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A colorimetric sensing method based on a paper-based vapor-test kit was successfully developed for the selective and sensitive real-time monitoring of formalin in food samples. The device was specifically designed to efficiently extract and detect formalin simultaneously. A microcentrifuge tube was used as the sample solution container, with the inner cap serving as the reaction and detection zone. Formalin was converted into gaseous formaldehyde through controlled heating, which was then extracted and collected on a filter paper coated with Nash's reagent. The color change on paper was used for formalin quantification using a smartphone for detection and image analysis. Under optimal conditions, our method provided a linear range of 0.5–75 mg L−1 with a detection limit of 0.11 mg L−1. This method effectively determined formalin in fresh food and vegetable samples, with recoveries ranging from 92 to 111%, demonstrating comparable accuracy to the standard method for practical food quality control and safety. [Display omitted] • A sensitive paper-based vapor-test kit was successfully developed for formalin. • This innovative approach combined headspace extraction, PADs, and image analysis. • An efficient sensing test kit represents a significant advancement for rapid, on-site detection of formalin in food products. • The sensor is cost-effective by utilizing commercially available materials. [ABSTRACT FROM AUTHOR]

Hydrophobic properties belong to the most important factors which determine functional properties of paper products. A number of methods related to the measurement of the interaction between water and paper are already used but most of them give results after specific period of time whereas many unit operations in modern industrial processes (e.g. printing) last usually less than one second. As a result, most of the existing methods are not corresponding to today’s requirements. The aim of the presented research was to develop the method based on image analysis for measuring the dynamics of penetration and permeation of liquid through paper. Special device named eXtended Liquid Penetration Analyser (XLPA) was built for this purpose. Based on the obtained results, the method developed allows to observe and analyse the dynamics of liquid permeation through paper. The proposed method fully replaces the method implemented in the PLG Sizing Tester, which estimated the time of a 50% decrease in brightness of a tested paper sample permeated by ink. Presented method offers the possibility of quantitative measurement of changes in liquid absorption with time resolution of 1/60 s. At the same time, thanks to the use of a camera and image analysis, it is possible to detect local areas of non-homogeneity in paper structure that differ with regards to their capability to absorb liquid, as well as to determine quantitative measures that characterize the non-homogeneity of the permeation process with reference to paper surface. [ABSTRACT FROM AUTHOR]

Sensor arrays, which draw inspiration from the mammalian olfactory system, are fundamental concepts in high-throughput analysis based on pattern recognition. Although numerous optical sensor arrays for various targets in aqueous media have demonstrated their diverse applications in a wide range of research fields, practical device platforms for on-site analysis have not been satisfactorily established. The significant limitations of these sensor arrays lie in their solution-based platforms, which require stationary spectrophotometers to record the optical responses in chemical sensing. To address this, this review focuses on paper substrates as device components for solid-state sensor arrays. Paper-based sensor arrays (PSADs) embedded with multiple detection sites having cross-reactivity allow rapid and simultaneous chemical sensing using portable recording apparatuses and powerful data-processing techniques. The applicability of office printing technologies has promoted the realization of PSADs in real-world scenarios, including environmental monitoring, healthcare diagnostics, food safety, and other relevant fields. In this review, we discuss the methodologies of device fabrication and imaging analysis technologies for pattern recognition-driven chemical sensing in aqueous media. [Display omitted] • Cross-reactive sensors are applied to paper-based arrays for simultaneous detection. • Portable digital recorders can be used for detecting various responses. • Imaging analysis techniques can accelerate accurate data processing. [ABSTRACT FROM AUTHOR]

Paper used in the printing industry generally contains a relatively thin porous coating covering a thicker fibrous base layer. The three-dimensional pore structure of coatings has a major effect on fluid flow patterns inside the paper medium. Understanding and quantifying the flow properties of thin coating layers is hence crucial. Pore spaces within the coating have an average size of about 180 nm. We used scanning electron microscopy combined with focused ion beam (FIB-SEM) to visualize the nano-scale pore structure of the paper coating layer. Post-processing of the FIB-SEM images allowed us to reconstruct the three-dimensional pore space of the coating. The 3D FIB-SEM images were analyzed in detail to obtain pore size distribution and porosity value. The permeability was estimated using the GeoDict software, based on solutions of the Stokes equation. By determining the porosity and permeability of increasingly larger domain sizes, we estimated the size of a representative elementary volume (REV) for the coating layer to be 60 µm 3 , which is well within the volume analyzed using FIB-SEM. The estimated porosity and permeability of the REV domain were 0.34 and 0.09 mDarcy, respectively. Using the pore morphology method, capillary pressure-saturation ( P c - S ) and relative permeability curves of the REV domain could be constructed next. The P c -S curves showed that the coating had a high air entry suction, which is very favorable for printing in that ink will invade the coating as soon as it is applied to the coating. Our results are essential for macroscale modelling of ink penetration into a coating layer during inkjet printing. Macroscopic models can be valuable tools for optimization of the penetration depth and the spreading of ink on and within paper substrates. [ABSTRACT FROM AUTHOR]

[Display omitted] • Assessment of ash from co-combustion of bark and sludges for nutrient recovery. • P amounts indicate that ash from co-combustion can be useful as a soil improver. • Morphology of slag particles was analysed with X-ray micro-tomography. • Overall, a high number of small and discrete pores. • Relatively thick particle walls and few pore openings indicates a need of grounding. Recycling phosphorus from waste streams for fertilization purposes could contribute to a sustainable society. The production in the pulp and paper industry results in several waste streams, among others nutrient-rich sludges in different forms. This study presents a detailed chemical and 3D characterization of ash from co-combustion of bark and two types of sludges from a paper mill; mixed sludge and biosludge. The combustion performance was investigated for these experiments and advanced analysis methods were used to characterise the ashes to correlate chemical and physical properties relevant for nutrient recycling. The elemental composition was determined by energy-dispersive X-ray spectroscopy; dominating crystalline phases by X-ray diffraction; and morphology, porosity, pore size distribution and active surface area of the slag were analysed with synchrotron-based X-ray micro-tomography and image analysis. Slag was formed in all combustion experiments to a large extent with increasing amounts with a higher proportion of sludge. Nutrient amounts indicate that slag particles from co-combustion of both biosludge and mixed sludge can be useful either as a soil improvement directly or for recovery processes. Slag from combustion of 30 wt% biosludge and 70 wt% bark contained the highest amount of phosphorus, 9 at % on a C and O free basis. Evaluation of tomography data showed that discrete and open pores could be distinguished on a micrometre scale. The porosity of the slag varied between the replicates and fuel mixtures, on average between 17 and 23 vol% for the bark and sludge mixtures. Open pore volume displayed large variations, on average 39–56 vol% of the pores were open pores connected to the surrounding volume. For all samples, 90 % of the pores were small, with an equivalent diameter under 30 μm, but the largest pore volume (80–90 %) consists of pores with an equivalent diameter over 75 μm. In soils, pores with a minimum equivalent diameter over 30 μm generally transmit water and the smaller pores store water. The slag particles have relatively thick walls, with few pore openings to the surroundings, indicating that the slag needs to be pre-treated by milling or crushing before application in the soil. [ABSTRACT FROM AUTHOR]

