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Forensic document examination has been considered one of the most important fields in the forensic science. For this, a quick, effective, and cheap techniques for evaluation of forensic evidence is highly required. This study explores the comparison of A4 document paper by chemical and physical analysis. 16 of white A4 paper from different brands were analyzed by FTIR for investigation of structural characteristics. Video Spectral Comparator 8000 has been used to compare the A4 papers under different light source. The inorganic filler composition in the paper is also explored by ICP‐OES. The calcium carbonate content in document papers play a discriminant role which found to be between 16.02 % and 35.54 %. Also, water contact angle has been utilized in order to examine the surface of paper which is generally related to the inorganic filler and other additives. The WCA results ranged between 83° and 111° that enable quick and easy way to compare A4 document papers. The experimental results have demonstrated that besides FTIR methods, other methods such as ICP‐OES for elemental composition, WCA for wetting test, VSC for visualization under different light of source could have been applied for comparison of document papers in case of criminal cases. [ABSTRACT FROM AUTHOR]

A user-friendly, cost-effectively, portable, and environmentally friendly colorimetric sensor for the quantitative determination of formaldehyde was developed based on the combining of microfluidic paper-based analytical device (μPAD), headspace microextraction (HSME), and digital image colorimetry. Coupling HSME and μPAD led to enhancements in selectivity and sensitivity of the sensor through sample cleanup and analyte enrichment. To construct the μPAD-HSME device, two pieces of paper as the sample and detection zone were placed facing each other so that a small common and sealed space was created between them. The color change occurred when the analyte in the gaseous form crossed this gap and reached the detection zone. Colorimetric sensing in the detection zone was performed based on the Hantzsch reaction. The color change in the detection zone was recorded by a smartphone and digital images were processed using image analysis software based on the RGB model. The influence of some key variables on the sensitivity of the method including derivatization reagent composition, sample volume, extraction temperature, and extraction time was studied and optimized. The linear dynamic range of the method was obtained in two ranges of 0.10–0.75 and 0.75–5.0 mg L−1 with a limit of detection of 0.03 mg L−1. The recoveries were in the range 80–126% for the quantification of formaldehyde in textile, milk, and wastewater samples. [ABSTRACT FROM AUTHOR]

We have achieved a successful synthesis of a label-free, flexible, portable, and colour-indicating biosensor using cholesteric nanostructure liquid crystals (LCs), commonly referred to as cholesteric LCs (CLCs), on paper fibres. This innovative approach holds significant promise for rapid screening in precision medicine and other applications. We incorporated optically active nematic LCs in various configurations within CLCs, allowing them to rotate along different axes. When exposed to light, these LCs reflected light at specific wavelengths. By employing polarised optical microscopy and a charged couple device (CCD), we conducted titration experiments with bovine serum albumin (BSA) on the paper substrate and quantified protein concentrations based on the observed colour shifts. Utilising internal Python pixel analysis software, we evaluated the red, green, and blue colour components, which served as biomarkers for different BSA concentrations. Our results demonstrated a linear correlation between BSA concentration and colour variations. This CLC-based paper-substrate biosensor exhibits the potential to efficiently screen a large number of samples, thereby enhancing the diagnostic accuracy in clinical settings. Combining the colour-indicating and quantifiable attributes of CLCs with the affordability and portability of paper substrates, we have developed a versatile biosensor. Its ease of use, rapid response, and high sensitivity make it a promising tool for future disease detection endeavours. [ABSTRACT FROM AUTHOR]

Flow and spontaneous imbibition phenomena in porous media are important for various industrial applications, including printing and medical lateral flow assays. Their quantitative characterization is important to better understand and select the appropriate raw materials. However, standard methods often require time-consuming tests, and/or expensive equipment. Different time scales must be considered, limiting the range of possible characterization tools. A novel experimental approach based on image analysis for characterizing spontaneous imbibition processes is presented. Hence, ultra-fast diffusion may be quantitatively characterized. Models are issued from the literature to consider physical phenomena at small (milliseconds) and medium range (seconds) of time scales. The obtained experimental data fit with theoretical results, providing valuable insights into the understanding of fluid flow behavior at different time scales. Furthermore, the identification of some physical properties for either the fluid, or the substrate, based on the theoretical models are possible, as the contact angle, which remains to be otherwise challenging. This study contributes to bridging the gap between spontaneous imbibition and capillary phenomena at different time scales, their modeling, and a characterization of material and/or fluid properties paving the way for enhanced understanding and control of fluid behavior in porous media. Different papers are considered to illustrate the method. [ABSTRACT FROM AUTHOR]

