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Computational Colour Science Using MATLAB, 2nd Edition
Computational Colour Science Using MATLAB 2nd Edition offers a practical, problem-based approach to colour physics. The book focuses on the key issues encountered in modern colour engineering, including efficient representation of colour information, Fourier analysis of reflectance spectra and advanced colorimetric computation. Emphasis is placed on the practical applications rather than the techniques themselves, with material structured around key topics. These topics include colour calibration of visual displays, computer recipe prediction and models for colour-appearance prediction.Each topic is carefully introduced at three levels to aid student understanding. First, theoretical ideas and background information are discussed, then explanations of mathematical solutions follow and finally practical solutions are presented using MATLAB. The content includes:A compendium of equations and numerical data required by the modern colour and imaging scientist.Numerous examples of solutions and algorithms for a wide-range of computational problems in colour science.Example scripts using the MATLAB programming language.This 2nd edition contains substantial new and revised material, including three innovative chapters on colour imaging, psychophysical methods, and physiological colour spaces; the MATLAB toolbox has been extended with a professional, optimized, toolbox to go alongside the current teaching toolbox; and a java toolbox has been added which will interest users who are writing web applications and/or applets or mobile phone applications.Computational Colour Science Using MATLAB 2nd Edition is an invaluable resource for students taking courses in colour science, colour chemistry and colour physics as well as technicians and researchers working in the area. In addition, it acts a useful reference for professionals and researchers working in colour dependent industries such as textiles, paints, print & electronic imaging.Review from First Edition:\"...highly recommended as a concise introduction to the practicalities of colour science...\" (Color Technology, 2004)
eBook
Skin color-specific and spectrally-selective naked-eye dosimetry of UVA, B and C radiations
Spectrally–selective monitoring of ultraviolet radiations (UVR) is of paramount importance across diverse fields, including effective monitoring of excessive solar exposure. Current UV sensors cannot differentiate between UVA, B, and C, each of which has a remarkably different impact on human health. Here we show spectrally selective colorimetric monitoring of UVR by developing a photoelectrochromic ink that consists of a multi-redox polyoxometalate and an e
−
donor. We combine this ink with simple components such as filter paper and transparency sheets to fabricate low-cost sensors that provide naked-eye monitoring of UVR, even at low doses typically encountered during solar exposure. Importantly, the diverse UV tolerance of different skin colors demands personalized sensors. In this spirit, we demonstrate the customized design of robust real-time solar UV dosimeters to meet the specific need of different skin phototypes. These spectrally–selective UV sensors offer remarkable potential in managing the impact of UVR in our day-to-day life.
Current ultraviolet (UV) sensors cannot differentiate between UVA, B and C, each of which has a remarkably different impact on human health. Here the authors show spectrally-selective colorimetric monitoring of ultraviolet radiations by developing a photoelectrochromic ink that consists of a multiredox polyoxometalate and an e
–
donor.
Journal Article
RNA-extraction-free nano-amplified colorimetric test for point-of-care clinical diagnosis of COVID-19
The global pandemic of coronavirus disease 2019 (COVID-19) highlights the shortcomings of the current testing paradigm for viral disease diagnostics. Here, we report a stepwise protocol for an RNA-extraction-free nano-amplified colorimetric test for rapid and naked-eye molecular diagnosis of COVID-19. The test employs a unique dual-prong approach that integrates nucleic acid (NA) amplification and plasmonic sensing for point-of-care detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a sample-to-assay response time of <1 h. The RNA-extraction-free nano-amplified colorimetric test utilizes plasmonic gold nanoparticles capped with antisense oligonucleotides (ASOs) as a colorimetric reporter to detect the amplified nucleic acid from the COVID-19 causative virus, SARS-CoV-2. The ASOs are specific for the SARS-CoV-2 N-gene, and binding of the ASOs to their target sequence results in the aggregation of the plasmonic gold nanoparticles. This highly specific agglomeration step leads to a change in the plasmonic response of the nanoparticles. Furthermore, when tested using clinical samples, the accuracy, sensitivity and specificity of the test were found to be >98.4%, >96.6% and 100%, respectively, with a detection limit of 10 copies/μL. The test can easily be adapted to diagnose other viral infections with a simple modification of the ASOs and primer sequences. It also provides a low-cost, rapid approach requiring minimal instrumentation that can be used as a screening tool for the diagnosis of COVID-19 at point-of-care settings in resource-poor situations. The colorimetric readout of the test can even be monitored using a handheld optical reader to obtain a quantitative response. Therefore, we anticipate that this protocol will be widely useful for the development of biosensors for the molecular diagnostics of COVID-19 and other infectious diseases.
This protocol provides an RNA extraction–free nano-amplified colorimetric test that enables rapid detection of SARS-CoV-2 with the naked eye. The test uses plasmonic gold nanoparticles capped with antisense oligonucleotides as a colorimetric biosensor for point-of-care diagnosis of COVID-19.