This article introduces a novel approach by coupling paper points with hollow fiber membrane for electroextraction (PP–HF-EE). The method was innovatively applied to extract methylene blue (MB) from large water volumes (up to 580 mL). A comprehensive study of six key parameters – organic filter, acceptor and donor phase composition, extraction time, applied voltage, and sample volume – was conducted using conventional flatbed scanning and digital image analysis. Our results revealed that extraction performance was primarily influenced by time, with low voltages (50 V) and low-conductivity organic filters (1-decanol) yielding comparable results to higher settings (300 V or 1-pentanol). Under optimized conditions (50 V, 60 min, 1-decanol as the organic filter), analytical performance parameters were assessed, demonstrating acceptable precision (RSD <18% for intra- and inter-day measurements) within a linear range of 5–100 μg L−1 (r = 0.98). PP–HF–EE demonstrated reliability through stable and reproducible electric current measurements during all extraction studies. Utilizing an extremely cost-effective detection system, PP–HF–EE achieved detection limits in the low ppb range, highlighting its potential as a promising variation of electromembrane extraction for environmental sample analysis. [Display omitted] • A new electroextraction approach for environmental samples was presented. • Paper point after extraction was subsequently examined by digital image analysis. • Quantification of methylene blue in tap water was achieved in the low ppb range. • The new electroextraction approach might be promising for environmental analysis. [ABSTRACT FROM AUTHOR]

A novel green fabrication approach is being proposed based on radiation assisted modification of Whatman filter paper 1 (WFP) for development of Acid Free-Paper based Analytical Devices (A f -PADs). A f -PADs exude immense potential as handy tools for on-site detection of toxic pollutants such as, Cr(VI), boron, etc., which have established detection protocols involving acid mediated colorimetric reactions that necessitate external acid addition. The proposed A f -PAD fabrication protocol asserts its novelty through elimination of external acid addition step, making the detection process safer and simpler. To achieve this, poly(acrylic acid) (PAA) was grafted onto WFP via a single step, room temperature process of gamma radiation induced simultaneous irradiation grafting, introducing acidic -COOH groups in the paper thereon. Grafting parameters namely, absorbed dose and concentrations of monomer, homopolymer inhibitor and acid were optimized. The -COOH groups incorporated in PAA-grafted-WFP (PAA- g -WFP) provide localized acidic conditions for colorimetric reactions between pollutants and their sensing agents, anchored on the PAA- g -WFP. A f -PADs loaded with 1,5-diphenylcarbazide (DPC) have been ably demonstrated for visual detection and quantitative estimation of Cr(VI) in water samples using RGB image analysis, with LOD value of 1.2 mg.L−1 and a measurement range comparable to that of commercially available PADs based Cr(VI) visual detection kits. [Display omitted] [ABSTRACT FROM AUTHOR]

Development and application of a new, simple, inexpensive, and eco-friendly method is presented for the quantification of bumetanide in human urine samples for the detection of doping in sports. The method involves the use of a paper platform and digital image detection and is based on the reaction between bumetanide, p -dimethylaminocinnamaldehyde (p -DAC), and HCl in a methanolic medium, yielding a colored compound in a delimited area on a qualitative filter paper. The concentrations of p- DAC and HCl were optimized by a chemometric experimental design. After the addition of the reagents to the paper, digital images were obtained by scanning in a multifunctional printer and analyzed using the RGB pattern. The linear bumetanide concentration range was 6.90 × 10−5–1.37 × 10−3 mol L−1 with R 2 = 0.993 and the limits of detection (LOD) and quantification (LOQ) were 3.60 × 10−4 and 1.09 × 10−4 mol L−1, respectively. A SPE clean-up step for the samples were required to eliminate the interference of urinary urea. The recoveries obtained varied from 94% to 105%, indicating the absence of significant matrix effects or interferences in urine samples after clean-up step. The proposed method was successfully applied to the analysis of bumetanide in human urine samples. • Spot test employing a paper platform delimited with hydrophobic barriers • μPAD associated with digital image detection for bumetanide determination • Determination of bumetanide in urine samples for doping sports • The method represents an advantageous alternative to most of the reported methods. [ABSTRACT FROM AUTHOR]

Cyanide anion can be found in foodstuffs, tobacco smoke and a variety of types of waters, mainly originating from anthropogenic activities. Due to its highly toxic nature, several agencies have established limits for cyanide levels in water. Additionally, monitoring cyanide levels in biological samples, such as blood and urine, is crucial for obtaining clinical information about the health condition of patients. Therefore, there is a pressing need for the development of simple, cost-effective, and reliable analytical methods capable of quantifying cyanide at low concentrations. This study presents a novel analytical method for the selective and sensitive determination of cyanide based on analyte volatilization, pre-concentration via single-drop microextraction (SDME) using a selective reagent, and colorimetric quantification using a paper-based analytical device. For this, 10 mL of a liquid sample was acidified with phosphoric acid and the generated HCN was collected using a single drop of 3 μL of a palladium dimethylglyoximate solution (Pd (DMG) 2 2−) positioned in the flask headspace using a syringe. The reaction of Pd (DMG) 2 2− leads to the formation of Pd(CN) 4 2− and the demasking of the organic ligand. After 15 min of extraction time, the reagent drop was added to a paper-based analytical device that has been previously impregnated with 3 μL of nickel chloride, resulting in the formation of a red precipitate of nickel (II) dimethylglyoximate. Digital images of the paper-based device were captured and the red channel (R) was used for quantification purposes. Under optimized conditions, the method demonstrates a suitable linear relation (r2 > 0.99) ranging from 26 to 286 μg L−1 and a limit of detection of 5 μg L−1. As a proof of concept, cyanide levels were quantified in water and urine samples using this method. The proposed approach offers high sensitivity and selectivity while requiring only a small volume of reagents. Furthermore, it exhibits a high degree of portability for in-situ applications. A selective and sensitive method for the determination of cyanide using HS-SDEM. [Display omitted] • Cyanide in liquid samples was determined by combining HS-SDME and digital image analysis. • Colorimetric reaction is performed on a microfluidic paper-based analytical device. • The reagent is easy to prepare and highly selective for cyanide. • Under optimized conditions, a limit of detection of 5 μg L-1 was achieved. • The point-of-care device is suitable for cyanide determination in water and urine samples. [ABSTRACT FROM AUTHOR]

Abstract: A method for the comparison of paper structure using light transmission images and frequency analysis was developed. The resolution of the light transmission images and the algorithm for the feature extraction were greatly improved to enhance the visibility of peaks in the 2D power spectrum that results from frequency analysis. A comparison method based on correlation measures how well the spectra match as a function of the orientation of the paper, yielding an objective and quantitative measure of similarity between 0 and 1. A technical validation was carried out with 25 different papers showing the potential of this method with common copy papers. Finally, the method was applied in a case. [Copyright &y& Elsevier]

Highlights • This is the first report on total lipid profile using a paper-based microfluidic device. • Pearson Correlation Coefficient (R) of 0.903, 0.9727, 0.9939 and 0.9866 for TC, LDL, HDL, and TG respectively as compared to conventional method. • The analysis can be done in a single device with as small as 10 μL of the serum sample. Abstract In this communication, a novel surface modification method of the paper surface using 3-aminopropyltriethoxysilane (APTES) and gold nanoparticles is reported. This functionalized paper (flower-shaped paper-based microfluidic devices (F-PMD) for simultaneous assay of multiple analytes) is used for determination of total lipid profiling (TLP) in a single device. Here, we have determined total cholesterol along with low-density lipoprotein (LDL), high-density lipoprotein (HDL) and triglycerides (TGL). The LDL and HDL were estimated by erasing the non-HDL and non-LDL components with a help of precipitating reagents. Standard graphs prepared by the present paper-based method nicely correlates with the conventional method (calculated by Roche- COBAS C111 autoanalyzer) with Pearson Correlation Coefficient (R) of 0.903, 0.9727, 0.9939 and 0.9866 respectively for total cholesterol, LDL, HDL and triglycerides. The present assay device is intended to assist in the screening of individual's lipid level for diagnosis of disorders involving high cholesterol level in the blood or for metabolic disorders associated with lipid and lipoprotein. As this is affordable, miniaturized, easily portable, self-testing and rapid, the present assay device can be used easily by pre-clinical, non-professionals, children in schools, labs, etc as a point-of-care diagnostics. [ABSTRACT FROM AUTHOR]