This study proposes a method to determine the two‐dimensional absorption capacity of paper towels. Individual plies were tested to minimize the effects of transverse wicking on wetting. The method involves arbitrary point source injection of liquid into the towel surface while recording microscopic images of the wetted areas. The samples were selected from the main manufacturing processes: conventional wet pressing and through‐air drying. Wetting graphs that illustrate the dynamic and static wetting behaviors were generated. The driving force was found to have a negligible effect on the maximum wetted area. The maximum wetted area and the paper grammage were used to determine the two‐dimensional absorption capacity. The results were validated by the basket‐immersion test method. [ABSTRACT FROM AUTHOR]

Medieval paper, a handmade product, is made with a mould which leaves an indelible imprint on the sheet of paper. This imprint includes chain lines, laid lines and watermarks which are often visible on the sheet. Extracting these features allows the identification of the paper stock and gives information about the chronology, localisation and movement of manuscripts and people. Most computational work for feature extraction of paper analysis has so far focused on radiography or transmitted light images. While these imaging methods provide clear visualisation of the features of interest, they are expensive and time consuming in their acquisition and not feasible for smaller institutions. However, reflected light images of medieval paper manuscripts are abundant and possibly cheaper in their acquisition. In this paper, we propose algorithms to detect and extract the laid and chain lines from reflected light images. We tackle the main drawback of reflected light images, that is, the low contrast attenuation of chain and laid lines and intensity jumps due to noise and degradation, by employing the spectral total variation decomposition and develop methods for subsequent chain and laid line extraction. Our results clearly demonstrate the feasibility of using reflected light images in paper analysis. This work enables feature extraction for paper manuscripts that have otherwise not been analysed due to a lack of appropriate images. We also open the door for paper stock identification at scale. [ABSTRACT FROM AUTHOR]

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]

A turn-on fluorescent aptasensor based on a paper-based microfluidic chip was developed to detect arsenite via aptamer competition strategy and smartphone imaging. The chip was prepared by wax-printing hydrophilic channels on filter paper. It is portable, low-cost, and environmentally friendly. Double-stranded DNA consisting of aptamer and fluorescence-labeled complementary strands was immobilized on the reaction zone of the paper chip. Due to the specific strong binding between aptamer and arsenite, the fluorescent complementary strand was squeezed out and driven by capillary force to the detection area of the paper chip, so that the fluorescent signal arose in the detection area under the excitation wavelength of 488 nm. Arsenite can be quantified by using smartphone imaging and RGB image analysis. Under the optimal conditions, the paper-based microfluidic aptasensor exhibited excellent linear response over a wide range of 1 to 1000 nM, with a detection limit as low as 0.96 nM (3σ). [ABSTRACT FROM AUTHOR]

Especially in the field of paper and print post-processing on an industrial scale, continuous cutting operations generate paper dust. Despite preventive measures like dedusting units, a high paper web velocity induces the release of particulate dust. As a result, the particles settle and accumulate on machine components and in the surrounding area. Resuspended particles around a potential ignition source represent a fire hazard. The prevention of such fire incidents requires frequent servicing and maintenance. However, the shutdown time on industrial scale applications remains cost-intensive. In this research, a cutting plotter executes reproducible knife edge cutting sequences to identify significant parameters affecting the paper dust formation on a macro and micro scale. For this purpose, an extraction system collects the exposed particles along the cutting line. The applied methods include gravimetric determination of the dust mass and dynamic image analysis to characterise particle size and shape. Final results indicate a significant influence of the blade wear condition. [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]

Medical imaging refers to the process of obtaining images of internal organs for therapeutic purposes such as discovering or studying diseases. The primary objective of medical image analysis is to improve the efficacy of clinical research and treatment options. Deep learning has revamped medical image analysis, yielding excellent results in image processing tasks such as registration, segmentation, feature extraction, and classification. The prime motivations for this are the availability of computational resources and the resurgence of deep convolutional neural networks. Deep learning techniques are good at observing hidden patterns in images and supporting clinicians in achieving diagnostic perfection. It has proven to be the most effective method for organ segmentation, cancer detection, disease categorization, and computer-assisted diagnosis. Many deep learning approaches have been published to analyze medical images for various diagnostic purposes. In this paper, we review the work exploiting current state-of-the-art deep learning approaches in medical image processing. We begin the survey by providing a synopsis of research works in medical imaging based on convolutional neural networks. Second, we discuss popular pretrained models and general adversarial networks that aid in improving convolutional networks' performance. Finally, to ease direct evaluation, we compile the performance metrics of deep learning models focusing on COVID-19 detection and child bone age prediction. [ABSTRACT FROM AUTHOR]