Journal Article
Digital postprocessing and image segmentation for objective analysis of colorimetric reactions
Recently, there has been an explosion of scientific literature describing the use of colorimetry for monitoring the progression or the endpoint result of colorimetric reactions. The availability of inexpensive imaging technology (e.g., scanners, Raspberry Pi, smartphones and other sub-$50 digital cameras) has lowered the barrier to accessing cost-efficient, objective detection methodologies. However, to exploit these imaging devices as low-cost colorimetric detectors, it is paramount that they interface with flexible software that is capable of image segmentation and probing a variety of color spaces (RGB, HSB, Y’UV, L*a*b*, etc.). Development of tailor-made software (e.g., smartphone applications) for advanced image analysis requires complex, custom-written processing algorithms, advanced computer programming knowledge and/or expertise in physics, mathematics, pattern recognition and computer vision and learning. Freeware programs, such as ImageJ, offer an alternative, affordable path to robust image analysis. Here we describe a protocol that uses the ImageJ program to process images of colorimetric experiments. In practice, this protocol consists of three distinct workflow options. This protocol is accessible to uninitiated users with little experience in image processing or color science and does not require fluorescence signals, expensive imaging equipment or custom-written algorithms. We anticipate that total analysis time per region of interest is ~6 min for new users and <3 min for experienced users, although initial color threshold determination might take longer.
This protocol provides ImageJ-based workflows for the analysis of images obtained from colorimetric assays. New users can take advantage of a basic workflow; more experienced users can benefit from more advanced analysis procedures.
Journal Article
Instant and low-cost detection of urinary microalbumin using smartphone technology and a paper-based platform with a colorimetric ratio analysis
Early detection of microalbuminuria is essential for preventing the progression of nephropathy and improving patient management. The present research proposes a simple, low-cost dye-binding method based on a standard addition principle for determining urinary albumin at clinically significant levels. The assay principle of the proposed paper-based analytical device is based on utilizing a specific and sensitive dye, bis(3′,3″-diiodo‐4′,4″‐dihydroxy‐5′,5″‐dinitrophenyl) ‐3,4,5,6-tetrabromosulfonphthalein (DIDNTB), which binds to urinary albumin under extreme low pH conditions. The strategy was based on testing with three different albumin concentrations in the urine samples to obtain different color intensity ratios denoted as R1, R2, and R3, and further used to calculate a semi-quantitative amount of albumin. Under the optimized conditions, the linear range from 10 to 200 mg/L albumin and the detection limit 8.2 mg/L (R
2
= 0.99) was obtained. Interference studies revealed that glucose, ascorbic acid, uric acid, L-histidine, and globulin were in the acceptable recovery range (89–109%). Reproducibility assessments showed that the coefficients of variation (CV) for this method ranged between 3.7% and 7.7%. Additionally, receiver operating characteristic (ROC) plots were generated to establish the cut-off value for instant semi-quantitative interpretation of the results. Results from real sample analysis revealed that the proposed method is comparable to a widely used quantitative immunoturbidity method (
r
= 0.94,
n
= 50).
Journal Article
Optical sensors for determination of biogenic amines in food
This review presents the state-of-the-art of optical sensors for determination of biogenic amines (BAs) in food by publications covering about the last 10 years. Interest in the development of rapid and preferably on-site methods for quantification of BAs is based on their important role in implementation and regulation of various physiological processes. At the same time, BAs can develop in different kinds of food by fermentation processes or microbial activity or arise due to contamination, which induces toxicological risks and food poisoning and causes serious health issues. Therefore, various optical chemosensor systems have been devised that are easy to assemble and fast responding and low-cost analytical tools. If amenable to on-site analysis, they are an attractive alternative to existing instrumental analytical methods used for BA determination in food. Hence, also portable sensor systems or dipstick sensors are described based on various probes that typically enable signal readouts such as photometry, reflectometry, luminescence, surface-enhanced Raman spectroscopy, or ellipsometry. The quantification of BAs in real food samples and the design of the sensors are highlighted and the analytical figures of merit are compared. Future instrumental trends for BA sensing point to the use of cell phone–based fully automated optical evaluation and devices that could even comprise microfluidic micro total analysis systems.
Journal Article
Rapid recognition of volatile organic compounds with colorimetric sensor arrays for lung cancer screening
Volatile organic compounds (VOCs) in breath can be used as biomarkers to identify early stages of lung cancer. Herein, we report a disposable colorimetric array that has been constructed from diverse chemo-responsive colorants. Distinguishable difference maps were plotted within 4 min for specifically targeted VOCs. Through the consideration of various chemical interactions with VOCs, the arrays successfully discriminate between 20 different volatile organic compounds in breath that are related to lung cancer. VOCs were identified either with the visualized difference maps or through pattern recognition with an accuracy of at least 90%. No uncertainties or errors were observed in the hierarchical cluster analysis (HCA). Finally, good reproducibility and stability of the array was achieved against changes in humidity. Generally, this work provides fundamental support for construction of simple and rapid VOC sensors. More importantly, this approach provides a hypothesis-free array method for breath testing via VOC profiling. Therefore, this small, rapid, non-invasive, inexpensive, and visualized sensor array is a powerful and promising tool for early screening of lung cancer.
Journal Article