[Display omitted] • A simple colourimetric µPAD for the real-time detection of bilirubin. • The developed µPAD can detect bilirubin concentrations up to 950 µM. • The detection is based on the formation of green-coloured copper-bilirubin complex. • Quantification of bilirubin using ImageJ software in RGB and LAB colour spaces. A paper-based colourimetric assay for the Point-of-Care Testing (PoCT) of bilirubin has been developed based on the formation of a green-coloured copper-bilirubin complex from a blue-coloured tetraamminecopper(II) sulphate complex. The reaction was studied and optimized by UV–Visible absorption spectroscopy and translated onto a paper strip. Hydrophobic circular well patterns on Whatman chromatography paper were created by wax printing. The tetraamminecopper(II) sulphate complex was drop cast and dried on the reagent zones in the wax-patterned paper. The images of reagent zones captured using a scanner were analyzed using ImageJ software. Bilirubin spiked blood serum was tested in the concentration range of 1.2 to 950 µM. The PAD exhibited sensitivities of 0.4197 a.u/μM and 0.1040 a.u/μM for concentration ranges of bilirubin 1.2 to 96 μM and 105 to 950 μM respectively and a low detection limit of 0.799 µM. The method is highly selective to bilirubin, even in the presence of other biomarkers in serum. A plasma separation membrane incorporated PAD was fabricated for the final testing and quantification of bilirubin from whole blood. [ABSTRACT FROM AUTHOR]

• A novel analytical method based on origami paper-based microfluidic device as a platform for paper chromatography. • Device fabrication processes is a simple single side printing and curing paper. • Consumption low amount of reagents/solvents and cost-effective analysis. • The method does not require any sample pretreatment step, applying a raid analytical procedure by the green aqueous solvent Herein, we report three-dimensional paper chromatography (3D-PC) as a micro-chromatographic platform. The method was based on applying the origami microfluidic device for separation, coupled by colorimetric methods for simultaneous determination. The microfluidic device fabrication was a facile printing approach. Two azo food dyes, Tartrazine (E102) and Indigo carmine (E132), were selected as a model analyte, while carbonate-bicarbonate buffer was used as the mobile phase. Our micro-chromatographic device is associated with two big advantages including needing very small volume of mobile phase (~12 µL) and ultrafast separation time (~35 s). Under the optimal conditions, the method provided acceptable linear ranges of 0. 0 g L 1–18.0 g L 1 (R2 = 0.997) for E102 and 0.070 g L 1–10.0 g L 1 for E132 and the limits of detection (3σ/slope) were evaluated as 0.620 and 0.060 g L 1, respectively. The proposed method was successfully applied in the separation and quantification of these dyes in commercial food products such as jelly, candy, and four kinds of drink samples without any sample preparation prior to analysis. The mean recovery values for the real sample analysis were in the range of 100.14%–102.38% for E132 and E102 respectively. The inter-device relative standard deviations were in the ranges of 1.5%–11.8%. In total, our chromatographic μPAD is small (1.0 cm × 1.0 cm × 0.5 cm), portable, inexpensive, no need of specialized user, requires low volumes of sample (0.5 μL), and can perform separation using 12 μL of aqueous mobile phase in very short time. [ABSTRACT FROM AUTHOR]

This article describes the design and fabrication of a novel lab-on-paper device for pH sensing using curcumin nanoparticles (CURNs). In order to fabricate the lab-on-paper, the wax dipping method was used. The color of loaded paper with CURNs changed from yellow to orange and red to brown in the pH range of 7–13. The image of the lab-on-paper was taken by a digital camera and the picture was processed and analyzed using Adobe Photoshop software. The change in mean color intensity with pH was recorded and employed as an analytical signal for quantitative sensing of pH. The parameters affecting the pH sensor were optimized to enhance the selectivity and sensitivity of the method. Under optimum conditions, the mean color intensity was linearly proportional to the pH in the range of 8–13. The relative standard deviations of 10 replicate measurements of pH 9 and pH 12 were 2.3% and 1.5%, respectively. The developed sensor was successfully applied to the determination of pH in different water samples with satisfactory results. [ABSTRACT FROM AUTHOR]

A challenge in developing microfluidic devices for fully portable and automated field analyses is the ability to integrate and store reagents in a stable form while maintaining a low cost for the system. Paper-based field-deployable devices are currently the most extensively explored platforms for field use; however, centrifugal devices offer a means for heightened device automation and portability. The basis for many field devices is chemical sensing via colorimetric reactions. Here, we describe the development of polyester-paper hybrid microfluidic devices using a fabrication method, compounded from the print, cut and laminate (PCL) technique, that allows for simple yet effective dry reagent storage for enhanced use with centrifugal or polymeric-based devices. We utilized various proof-of-principle colorimetric assays for multiple applications, including the analysis of total protein, serum albumin, cocaine, 2,4,6-trinitrotoluene (TNT) and iron content. Localized reagent integration facilitated by paper punches allowed for both reagent stability prior to reaction for storage, color stability post-reaction for image analysis, and was compatible for multi-step analyses. Qualitative and quantitative results were achieved with the broad range of sample applications trialed here, while still maintaining the ability for downstream processing. [ABSTRACT FROM AUTHOR]

Abstract: The reaction kinetics of alkaline phosphatase (ALP) adsorbed on paper was quantified by image analysis using a colorimetric technique under conditions of excess enzyme. A classical reaction kinetics approach integrated with image processing technique was used to analyse the coloured product formation from the enzyme substrate reaction against time. The order of reaction and rate constant of enzyme activities on paper surface were calculated. ALP was either physisorbed directly on paper or adsorbed on paper treated with a monolayer of a high molecular weight cationic polyacrylamide (CPAM), an anionic polyacrylic acid (PAA) or a high molecular weight polyethylene oxide (PEO). The reaction rate of enzymatic paper follows a first order reaction with respect to the concentration of enzyme–substrate complex. ALP immobilized on paper has a reaction rate 2 to 3 orders of magnitude lower than the free ALP enzyme in buffer solution. This might be due to a critical loss of enzyme flexibility upon adsorption. No increase in reaction rate was achieved by immobilizing ALP on paper treated with a high molecular weight cationic polyacrylamide (CPAM) or a highly charged anionic polyacrylic acid oligomer (PAA), which suggests the enzyme orientation was not significantly affected. However, the reaction rate for ALP on PEO treated paper was lower than that on CPAM or PAA treated papers. That is probably due to some PEO-enzyme interaction affecting the tertiary structure of the ALP enzyme. [Copyright &y& Elsevier]

