films, alongside the 99%E extract, which had similar alcohol content and TPC values. The films averaged 20-21 μm in thickness. Moreover, incorporating both extracts into the gelatin films increased moisture content and water solubility, though the change in water vapor permeability was not significant compared to the neat gelatin film. The gelatin film incorporating AE-extracted red cabbage (GAE) showed higher water solubility than that incorporating the 99%E extract (GE). Both green-based gelatin active films showed differences in appearance color in the third week. The GAE film exhibited greater color stability, attributed to anthocyanin's distinctive chemical structures favoring acidic environments. This gelatin film incorporating red cabbage by AE-extracted holds promise as an eco-friendly active food packaging material.

A Hybrid Image Augmentation Technique for User- and Environment-Independent Hand Gesture Recognition Based on Deep Learning

This research stems from the increasing use of hand gestures in various applications, such as sign language recognition to electronic device control. The focus is the importance of accuracy and robustness in recognizing hand gestures to avoid misinterpretation and instruction errors. However, many experiments on hand gesture recognition are conducted in limited laboratory environments, which do not fully reflect the everyday use of hand gestures. Therefore, the importance of an ideal background in hand gesture recognition, involving only the signer without any distracting background, is highlighted. In the real world, the use of hand gestures involves various unique environmental conditions, including differences in background colors, varying lighting conditions, and different hand gesture positions. However, the datasets available to train hand gesture recognition models often lack sufficient variability, thereby hindering the development of accurate and adaptable systems. This research aims to develop a robust hand gesture recognition model capable of operating effectively in diverse real-world environments. By leveraging deep learning-based image augmentation techniques, the study seeks to enhance the accuracy of hand gesture recognition by simulating various environmental conditions. Through data duplication and augmentation methods, including background, geometric, and lighting adjustments, the diversity of the primary dataset is expanded to improve the effectiveness of model training. It is important to note that the utilization of the green screen technique, combined with geometric and lighting augmentation, significantly contributes to the model’s ability to recognize hand gestures accurately. The research results show a significant improvement in accuracy, especially with implementing the proposed green screen technique, underscoring its effectiveness in adapting to various environmental contexts. Additionally, the study emphasizes the importance of adjusting augmentation techniques to the dataset’s characteristics for optimal performance. These findings provide valuable insights into the practical application of hand gesture recognition technology and pave the way for further research in tailoring techniques to datasets with varying complexities and environmental variations.

Effect of curing mode of resin composite cements on water sorption, color stability, and biaxial flexural strength

ObjectivesTo determine whether water sorption and solubility of a recently introduced self-adhesive cement is comparable to two clinically tested resin composite cements after thermal aging, and if this is affected by the curing mode. Whether water sorption is correlated with color difference and biaxial flexural strength was also investigated. MethodsWater sorption and solubility of three resin composite cements {RelyX Universal (RUV), (Panavia V5 (PV5), Panavia SA plus (PSA)} were measured after thermal aging. Disk-shaped specimens were either light-cured or autopolymerized (n=15 per group). Color difference ΔE00 and biaxial flexural strength were also obtained. ResultsSorption was highest for RUV (auto: 54.9 ± 9.0µg/mm3, light: 49.7 ± 4.9µg/mm3), followed by PSA (auto: 37.7 ± 1.4µg/mm3, light: 34.5 ± 1.1µg/mm3) and PV5 (auto: 21.7 ± 0.7µg/mm3, light: 22.1 ± 0.4µg/mm3). Light-curing reduced solubility values, particularly for RUV (from 60.7 ± 20.8µg/mm3 to 6.4 ± 0.8µg/mm3). Color differences of ΔE00 > 1.8 (considered clinically not acceptable) were noted after aging for RUV and PSA. Sorption and ΔE00 values after aging were correlated linearly (R2 = 0.970). Biaxial flexural strength values were highest for PV5 (light: 153.4 ± 15.9MPa; auto: 133.2 ± 18.0MPa) and lowest for RUV (light: 99.3 ± 12.8MPa; auto: 35.1 ± 8.3MPa). SignificanceLight-curing has beneficial effects on sorption, color stability, and biaxial flexural strength of resin composite cements. Cements containing 2-hydroxymethacrylate such as RUV and PSA are more prone to water sorption and color changes.

Microwave heating concentration of raspberry pulp: Evaluation of processing variables on concentration characteristics and quality attributes

Concentration of fruit pulp is an important unit operation in food processing and has a wide range of applications. In this study, the microwave heating concentration (MHC) of raspberry pulp at different microwave powers, heating times and sample masses were investigated considering concentration characteristics and quality attributes. The results showed that increasing microwave power/heating time or decreasing sample mass significantly decreased the moisture content but had no significant effect on the temperature of raspberry pulp, while these conditions resulted in loss of total anthocyanin content and deterioration of total color difference. LF-NMR and SEM results revealed that the changes in temperature and moisture content caused by MHC significantly affected the total anthocyanin content and total color difference of the final product. Microwave power of 800 W, heating time of 3 min and sample mass of 90 g are selected as suitable parameters for MHC of raspberry pulp. This study may provide guidance for the development of appropriate technology for MHC of berry pulp.