RGB Color Mode Research Articles

Design of microfluidic fluorescent sensor arrays for real-time and synchronously visualized detection of multi-component heavy metal ions

The majority of the environmental heavy metal ions exist in the form of multi-components, and the current single-to-single rapid detection methods are unable to meet the needs of simultaneous multi-component detection. Here, we have designed a microfluidic fluorescence sensor array by combining microfluidic sensing and organic fluorescent switches for the real-time and simultaneous visual detection of multi-component heavy metal ions. A series of “light-up” organic molecular probes was designed and synthesized, exhibiting a strong ability to bind heavy metal ions and resulting in the opening of probe fluorescence. Meanwhile, we design microfluidic sensor plate, the patterned path of the microfluidic plate has drainage channel wall and 2.70° downward slope, which can enable the samples to quickly reach the detection area. By loading organic molecular probes into the detection area, the microfluidic sensor array achieves simultaneous detection of four heavy metal ions. Combined with intelligent terminal, read and analyze the RGB color mode (RGB) results of detection, obtain quantitative information. The microfluidic fluorescence sensor array developed here can meet the requirements for in situ and semi-quantitative detection of a range of heavy metal ions with a low detection limit, fast reaction speed, and without the need for pretreatment. It represents a novel engineering technology approach for real-time detection of multi-components in the environment.

Unconventional luminescent CS–PEC-based composite hemostasis sponge with antibacterial activity and visual monitoring for wound healing

Multifunctional wound dressings are promising medical materials for various applications. Among them, dressings with antimicrobial activity, high biosafety, and real-time monitoring have attracted considerable research interest. Herein, a biodegradable hemostatic sponge comprising a chitosan skeleton and polyelectrolyte–surfactant complex (CS–PEC) was developed as a versatile wound dressing for wound pH monitoring and inhibition of bacterial infection. CS–PEC sponge with high porosity exhibited satisfactory fluid absorption capacity and biocompatibility, along with antibacterial properties against E. coli and S. aureus. In vivo experiments in rat liver trauma model revealed that wounds treated with the CS–PEC sponge recorded less blood loss (97.1 mg) and shorter hemostasis time (27.2 s) than those treated with commercial gelatin sponge (309.1 mg and 163.5 s, respectively). Furthermore, PECs based on unconventional luminescent molecules (L-C16-Hyp) were used as pH fluorescent indicators, which endowed the sponge with fluorescence-responsive behavior to wound pH changes in the range of 5.0–8.5. Visual images can be captured using a smartphone and converted to RGB color mode values for on-site assessment of wound status. This study sheds light on the design and application of unconventional luminescent materials in wound dressing and provides a smart and effective solution for wound management.

A three-in-one versatile sensor for concise detecting biogenic amines and beef freshness

Biogenic amines (BAs), as important indicators for evaluating food spoilage caused by fermentation processes or microbial activities, present significant risks of food safety. Consequently, the development of a simple, sensitive, and selective detection method for amines is of great importance. In this study, we proposed a three-in-one sensor 3,6-bis(dimethylamino)-9-(ethylthio)xanthylium (PSE) for high sensitivity and selectivity detecting BAs with multimodal responses, including olfactory, colorimetric, and fluorescent signals, thus facilitating convenient real-time detection of BAs. Mechanism study indicated that the nucleophilic substitution of PSE with BAs induced such rapid multi-responses with a low detection limit (LOD = 0.03 μM). We further fabricated PSE loaded paper for portable detection of BAs vapors. And the accurate determination of BAs levels is achieved through analyzing the RGB color mode. Finally, we successfully applied these test strips for non-destructive assessing meat beef freshness with the assistance of a smartphone in on-site scenarios.

Facile preparation of a dual-emission paper-based fluorescent sensor based on carbon quantum dots and rhodamine B for dual-mode detection of Hg2+

In this study, carbon quantum dots (CQDs) and rhodamine B (RhB) were physically mixed to construct a highly selective and sensitive ratiometric fluorescent sensor (CQDs@RhB) for the quantitative and visual detection of Hg2+. After adding Hg2+, the emission peak of CQDs at 445 nm was quenched and the peak of RhB at 575 nm remained unchanged; the ratio of the two emission peaks had a linear relationship with the Hg2+ concentration. The CQDs@RhB had a detection range of 0–15 µM and the limit of detection (LOD) is 65.93 nM and a color change from blue to pink was visible to the naked eye under ultraviolet light. The study revealed a static quenching mechanism of CQDs@RhB. The established method was successfully applied to the detection of Hg2+ in real water and rice samples with satisfactory results. In addition, a portable fluorescent paper-based sensor platform was developed using computer software assistance. The relationship with Hg2+ concentration was constructed by converting the pictures obtained under ultraviolet light to RGB color mode for visualization and quantitative detection of Hg2+. This study provides a valuable strategy for constructing a rapid detection system for Hg2+ in the field.