This work describes a fast and simple assay for in situ detection of thiocyanate, i.e., a biomarker of tobacco smoke exposure, in human saliva. The assay is based on the formation of an iron(III)-thiocyanate colored complex in a paper-based sensing platform and subsequent image analysis using a scanner as detection device. Experimental parameters influencing the color intensity of the complex were fully evaluated, including the selection of detection conditions, type of paper substrate, test zone dimensions and composition as well as the stability of the paper-based device. Under optimal conditions, the detection limit was 0.06 mM of thiocyanate, and the repeatability, expressed as relative standard deviation, was 3%. The proposed method, characterized by its simplicity, portability and low sample consumption, was applied to the detection of thiocyanate in a series of human saliva samples. Average thiocyanate levels in the ranges 0.28–0.87 mM and 0.78–4.28 mM were found for non-smokers and smokers, respectively. Recovery studies were carried out at two concentration levels, showing recovery values in the range of 96.1–103.6%. [ABSTRACT FROM AUTHOR]

[Display omitted] • Dual-color paper-based aptasensor is developed for visual detection of OTA and ZEN. • A hydrophobic paper substrate is made via laser printing and heating treatment. • A smartphone is used to capture and analyze the fluorescent images. • ZEN and OTA can be analyzed with LODs down to 0.44 ng/mL and 0.098 ng/mL. A portable paper-based microfluidic aptasensor is established to simultaneously and visually detect zearalenone (ZEN) and ochratoxin A (OTA). The targets at the sample zone can migrate to two detection zones through dual-channels and result in green and blue fluorescence recovery. This is due to the specific recognition by a respective aptamer that destroys fluorescence resonance energy transfer (FRET) from dual-color upconversion nanoparticles (UCNPs) to Cu-TCPP nanosheets. By capturing fluorescent images and analyzing the corresponding RGB value via a smartphone, ZEN and OTA can be analyzed with limits of detection down to 0.44 ng/mL and 0.098 ng/mL in the linear ranges of 0.5–100 ng/mL and 0.1–50 ng/mL, respectively. Satisfactory recoveries are also obtained for ZEN (94.5–103.7 %) and OTA (92.2–106.8 %) in corn flour. With the advantages of simple operation, low sample consumption, and broad adaptability, this promising platform allows for the on-site detection of multiple hazards in food. [ABSTRACT FROM AUTHOR]

• LAMP reaction is performed on NC and Filter paper membranes for E. coli detection. • Dried LAMP reagents and detection dye are added to the membrane prior to DNA sample. • Filter paper demonstrated uniform distribution of DNA amplicons across the surface. • E. coli detection results are retained for a longer time on filter paper membranes. • Extent and rate of LAMP amplification reaction is higher in Filter paper membranes. Paper-based point-of-care (POC) devices have attracted tremendous attention because of low-cost, simple fabrication, and portability. LAMP-based POC platform comprises a paper substrate on which the DNA amplification reaction occurs. The quality of the paper substrate plays a critical role in performing an efficient LAMP reaction and for effective visualization of the amplification result. The major objective of the current work is to replace the frequently utilized nitrocellulose (NC) membrane by a cost-effective and high quality paper membrane viz. Whatman filter paper (WF) for rapid detection of E. coli via LAMP reaction. Isolated DNA is added on the paper membranes, which undergo LAMP reaction. The effect of initial DNA concentration and time on LAMP amplification reaction rate is analyzed on paper membranes via image analysis for the first time. Overall study inferred that WF is suitable for effective naked-eye detection and greater extent of LAMP reaction (generation of 19 968 DNA copies). [ABSTRACT FROM AUTHOR]

The in-plane fiber orientation distribution has a decisive impact on paper mechanical and dimensional properties (e.g., tensile stiffness, hygroexpansion). It is usually estimated offline through relatively expensive bench instrumentation such as diffusion-based optical methods and ultrasonic devices. In this work we present an alternative methodology that is fast, portable, inexpensive and able to provide the complete surface polar fiber orientation profile. The proposed technology combines an image acquisition setup, consisting of a digital camera with a low angle illumination system, with the gradient-segmentation method (GSM), a robust image analysis algorithm. This camera-GSM methodology presented high internal consistency, accurately identifying the angles of samples subjected to known rotations at the imaging step. The methodology also produced comparable results to the TSO (tensile stiffness orientation) technique, used as reference. The methodology is easily transferable to plant operation, including for the online assessment of fiber orientation. • A new image-based methodology was proposed to estimate the in-plane fiber orientation. • It just requires a digital camera equipped with a low angle illumination system. • The image analysis algorithm developed (GSM) is a gradient method with adaptive thresholding scheme. • Consistency and accuracy of the proposed methodology was assessed and confirmed. • The proposed methodology has potential for online monitoring of fiber orientation. [ABSTRACT FROM AUTHOR]

Abstract: Background: Sample collection instructions for the bloodspot lead screening program conducted by the Nebraska Medical Center recommend continuous application of a single finger-stick blood drop per printed filter paper circle (a volume of approximately 50 μl). In this study, we assessed whether apparent blood volumes and geometries of finger-stick bloodspot samples submitted for lead testing were consistent with collection recommendations. Methods: Samples were 422 extra bloodspots from 138 patients that were submitted for lead analysis. Using image analysis, apparent blood volumes were computed by comparison of bloodspot areas to bloodspot areas for standards of known volume. Circularity of samples was also assessed by image analysis. Results: Mean blood volume (25±13 μl) was approximately 50% of that needed to fill a printed circle. The distribution of volumes had three local maxima, consistent with bloodspot formation by multiple discrete applications of blood drops of small volumes (17±6 μl) rather than by continuous application of blood. Multi-drop samples were also apparent from non-circular geometries. Conclusions: Bloodspots submitted for lead analysis showed an apparently inherent drop volume of less than 20 μl per drop and the application of multiple drops. Non-ideality of such specimens indicates the need for continuing education of bloodspot collectors. [Copyright &y& Elsevier]

Foodborne pathogens are major public health concerns worldwide. Paper-based microfluidic devices are versatile, user friendly and low cost. We report a novel paper-based single input channel microfluidic device that can detect more than one whole-cell foodborne bacteria at the same time, and comes with quantitative reading via image analysis. This microfluidic paper-based multiplexed aptasensor simultaneously detects E. coli O157:H7 and S. Typhimurium. Custom designed particles provide colorimetric signal enhancement and false results prevention. Several aptamers were screened and the highest-affinity aptamers were optimized and employed for detection of these bacteria in solution, both in a buffer as well as pear juice. Image analysis was used to read and quantify the colorimetric signal and measure bacteria concentration, thus rendering this paper based microfluidic device quantitative. The colorimetric results show linearity over a wide concentration range (102 C F U / m L to 108 C F U / m L) and a limit of detection (LOD) of 103 C F U / m L and 102 C F U / m L for E. coli O157:H7 and S. Typhimurium, respectively. An insignificant change in colorimetric response for non-target bacteria indicates the aptasesnors are specific. The reported multiplexed colorimetric paper-based microfluidic devices is likely to perform well for on-site rapid screening of pathogenic bacteria in water and food products. [ABSTRACT FROM AUTHOR]

A novel method is presented for distinguishing postal stamp forgeries and counterfeit banknotes from genuine samples. The method is based on analyzing differences in paper fibre networks. The main tool is a curvelet-based algorithm for measuring overall fibre orientation distribution and quantifying anisotropy. Using a couple of more appropriate parameters makes it possible to distinguish forgeries from genuine originals as concentrated point clouds in two- or three-dimensional parameter space. [ABSTRACT FROM AUTHOR]

Highlights: [•] Public displays, paper and web forms were compared as feedback mechanisms. [•] We examined the quantity and quality of feedback obtained from each medium. [•] Public displays produced a high quantity of feedback but mostly noise. [•] Paper and web forms generated lower quantity of feedback but better quality. [•] Public displays can be leveraged as significant interest generators. [ABSTRACT FROM AUTHOR]

Spray deposit and superficial coverage play key roles in phytosanitary treatments. Their measurement is a quite complex task that requires adding suitable tracers to the mixture (deposit) and using some artificial targets (superficial coverage). With these laboratory tests, unit deposit values, measured in Petri dishes containing silicon oil, were correlated with percentage of covered surface, measured with water sensitive papers (WSPs) after spraying a water solution with red Ponceau at 2% concentration. An Albuz ATR 80 hollow cone nozzle was used at the spraying pressures of 0.3, 0.5, 1.0 and 1.5 MPa. The results showed a significant correlation between unit deposit d u (μL cm−2) and the fraction of covered surface x S ( d u = 2.2095 ⋅ x S − 0.3473 , R2 = 0.761, p -level < 0.001), that could allow estimating spray deposition from WSP analysis only, even with high values of percentage of superficial coverage (30%–80%). Moreover, measured data were used to simulate the WSP behaviour. The results of simulation showed that in a practical spray application with a high fraction of superficial coverage, spread factors higher than those reported in WSP datasheets should be considered. • Laboratory tests with Albuz ATR80 hollow cone nozzle at four pressures. • Drop size distribution measured by following ISO 5682-1:1996 standard procedure. • Unit deposit = 2.2095 × fraction of covered surface – 0.3473. • WSP model with increased spread factor. • To adapt the model for other working conditions. [ABSTRACT FROM AUTHOR]

Existing microfluidic technologies for blood tests have several limitations, including difficulties in integrating the sample preparation steps, such as blood dilution, and precise metering of tiny samples (microliter) for accurate downstream analyses on a chip. Digital microfluidics (DMF) is a liquid manipulation technique that can provide precise volume control of micro or nano-liter liquid droplets. Without using sensitive but complex detection methods for tiny droplets involving fluorescence, luminescence, and electrochemistry, this article presents a DMF device with embedded paper-based sensors to detect blood lithium-ion (Li+) concentration by colorimetry. Dielectrophoresis on the DMF device between two parallel planar electrodes separates plasma droplets (from tens to hundreds of nanoliters in volume) from undiluted whole blood (a few microliters) within 4 min with an efficiency exceeding 90%. The embedded paper sensors contain a detection reagent to absorb the DMF-transported plasma droplets. These droplets change the color of the paper sensors in accordance with the Li+ concentration. Subsequently, colorimetry is used to reveal the Li+ concentration via image analysis. The proposed method meets the detection-sensitivity requirement for clinical diagnosis of bipolar disorder, making the DMF device a potential therapeutic tool for rapid whole-blood Li+ detection. • Plasma droplets can be separated from whole blood via dielectrophoresis with DMF. • Paper sensor–embedded DMF devices can detect lithium ions via colorimetry. • Detection of lithium ions in whole blood can be completed within 4 min. [ABSTRACT FROM AUTHOR]

A paper-based colourimetric assay for the detection of alanine transaminase has been developed. In the presence of alanine transaminase, 2,4-dinitrophenyl hydrazine changes to pyruvate hydrazone leading to a colour change from pale yellow to dark yellow. Reaction conditions were optimized using absorption spectroscopic studies. Hydrophobic patterns on the Whatman chromatographic paper were created by wax printing, and the reagents were drop cast at the reagent zone. On the paper device, the intensity of the yellow colour increases with ALT concentration in the range of 20–140 U/L in human serum. For the quantification of ALT, coloured images were captured using a digital camera and were processed with Image J software. The machine learning approach was also explored for the ALT analysis by training with colour images of the paper device and testing using a cross-validation procedure. The results obtained with real clinical samples on the paper device showed good accuracy of less than 5% relative error with the clinical lab results. Furthermore, the paper device shows high selectivity to ALT in the presence of various interfering species in blood serum with a sensitivity of 0.261 a.u/(U/L), a detection limit of 4.12 U/L, and precise results with an RSD of less than 7%. For the testing of whole blood, a plasma separation membrane was integrated with the patterned paper. [Display omitted] • Colourimetric detection of ALT on paper strip using 2,4-DNPH. • Negligible interference from other biomolecules. • Tested with serum and ALT spiked serum samples. • Plasma separation membrane incorporated strip used for testing of blood samples. • Quantification of ALT on paper strip using ImageJ and Machine learning approach. [ABSTRACT FROM AUTHOR]

Enzymatic versus chemical deinking is examined for MOW and photocopy prints. Several enzymatic preparations and two fibre/ink particle separation methods are tested. Deinking was monitored by image analysis and standard pulp and paper characterisation procedures. The effectiveness of the fibre/ink particle separation method depends on the ink particle’s size: for smaller particles a washing step is recommended whereas for larger particles, the use of flotation is necessary. The enzymatic treatment is a competitive alternative for MOW and photocopy paper deinking. However, the process requires the selection of an adequate enzymatic preparation for each paper grade. [Copyright &y& Elsevier]

Chronic Kidney Disease (CKD) is becoming one of the major causes of morbidity and mortalities in 21st century. We have developed a bioengineered cellulosic paper device for the quantification of albumin (ALB) in physiological samples. The paper surface was activated and antibodies specific to target biomarker was immobilized on engineered paper surface. Every step after modification was characterized by FTIR, XPS, SPM and optical analysis. Further, the device model was designed using CAD file, and a 3-D cascade device was fabricated with in-built constant light source to provide proper and controlled environment for in-situ image analysis. After adding the sample on the bioengineered paper, the antigen-antibody reaction takes place, after that addition of dye results in change of color from yellow to blueish-green within 40 s. An optical method was employed for the analysis of the images by recognizing the specific area and the color intensity. Additionally, the immunosensor specificity was evaluated on number of molecules that are usually found in the serum sample. The linear dynamic range of the developed immunosensor has been reported to be 1–60 mg/mL, covering the normal as well as clinical range of ALB in physiological samples with a detection limit of 0.049(±0.002) mg/mL. With good precision and recovery, the device was able to successfully determine the ALB concentrations in serum sample. The developed device has simple and user-friendly interface and it may also help diagnosing CKD in personalized settings. [ABSTRACT FROM AUTHOR]

Abstract: The porosity and specific surface areas of four industrial paper materials were determined from synchrotron X-ray microtomography. The porosity profile within the thickness of each paper material shows that a paper sheet consists of three layers: two boundary layers, which present a strong gradient of porosity, and a “bulk” layer in which the porosity is almost constant. The anisotropy and the heterogeneity scale of the microstructure in the “bulk” layer was then analyzed by means of covariograms. It is shown that the microstructure of the four studied papers is transverse isotropic and that the anisotropy of papers containing fillers is less pronounced. Finally, the representative elementary volume (REV) for both studied microstructural properties was evaluated using two techniques: a systematic analysis of the influence of the volume size on the property measurement, and a statistical methodology. The REVs given by both methodologies are then compared. [Copyright &y& Elsevier]