Luminescent MOF-Based Nanofibers with Visual Monitoring and Antibacterial Properties for Diabetic Wound Healing.

Diabetic wound healing remains as a serious challenge for medical circles that required continuous monitoring and effective management. Herein, the glucose oxidase/carbon dots@copper-metal-organic framework-based nanofibers (GOx/CDs@MOF NFs) were proposed as a multifunctional wound dressing, aiming to visually monitor wound pH and inhibit bacterial infection. In the diabetic wound microenvironment, the GOx/CDs@MOF NFs could convert endogenous glucose into hydroxyl radial (•OH) through the cascade catalytic reaction. In vivo and vitro experimental results confirmed that the GOx/CDs@MOF NFs could efficiently kill bacteria and promote wound healing. Additionally, CDs as a pH fluorescent indicator endowed GOx/CDs@MOF NFs with sensitive and reversible fluorescent sensing behavior to wound pH, and these visual images could also be captured by smartphones and transformed into RGB color mode (red, green, blue) values, allowing for onsite evaluation of the wound status. This multifunctional wound dressing provides a smart and effective solution for diabetic wound management and takes an immeasurable step toward the development of the next generation of digitally visualized wound dressings.

Enabling Intelligent IoTs for Histopathology Image Analysis Using Convolutional Neural Networks.

Medical imaging is an essential data source that has been leveraged worldwide in healthcare systems. In pathology, histopathology images are used for cancer diagnosis, whereas these images are very complex and their analyses by pathologists require large amounts of time and effort. On the other hand, although convolutional neural networks (CNNs) have produced near-human results in image processing tasks, their processing time is becoming longer and they need higher computational power. In this paper, we implement a quantized ResNet model on two histopathology image datasets to optimize the inference power consumption. We analyze classification accuracy, energy estimation, and hardware utilization metrics to evaluate our method. First, the original RGB-colored images are utilized for the training phase, and then compression methods such as channel reduction and sparsity are applied. Our results show an accuracy increase of 6% from RGB on 32-bit (baseline) to the optimized representation of sparsity on RGB with a lower bit-width, i.e., <8:8>. For energy estimation on the used CNN model, we found that the energy used in RGB color mode with 32-bit is considerably higher than the other lower bit-width and compressed color modes. Moreover, we show that lower bit-width implementations yield higher resource utilization and a lower memory bottleneck ratio. This work is suitable for inference on energy-limited devices, which are increasingly being used in the Internet of Things (IoT) systems that facilitate healthcare systems.

Adoption of Artificial Intelligence Along with Gesture Interactive Robot in Musical Perception Education Based on Deep Learning Method

The present work aims to improve students’ interest in music teaching and promote modern teaching. A distributed application system of artificial intelligence gesture interactive robot is designed through deep learning technology and applied to music perception education. First, the user’s gesture instruction data is collected through the double channel convolution neural network (DCCNN). It uses the double-size convolution kernel to extract feature information in the image and collect the video frame’s gesture instruction. Secondly, a two-stream convolutional neural network (two-stream CNN) recognizes the collected gesture instruction data. The spatial and temporal information is extracted from RGB color mode (RGB) images and optical flow images and input into the two-stream CNN to fuse the prediction results of each network as the final detection result. Then, the distributed system used by the interactive robot is introduced. This structure can improve the stability of the interactive systems and reduce the requirements for local hardware performance. Finally, experiments are conducted to test the gesture command acquisition and recognition network, and the performance of the gesture interactive robot in practice. The results indicate that combining convolution kernels of [Formula: see text] and [Formula: see text] can increase the recognition accuracy of DCCNN to 98% and effectively collect gesture instruction data. The gesture recognition accuracy of two-stream CNN after training reaches 90%, higher than the mainstream dynamic gesture recognition algorithm trained with the same data set. Finally, the recognition test of gesture instructions is carried out on the gesture interactive robot reported here. The results show that the recognition accuracy of the gesture interactive robots is more than 90%, meeting the routine interaction needs. Therefore, the interactive gesture robot has good reliability and stability and is applicable to music perception teaching. The research reported here has guiding significance for establishing music teaching with multiple perception modes.