• A fluorimetric detection of gold on microfluidic paper device was developed using a common cellphone and analysis using Photoshop software. • The new paper device was combined with fire-assay method in analysis of gold in ores. • This sensor had good LOD due to three stage pre-concentration. • New method proved to work comparable to reference assay (Fire-assay-AAS) The present study was conducted to develop a simple, low-cost and sensitive micro fluidic paper-based analytical device (µPAD) for analysis of gold in geological samples. This µPAD was fabricated employing eyeliner pencil method. It consists of different zones, including detection, pH adjustment, reaction and elution. We injected 29 µL elution solution in the center of µPAD, direct Au3+, after adjusting pH, to make it react with rhodamine B. The formation of RB-Au3+ complex led to quench of rhodamine B fluorescence. The image of each detection zone was captured using a cell phone camera under a UV lamp, and luminosity intensity was subsequently measured with Photoshop software. Various parameters were studied in order to achieve the most efficient performance of the paper sensor. Under the optimized condition, a wide linear range (1–40 mg L−1, R2 = 0.996) was obtained with detection limit of 0.15 mg L−1. Ultimately, the developed µPAD was applied for the determination of gold in ore samples. The obtained results were in good agreement with those obtained from standard method. The combination of fire assay and µPAD in the determination of gold in geological samples improved the detection limit based on enrichment factor of 75. [ABSTRACT FROM AUTHOR]

[Display omitted] • A distance based paper sensor was developed for detection of Lactate in the blood sample. • Detection was coupled with image analysis to eliminate the visual errors or personal obsessions. • Green synthesized nanoparticles was used as sensing element without needing enzyme for detection of lactate. • The proposed sensor can be used as a reliable device for detecting the lactate concentration of patient blood samples. Rapid detection of lactate as the major fuel source and material to support the level of blood sugar can open up a new class of analysis for nutritionists and sports medicine practitioners. Here, a rapid and user-friendly method for monitoring changes in the blood lactate concentration is reported, involving the use of a paper strip coated with gold nanoparticles (AuNPs). The aqueous extract of Satureja hortensis is used as the reduction agent in a green synthesis of the AuNPs. Due to the interaction between the NPs and lactate flowing across the paper strip, they change color from red to purple, which can be detected by the naked eye. It is possible to create a distance-based paper sensor, representing these changes as a column of colored bars on the paper substrate whose length has a good linear relationship with the lactate concentration ranged between 1.0 and 30.0 mM. By recording the color changes with a scanner, the sensor response is also obtained using an image analysis method, leading to a linear calibration curve in the lactate concentration range of 0.5–30.0 mM. The resulting detection limits of the lactate measurements are found to be 0.6 and 0.47 using the distance measurement and image analysis methods, respectively. Interestingly, in the presence of interfering species, the sensor is selective for lactate, while also showing good performance in measuring the lactate concentration in the real blood samples. [ABSTRACT FROM AUTHOR]

• A simple and affordable protocol to fabricate μPADs was proposed based on the use of a 3D pen. • Hydrophobic barriers were effectively created with an acrylate-based resin. • The barriers revealed good chemical resistance when exposed to organic solvents. • The reported protocol allows the creation of zones with 2 mm diameter and channels with 3 mm width. • Clinical and environmental applications were successfully reported. This paper describes for the first time the use of a 3D pen to fabricate paper-based analytical devices. 3D pens are usually commercialized as "toy for children" and a kit containing four units and a handheld flashlight can be found at cost of US$ 10−15. The protocol involves the 3D pen drawing of the desirable layout on paper using an acrylic resin followed by a curing stage through a handheld flashlight. The barriers created with 3D pen revealed good chemical resistance when exposed to acid and alkaline solutions, surfactants and organic solvents, except ethanol. The proposed approach enabled the creation of zones with 2 mm diameter and channels with 3 mm wide. The analytical feasibility of the devices created with 3D pen was investigated through colorimetric measurements of clinically and environmentally relevant analytes using a free application for image capture and analysis. Considering the instrumental simplicity and the satisfactory analytical performance, we believe the reported approach exhibits potentiality to be implemented in laboratories or research centers with limited resources, opening possibilities to create the desirable devices for the point-of-need applications using only a pen and a flashlight. [ABSTRACT FROM AUTHOR]

• The optical reader was developed for the colorimetric measurement of a wax printed paper-disc platform. • The device was demonstrated by simultaneous determination of glucose and lactate by in situ real-time absorbance measurement. • Analysis results can be delivered with low detection limits, high accuracy, and high specificity within 20 s. • This approach can be widely used for colorimetric quantitation where simultaneous analysis of parallel reactions is required. In this study, we developed a wax printed paper-disc centrifugal optical device platform and simultaneously detected glucose and lactate through real-time absorbance measurements. The disposable paper module was manufactured using a simple wax printing method and was incorporated into reusable discs for colorimetric monitoring. Moreover, the paper-disc's self-calibration capability minimizes the effects of ambient conditions (ambient light, temperature, humidity and measurement time, etc.), enabling quantification with high accuracy and precision. The photodiode (PD) and light-emitting diode (LED) of the developed optical devices were able to monitor the color conversion in multiple reaction zones on a rotating paper-disc in real-time, regardless of ambient light conditions. Quantitative results were available in less than 20 s and did not require any complex image analysis. The detection limits of glucose and lactate were 27.2 μ M and 29.6 μ M, respectively, and simultaneous detection of glucose and lactate was possible even with a small serum volume (1.0 μ L). Thus, the developed wax printed paper-disc centrifugal optical device platform has promising prospects for clinical multianalyte point-of-care testing due to easy manufacturing, cost-effectiveness, user-friendliness, and high sensitivity. [ABSTRACT FROM AUTHOR]

• A novel image processing software was developed that could evaluate the spray coverage rates and droplet counts accurately as compared with DepositScan, ImageJ and SnapCard softwares. • Advanced morphological segmentation techniques used in image processing software caused more accurately performance than the other imaging softwares. • Droplet counts obtained by novel image processing software were higher compared to the other image processing softwares. • Detecting overlapping droplets is an important novelty compared with the other image processing softwares as it provides both better accuracy and more data. The overuse of pesticides is critically important for the environment because of contamination. The correct use of pesticides requires spraying optimization on the intended region. There are a lot of experimental and commercial softwares for determining the spraying parameters by using artificial targets such as water-sensitive papers. A novel image processing software was developed that could evaluate the spray coverage rates and droplet counts quickly and accurately as compared with DepositScan, ImageJ and SnapCard softwares. Water-sensitive papers were used as deposit collectors for providing a quick assessment of spray coverage. Each water-sensitive paper was assessed by comparing the three existing imaging softwares against the novel imaging software developed in Vision Acquisition Software (VAS) by National Instruments. A conveyor belt was set up for carrying the water-sensitive papers. Conveyor belt system was used for four nozzle types (AI11002, CN11002, FF11002, TTJ6011002) and three different belt speeds (4, 5 and 6 km h−1). Scanned and digitized water-sensitive paper images were evaluated with the existing software in order to determine the success of the new software. Results showed that the coverage rate results of developed imaging software had very close proximities, which were between 73.3–97.1%, 70.3–95.3% and 69.4–94.5% at belt speeds of 4, 5 and 6 km·h−1, respectively. Advanced morphological segmentation techniques used in image processing software caused more accurate performance than the other imaging programs. Droplet counts obtained by the novel image processing program were higher compared to the other image processing programs for all nozzle types and at all speeds. Detecting overlapping droplets was also an important novelty compared with the other image processing softwares as it provided both better accuracy and more data. [ABSTRACT FROM AUTHOR]