Image Aided Recognition of Wireless Capsule Endoscope Based on the Neural Network.

Wireless capsule endoscopy is an important method for diagnosing small bowel diseases, but it will collect thousands of endoscopy images that need to be diagnosed. The analysis of these images requires a huge workload and may cause manual reading errors. This article attempts to use neural networks instead of artificial endoscopic image analysis to assist doctors in diagnosing and treating endoscopic images. First, in image preprocessing, the image is converted from RGB color mode to lab color mode, texture features are extracted for network training, and finally, the accuracy of the algorithm is verified. After inputting the retained endoscopic image verification set into the neural network algorithm, the conclusion is that the accuracy of the neural network model constructed in this study is 97.69%, which can effectively distinguish normal, benign lesions, and malignant tumors. Experimental studies have proved that the neural network algorithm can effectively assist the endoscopist's diagnosis and improve the diagnosis efficiency. This research hopes to provide a reference for the application of neural network algorithms in the field of endoscopic images.

The coloring mechanism of a novel golden variety in &lt;i&gt;Populus deltoides&lt;/i&gt; based on the RGB color mode

Compared to flower color and red leaf mutants, the mechanism of yellow leaf formation in woody plants is more complicated and less understood. Poplars are common and widely distributed perennial trees. Here, we obtained a golden leaf mutant poplar variety (JHY) and compared it with its original green leaf poplar (<i>Populus sp</i>. Linn. ‘2025’) in terms of phenotype, pigment content, the transcriptomes and metabolomes. Through transcriptome sequencing, we found that the chlorophyll degradation genes, and the genes in anthocyanin metabolism in JHY were up-regulated compared to L2025 and the carotenoid synthesis genes were down-regulated. Further based on HPLC-ESI-MS/MS technology, 16 differentially expressed anthocyanins were identified, 14 reddish anthocyanins of which were significantly up-regulated. According to these results, we proposed a coloring mechanism of JHY based on the RGB color mode. The yellow color of carotenoids and the red color of anthocyanins overlay each other, combined with a reduction in chlorophyll, turning the leaves golden. This study systematic analyzes the causes of golden leaf formation through the omics integration approach, which will provide reference for the breeding of golden leaf trees.

Неопределенности поглощенной дозы, измеренной дозиметром GAFCHROMIC EBT3 на клинических электронных и фотонных пучках медицинских ускорителей

Purpose: Investigation of the relative errors of absorbed dose measurement based on polymer films Gafchromic EBT3 for clinical electron and photon beams of medical accelerators.&#x0D; Material and methods: Polymer Gafchromic EBT3 films were calibrated using different radiation beams, namely photon and electron beams of Elekta Axesse medical accelerator with beam energy equal to 10 MV and 10 MeV, correspondingly, and electron beam of a betatron for intraoperative radiotherapy with beam energy equal to 6 MeV. The film pieces were irradiated by the uniform dose field in the dose range from 0.5 to 40 Gy. The dose value was controlled by cylindrical ionization chamber in the case of Elekta Axesse accelerator and by the Markus parallel chamber in the case of betatron. The irradiated films were scanned using Epson Perfection V750 Pro flatbed scanner in 16 bit RGB color mode with 150 dpi resolution. The red and green channels were used for further analysis. The central part of each film was used for calculation of average values of net optical density and its root-mean-square. As a result, the calibration curves, i.e. dependence on the reference absorbed dose measured by ionization chamber on the net optical density were constructed taking into account uncertainties of dose measurement and optical density measurement.&#x0D; Results: The relative uncertainty for the dose measurement lies within 7 % for low doses (less than 1 Gy) and within 4 % for higher doses. The green channel is less sensitive to the radiation, but its relative uncertainty values are in general 1–2 % lower than the ones for the red channel. The use of different calibration sources results in different calibration curves with difference up to ±6 % for the green channel.&#x0D; Conclusion: The polymer Gafchromic EBT3 films could be used for absorbed dose measurement for the doses not less than 0.5 Gy. For lower dose values the dose measurement uncertainty caused by statistical reasons amounts 15 %. For dose values of about 1 Gy and higher the dose measurement uncertainty amounts 5 % that allows to use the films for transverse and longitudinal prescription treatment dose distribution measurement with very high spatial resolution.

Microstructure changes in radiochromic films due to magnetic field and radiation

To correlate the dose response and changes in microscopic structures of the radiochromic films exposed to the clinical magnetic field in the range 1.5-3 T with standard and flattening filter-free (FFF) photon beams. The radiochromic film was cut into 5 × 5 cm2 sheets/samples from one batch. These samples were exposed to a 1.5-T and/or 3-T B-fields from an MRI scanner using an abdominal sequence for 7 min before and after irradiation with 6 MV and/or 6 MV FFF beams. Films were placed in a reference condition at 5 cm depth in a solid water phantom and exposed up to 20 Gy. The sample orientation was maintained the same during exposure, readout, and scanning electron microscopic (SEM) analysis. The samples were scanned with an Epson Expression 11000XL in a 48-bit RGB color mode at 300 dpi with red channel. Scanned images were processed in Image J and red channel mean intensity values were recorded. The samples were then coated with 6 nm gold and imaged by SEM Teneo (5 kV, 13 pA) under 2000, 2500, and 3000 magnifications for texture analysis. The changes in the microstructure of the films in magnetic fields (1.5- and 3.0-T) were dose dependent. The orientation and granular size of samples at higher doses were altered compared to the controls. Needle-shaped structures of the active layer were longer and aligned for samples exposed to higher doses and magnetic field. However, no significant changes in optical density due to the presence of a magnetic field pre/postirradiation up to 20 Gy were observed. Fine structures of the film represent the polymerization characteristics that are affected by the radiation dose in the magnetic field. Upon exposure to radiation, diacetylene monomers undergo polymerization that forms longer chains with a temporal response. Even though this study did not notice any significant changes in optical density due to the presence of magnetic field, this should be studied in simultaneous application of the magnetic field during treatment in a dedicated MR-linac unit.

Functional whipped confection of new composition

Was studied the technology of producing whipped products on agar with substitute of egg white with premium wheat flour. Was proved the choice - chicory powder. Determined dispersity of whipped masses and found that with the chicory powder proportion of air bubbles with size of less than 0.3 mm increases. This is due to reduction of moisture aerated intermediate product that leads to an increase in the mass and improve the dispersion of structural and mechanical properties of the finished product. Determined the antioxidant activity of the product with chicory powder. This rate is 40% higher than in the control sample, because of a high content of vitamin in the powder. Determined the organoleptic and physical-chemical indicators of quality. The intensity of color was determined using computer image processing in RGB color mode. The highest intensity of color is 244 conventional units, was observed in the sample taken for control, because the product contains the minimum amount of coloring substances. The intensity of the color of the sample with chicory powder is reduced by 50 conventional units, which indicates a change in the color of the product from light-colored to darker. Energy value of whipped product with chicory powder is 271 kcal (1134 kJ). Nutritional value of the product is more than in a control sample for potassium content in 2.2 times; vitamins A and C - 1.1 and 0.9 times respectively. carbohydrate content was reduced by 15%. Products enriched with chicory powder have a pleasant taste and aroma, attractive appearance, which eliminates the usage of chemical dyes and fragrances. In addition, the products have high nutritional value, contain inulin. They can be recommended for adults and children, especially those who suffer from intolerance to egg protein.

Research of color characteristics of sugar production intermediates

It is known that in a sugar production, only about 80% of sucrose, extracted from the beet, is output as a commercial product. The rest is lost during the processing or remains in intermediates. The color of white sugar is mainly determined by the color of the returned to the first stage of crystallization of the brown sugars melt. An effective way to improve the quality of melt is affination of brown sugars. Coloring substances are preferably present in the film on the surface of sugar crystals. To improve the efficiency of affination experiments were carried out by layer-by-layer processing of the normalized crystal size with the saturated solution of white sugar. To evaluate the numerical characteristics of the color of the samples studied scanerometrical method followed by computer processing of images in RGB color mode was used. The studies suggest that the solution of the starting yellow sugar having visual yellow color intensively absorbs 450–480 nm of spectrum, so there is no blue component in the graphs. During the affination removing of coloring substances from the surface of crystals takes place changing the light absorption intensity. There is a bleaching of the samples at affination duration up to 3 minutes. Further 5–10 min treatment is accompanied by partial diffusion of colorants from mother liquor to the surface of crystals and improved chromaticity. Prolonged affination results in crystals abrasion; it is accompanied by unproductive energy consumption on the mixing process. The results obtained indicate that the effective removal of coloring substances occurs within 1–3 minutes of affination. In this case brown sugar chromaticity decreases from 625 to 130–230 units of optical density and mother liquor chromaticity is increased from 20 to 900–1600 units of optical density. The studies suggest that most of the coloring substances determining the chromaticity of yellow sugars is found in the film on the crystal surface and is easily removed by 3 min long affination. Method of determining of objects color characteristics in RGB system describes adequately the intermediates coloring of sugar production and can be used in research.