Abstract: A method is described for the simultaneous calibration of online grammage and moisture measurement by applying machine reel sampling and traceable sample area measurement. The area measurement is based on a flatbed scanner and image analysis. It is demonstrated that a relative uncertainty of 0.5% can be achieved in dry grammage calibration at the 95% confidence level. The determination of grammage and moisture were performed by applying the EN ISO 536 and the EN ISO 287 standards, respectively. The described technique can also be applied with the calibrations performed for the paper industry. [Copyright &y& Elsevier]

The present work reports on the combination of paper-based analytical devices (PADs) and information technology (IT) equipment for non-instrumental determination of boron. PADs prepared with curcumin as a receptor and ethanolic extracts of Curcuma longa L. powder were evaluated for sensing. The colorimetric assay is based on a two step-strategy involving initially the formation of rosocyanin in the PAD under acidic conditions, with subsequent color change (from red to blue-green) at alkaline pH. The color change produced in the PAD is then exploited for determination of boron by digitization and image processing with IT devices (scanner and tablet camera) and an image analysis program, respectively. Under optimal conditions, the proposed assay showed limits of detection in the range 0.2–0.8 mg/L depending on the PADs and IT devices used for colorimetric reaction and digitization, respectively. In addition, the repeatability, expressed as relative standard deviation, was found to be below 5% (5 mg/L, N = 10). PADs prepared with curcumin and ethanolic extracts of Curcuma longa L. powder showed excellent lifetime and successful applicability to the analysis of water samples of different complexity with recoveries in the range 93–105%. Image 1 • PADs and IT equipment enable the colorimetric determination of boron. • Curcuma longa L. is successfully implemented in PADs for analytical purposes. • PADs containing curcumin show excellent lifetime for boron determination. • A wide variety of water samples can be analyzed in a fast and easy way. [ABSTRACT FROM AUTHOR]

Abstract: It is shown that there are some mistakes in the paper “A singular-value decomposition-based image watermarking using genetic algorithm” by Veysel Aslantas in Int. J. Electron. Commun. AEU 2008;62(5):386–94. [Copyright &y& Elsevier]

The high process speed as well as the low stress at which the web is submitted are two good reasons for considering roll coating over other technologies for paper coating such as slot coating or blade coating. However, due to the film splitting some filaments of coating fluid are formed and broken up at the exit of the transfer nip resulting in small droplets ejected to the surroundings. Such phenomenon, known as misting, appears usually at high speed when using low concentrated coating fluids. The runnability of two coating colors has been evaluated by coating bond paper in a pilot roll coater at process speeds similar to those encountered in the paper industry. Misting droplets size and distribution determined by image analysis have been related with the coating transfer efficiency and the extensional viscosity. It was demonstrated that high solids content suspensions having large extensional viscosity produce less misting especially at high speed resulting in higher coating effectiveness. [ABSTRACT FROM AUTHOR]

Polymeric carrier fabrics are commonly used in many industrial processes including manufacture of paper and board. Apart from acting as a carrier for the compressible porous material during the manufacturing process, the synthetic woven fabrics comprising mainly of poly ethylene terypthalate (PET) yarns, impart valuable product attributes, i.e. softness, bulk, absorbency, etc. in consumer products. The three-dimensional structure of the fabrics plays a critical role in deciding the manufacturing and energy efficiency as well as product end-use properties.X-ray micro computed tomography (X-μCT) provides a non-intrusive technique to visualize and analyze the three-dimensional structure of porous materials such as paper [The 3 Dimensional Structure of Paper and Its Relationship to Liquid and Vapor Transport, The Science of Papermaking, p. 1289; Tappi J 84 (2001) 1; APPITA 55 (2002) 230]. In this paper, we use this technique to visualize the three-dimensional structure of polymeric fabrics commonly used in paper manufacture [The 3 Dimensional Structure of Paper and Its Relationship to Liquid and Vapor Transport, The Science of Papermaking, p. 1289; Tappi J. 84 (2001) 1; APPITA 55 (2002) 230]. Digital image analysis techniques based on mathematical morphology and stereology were used to determine traditional pore descriptors such as porosity, yarn–void interfacial area, tortuosity and hydraulic radii distribution in the two principal orthogonal directions [The 3 Dimensional Structure of Paper and Its Relationship to Liquid and Vapor Transport, The Science of Papermaking, p. 1289; APPITA 55 (2002) 230]. Comparison of the average yarn diameter by X-μCT and image analysis and physical measurement using light microscopy agreed to within 3% indicating the good accuracy of the X-ray technique. The differences in fabric pore structural characteristics between the in-plane and transverse directions reported here help explain the differences in liquid and vapor transport in the two principal directions.Lattice-Boltzmann simulations of fluid flow and Monte-Carlo simulations of vapor diffusion through actual 3D structures of fabric provide a direct method to predict the permeability and diffusivity characteristics of these complex media. Comparison of structural characteristics between image analysis and simulations show reasonable agreement. [Copyright &y& Elsevier]

This paper discusses the role of Transfer Learning (TL) and transformers in cancer detection based on image analysis. With the enormous evolution of cancer patients, the identification of cancer cells in a patient's body has emerged as a trend in the field of Artificial Intelligence (AI). This process involves analyzing medical images, such as Computed Tomography (CT) scans and Magnetic Resonance Imaging (MRIs), to identify abnormal growths that may help in cancer detection. Many techniques and methods have been realized to improve the quality and performance of cancer classification and detection, such as TL, which allows the transfer of knowledge from one task to another with the same task or domain. TL englobes many methods, particularly those used in image analysis, such as transformers and Convolutional Neural Network (CNN) models trained on the ImageNet dataset. This paper analyzes and criticizes each method of TL based on image analysis and compares the results of each method, showing that transformers have achieved the best results with an accuracy of 97.41% for colon cancer detection and 94.71% for Histopathological Lung cancer. Future directions for cancer detection based on image analysis are also discussed. [ABSTRACT FROM AUTHOR]

The study of biotic nomenclature has resulted from gene expression profiling using integrated image analysis techniques. The study emphasized in this paper confers Modified Intuitionistic Fuzzy Clustering Method (MIFCM) for spot segmentation of microarray image. In order to achieve the basic condition of intuitionism, a generator using Intuitionistic Fuzzy set (IFS) is used. MIFCM approach considers degree of uncertainty, value of association and value of non-association to determine similarity between the microarray spot data points which further helps in clustering. For non-association value calculation, Sugeno's [47] and Yager's [30] [44] fuzzy complement generator [49] with intuitionism approach is proposed in this work. To achieve elementary level of intuitionism [49] , MIFCM is integrated with Hausdorff distance metrics [43]. The Hausdorff distance metrics is used to quantify the distance metrics betwixt microarray image pixel and cluster centers. The study discusses the constraints of the evolutionary Fuzzy C-Means (FCM) method [4] and adoption of new fuzzy complement generator which overcomes limitations to increase the clustering efficiency. Further, the paper presents detailed methodology of calculating the parameters required to convert crisp spot data of microarray image into fuzzy set which will be input to the next stage of kernel induced clustering using MIFCM technique. [ABSTRACT FROM AUTHOR]