High Precision Traffic Monitoring Alert System using Image Background Subtraction

Objective: Monitoring the road traffic is helpful to know about the traffic density of a particular location, which helps in redirecting the traffic when crowded. In this paper, traffic density is monitored and vehicle count is estimated using background subtraction algorithm. Methods: The proposed technique utilizes a novel Motion Detection and Running Gaussian Average (MDRGA) recursive technique. The frame is captured from the input video sequence and is transformed to 0 to 255 gray levels from RGB color mode. This conversion considers the RGB values for each pixel and yield the corresponding reflectance value proportional to the brightness percentage of that pixel. The edge detection is then performed on the gray converted by locating the pixels of the image that correspond to the edges. Findings: The proposed system detects motion by comparing sequential frames crossing an imaginary line marked in the reference frame. Thus, the traffic density is detected and the proposed method is found to be efficient in terms of cost, quality and accuracy. This algorithm fetches the input video quickly from camera or storage device, processes immediately and gives the count of vehicles. This proposed system avoids occlusion problems and gives better results. Applications/ Improvements: This algorithm is helpful to avoid traffic collisions at peak areas, to avoid accidents and to reach the destination on time. Thus, the proposed system finds its application in real time systems and provides risk free environment.

The 3D Surface Measurement and Simulation for Turbine Blade Surface Based on Color Encoding Structural Light

This paper proposes a color encoding structural light approach for the three-dimensional measurement of turbine blade surface. It adopts RGB color mode design coding scheme, by using the six basic colors, red, green, blue, yellow, magenta, and cyan for color-coded stripes. Every three stripes are grouped together, while the color combinations for each group are different. The coding pattern based on these color stripes is projected to the blade. A CCD camera then captures the image modulated by the blade. We then decode this image to obtain the three-dimensional coordinates of the measured points on blade surface. According to the structure light measurement principle, we designed and determined the parameters of the three-dimensional measurement. This paper established a mathematical model of a turbine blade through simulation by using 3ds max software. We designed a threedimensional measurement system for the simulation, and obtained the three-dimensional coordinates of the blade surface by measuring the turbine blade. Finally, the threedimensional blade model reconstructed by the measured data is established.

An Approach to Detection of Solder Joints on Printed Circuit Boards

To automate present Automatic Optical Inspection (AOI) systems, an intelligent method based on lightness analysis for solder joints detection is proposed in this paper. Firstly, the image taken from real printed circuit board (PCB) is preprocessed and segmented. Then, we compute the image similarity by calculating the Euclidean distance. If the similarity exceeds the threshold, we extract the lightness of solder joints by converting between RGB color mode and HLS color mode. Lastly, all the defects of solder joints are classified into several different types according to their lightness appearances. Experiment results show that the method deduced in this paper can detect accurately solder defects from different patches.

Computerized Color Distinguishing System for Color Printed Fabric by Using the Approach of Probabilistic Neural Network

This article proposes an innovative color printed fabric computer color distinguishing system whose main functions are to precisely distinguish the printed fabric pattern colors and match colors to improve the current time-consuming color distinguishing conducted by manpower. The RGB color mode is an industrial color standard, by which the change and overlapping of color channels of red, green, and blue represent types of colors. RGB stands for red, green, and blue, respectively. It is one of the most widely used color system and covers almost all of the colors sensible to human vision. Hence, this paper adopts the RGB color mode to present color printed fabric images. First, to reduce the color distinguishing computation, a genetic algorithm was applied in search of small images of the same color in the original color printed fabric. Then, color distinguishing computation was conducted by a probabilistic neural network (PNN), which has the advantage of a very fast learning speed. Finally, PANTONE® standard color tickets were applied in matching colors. The experimental results revealed that the PNN design can easily realize and achieve accurate, fast color classification. It is proved that this color distinguishing system can be practically applied in printed fabric color distinguishing and matching.

Use of Computer-Assisted Color Treatment of Chromatograms in the TLC Determination of Tartrazine

A procedure was developed for the treatment of thin-layer chromatograms in the analysis of the Tartrazine E102 synthetic food dye. The procedure includes the conversion of a TLC plate into the Windows 95/98 bit-mapped graphics format using scanning on a flatbed scanner followed by the processing of the image obtained with the Adobe Photoshop 5.0 program package in the RGB color mode (red, green, and blue color channels).