Cancer is a life-threatening ailment characterized by the uncontrolled proliferation of cells. Breast cancer (BC) represents the most highly infiltrative neoplasms and constitutes the primary cause of mortality in the female population due to cancer-related complications. Consequently, the imperative for early detection and prognosis has emerged as a means to enhance long-term survival rates and mitigate mortality. Emerging artificial intelligence (AI) technologies are being utilized to aid radiologists in the analysis of medical images, resulting in enhanced outcomes for individuals diagnosed with cancer. The purpose of this survey is to examine peer-reviewed computer-aided diagnosis (CAD) systems that have been recently developed and utilize machine learning (ML) and deep learning (DL) techniques for the diagnosis of BC. The survey aims to compare these newly developed systems with previously established methods and provide technical details, as well as the advantages and disadvantages associated with each model. In addition, this paper addresses several unresolved matters, areas of research that require further exploration, and potential avenues for future investigation in the realm of advanced computer-aided design (CAD) models utilized in the interpretation of medical images. Furthermore, the integration of Internet of Things (IoT) in BC research and treatment holds immense significance by facilitating real-time monitoring and personalized healthcare solutions. IoT devices, such as wearable sensors and smart implants, enable continuous data collection, empowering healthcare professionals to track patients' vital signs, response to treatment, and overall health trends, fostering more proactive and tailored approaches to BC management. Moreover, the advent of 5G technology in BC applications promises to revolutionize communication speeds and data transfer, enabling rapid and seamless transmission of large medical datasets. This high-speed connectivity enhances the efficiency of remote diagnostics, telemedicine, and collaborative research efforts, ultimately accelerating the pace of innovation and improving patient outcomes in BC care. The present study aims to examine various classifiers utilized in ML and DL methodologies for the purpose of diagnosing BC. Research findings have demonstrated that DL has superior performance compared to standard ML methods in the context of BC diagnosis, particularly when the dataset is extensive. The existing body of research indicates that there are significant gaps in knowledge that need to be addressed in order to enhance healthcare outcomes in the future. These gaps highlight the pressing need for both practical and scientific research in the field. Finally, IoT and 5G will be how they can be used in order to enhance BC detection, treatment and patient care. • Cancer, characterized by uncontrolled cell proliferation, poses a significant threat to human life. • Breast carcinoma is highly invasive and a leading cause of female cancer-related mortality, emphasizing the need for early detection and prognosis. • Emerging AI technologies are assisting radiologists in analyzing medical images, improving cancer diagnosis outcomes. • This survey focuses on recent computer-aided diagnosis (CAD) systems using machine learning and deep learning for breast carcinoma diagnosis. • The paper identifies unresolved research areas and future investigation prospects in advanced CAD models for medical image interpretation. [ABSTRACT FROM AUTHOR]

Cancer is a condition in which abnormal cells uncontrollably split and damage the body tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical images play an indispensable role in detecting various cancers; however, manual interpretation of these images by radiologists is observer-dependent, time-consuming, and tedious. An automatic decision-making process is thus an essential need for cancer detection and diagnosis. This paper presents a comprehensive survey on automated cancer detection in various human body organs, namely, the breast, lung, liver, prostate, brain, skin, and colon, using convolutional neural networks (CNN) and medical imaging techniques. It also includes a brief discussion about deep learning based on state-of-the-art cancer detection methods, their outcomes, and the possible medical imaging data used. Eventually, the description of the dataset used for cancer detection, the limitations of the existing solutions, future trends, and challenges in this domain are discussed. The utmost goal of this paper is to provide a piece of comprehensive and insightful information to researchers who have a keen interest in developing CNN-based models for cancer detection. [ABSTRACT FROM AUTHOR]

A unique crystalline signature not reported previously for atactic poly(methyl methacrylate) PMMA was observed in the X-ray diffraction of single wall carbon nanotubes (SWNT)/PMMA bucky papers indicating ordered PMMA wrapping on SWNT. This ordered PMMA wrapping was not observed in few wall carbon nanotubes (FWNT)/PMMA and multiwall carbon nanotube (MWNT)/PMMA bucky papers. [ABSTRACT FROM AUTHOR]

This paper applies an image analysis technique to quantify the two-phase flow videos after an expansion valve. This method first finds the liquid-vapor interface and then estimates the void fraction and velocity of each phase. This paper also proposes a one-dimensional developing two-phase flow model based on the force-momentum balance. The void fraction of the developing flow predicted by the model shows a similar trend to the quantified experiment data from image analysis: void fraction will decrease and then stabilize as flow develops along the tube. In essence, the change in void fraction and flow velocity is a result of unbalanced force in liquid and vapor phase. This model is also capable of estimating the distance to achieve fully developed flow after an expansion valve. The ability to predict two-phase flow behavior is not only important to the theoretical study of two-phase flow, but also critical to two-phase flow system design to optimize heat transfer and pressure drop. [ABSTRACT FROM AUTHOR]

Accurate cloud and shadow detection is a crucial prerequisite for optical remote sensing image analysis and application. Multi-temporal-based cloud and shadow detection methods are a preferable choice to detect clouds in complex scenes (e.g., thin clouds, broken clouds and clouds with interference from artificial surfaces with high reflectivity). However, such methods commonly require cloud-free reference images, and this may be difficult to achieve in time-series data since clouds are often prevalent and of varying spatial distribution in optical remote sensing images. Furthermore, current multi-temporal-based methods have limited feature extraction capability and rely heavily on prior assumptions. To address these issues, this paper proposes a Siamese network (Siamnet) for cloud and shadow detection based on Time-Series cloudy Images, namely TSI-Siamnet, which consists of two steps: 1) low-rank and sparse component decomposition of time-series cloudy images is conducted to construct a composite reference image to cope with dynamic changes in the cloud distribution in time-series images; 2) an extended Siamnet with optimal difference calculation module (DM) and multi-scale difference features fusion module (MDFM) is constructed to extract reliable disparity features and alleviate semantic information feature dilution during the decoder part. TSI-Siamnet was tested extensively on seven land cover types in the well-known Landsat 8 Biome dataset. Compared to six state-of-the-art methods (including four deep learning-based methods and two classical non-deep learning-based methods), TSI-Siamnet produced the best performance with an overall accuracy of 95.05% and MIoU of 84.37%. In three more challenging experiments, TSI-Siamnet showed enhanced detection of thin and broken clouds and greater anti-interference to highly reflective surfaces. TSI-Siamnet provides a novel strategy to explore comprehensively the valid information in time-series cloudy images and integrate the extracted spectral-spatial–temporal features for reliable cloud and shadow detection. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) has seen a dramatic rise in popularity for remote-sensing image acquisition and analysis in recent years. It has brought promising results in low-altitude monitoring tasks that require detailed visual inspections. Semantic segmentation is one of the hot topics in UAV remote sensing image analysis, as its capability to mine contextual semantic information from UAV images is crucial for achieving a fine-grained understanding of scenes. However, in the remote sensing field, recent reviews have not focused on combining "UAV remote sensing" and "semantic segmentation" to summarize the advanced works and future trends. In this study, we focus primarily on describing various recent semantic segmentation methods applied in UAV remote sensing images and summarizing their advantages and limitations. According to the distinction in modeling contextual semantic information, we have categorized and outlined the methods based on graph-based contextual models and deep-learning-based models. Publicly available UAV-based image datasets are also gathered to encourage systematic research on advanced semantic segmentation methods. We provide quantitative results of representative methods on two high-resolution UAV-based image datasets for fair comparisons and discussions in terms of semantic segmentation accuracy and model inference efficiency. Besides, this paper concludes some remaining challenges and future directions in semantic segmentation for UAV remote sensing images and points out that methods based on deep learning will become the future research trend. • Summarize semantic segmentation methods and datasets for UAV remote sensing images. • Provide fair comparisons of representative methods in accuracy and efficiency. • Identify challenges and future directions for UAV image semantic segmentation. • Semantic segmentation methods based on deep learning will be the mainstream. [ABSTRACT FROM AUTHOR]