During the storage of celluloid pictures for animation films over half a century, an interleave paper adhered to acrylic paint. The purpose of this study is to establish a methodology to cleanly remove the paper from the paint. A layered film, a replica of the celluloid pictures, adhered with paper was prepared and immersed in water or ethanol. The effect of these solvents on the peeling behavior was investigated using a peel test. The maximum peel force for the dry layered film in was distributed at ~0.5 N, independently of the peel speed. The peel force was significantly reduced after the layered film was immersed in pure water or ethanol. A morphological observation revealed that the dry paper was peeled off via the cohesive failure of the paper. After the layered film was immersed in pure water, the paper was also peeled off via cohesive failure. The layered film immersed in ethanol was peeled off at the paper/paint interface. To clear the effect of the volume change in the paint on peel behavior, the relative volume was determined via image analysis. The relative volume of paint was 1.56 in pure water and 1.37 in ethanol. It can be considered that the large difference in the volume of paint induces a large shear stress at the paint/paper interface. [ABSTRACT FROM AUTHOR]

We propose a printed 384‐well microtiter paper‐based fluorescent chemosensor array device (384‐well microtiter PCAD) to simultaneously categorize and discriminate saccharides and sulfur‐containing amino acids for food analysis. The 384‐well microtiter PCAD requiring 1 μL/4 mm2 of each well can allow high‐throughput sensing. The device embedded with self‐assembled fluorescence chemosensors displayed a fingerprint‐like response pattern for targets, the image of which was rapidly captured by a portable digital camera. Indeed, the paper‐based chemosensor array system combined with imaging analysis and pattern recognition techniques not only successfully categorized saccharides and sulfur‐containing amino acids but also classified mono‐ and disaccharide groups. Furthermore, the quantitative detectability of the printed device was revealed by a spike and recovery test for fructose and glutathione in a diluted freshly made tomato juice. We believe that the 384‐well microtiter PCAD using the imaging analysis system will be a powerful sensor for multi‐analytes at several categorized groups in real samples. [ABSTRACT FROM AUTHOR]

Machine learning has been leveraged for image analysis applications throughout a multitude of subspecialties. This position paper provides a perspective on the evolutionary trajectory of practical deep learning tools for genitourinary pathology through evaluating the most recent iterations of such algorithmic devices. Deep learning tools for genitourinary pathology demonstrate potential to enhance prognostic and predictive capacity for tumor assessment including grading, staging, and subtype identification, yet limitations in data availability, regulation, and standardization have stymied their implementation. [ABSTRACT FROM AUTHOR]

We believe the switch to a digital pathology (DP) workflow is imminent and it is essential to understand the economic implications of conversion. Many aspects of the adoption of DP will be disruptive and have a direct financial impact, both in short term costs, such as investment in equipment and personnel, and long term revenue potential, such as improved productivity and novel tests. The focus of this whitepaper is to educate pathologists, laboratorians and other stakeholders about the business and monetary considerations of converting to a digital pathology workflow. The components of a DP business plan will be thoroughly summarized, and guidance will be provided on how to build a case for adoption and implementation as well as a roadmap for transitioning from an analog to a digital pathology workflow in various laboratory settings. It is important to clarify that this publication is not intended to list prices although some financials will be mentioned as examples. The authors encourage readers who are evaluating conversion to a DP workflow to use this paper as a foundational guide for conducting a thorough and complete assessment while incorporating in current market pricing. Contributors to this paper analyzed peer-reviewed literature and data collected from various institutions, some of which are mentioned. Digital pathology will change the way we practice through facilitating patient access to expert pathology services and enabling image analysis tools and assays to aid in diagnosis, prognosis, risk stratification and therapeutic selection. Together, they will result in the delivery of valuable information from which to make better decisions and improve the health of patients. [ABSTRACT FROM AUTHOR]

The purpose of this study was to evaluate a simple and low-cost colorimetric method based on Fe(III) chloride and potassium hexacyanoferrate(III) for determination of acetaminophen, ascorbic acid and phenylephrine, which can be used in small laboratories using restricted materials and resources. A paper based sensor using the reagent was introduced. Significance of different variables in determination of drugs were studied by Placket-Burman design and optimal values for concentration of hydrochloric acid, Fe(III) chloride and potassium hexacyano ferrate(III), 0.01 M, 0.004 M and 0.004 M, respectively were obtained. Without using any sophisticated instrument and only by image analysis the concentration of acetaminophen, ascorbic acid and phenylephrine was determined in pharmaceutical samples. In this way we were able to determine by analyzing the final color of the reactions. The linear range in ppm for all the analytes was obtained as 0.00–50.00 and limit of detection of 2.52, 2.48 and 2.48 were obtained for acetaminophen, ascorbic acid and phenylephrine, respectively. Percent relative standard deviation (RSD %) and percent relative error (RE %) of the proposed method for analysis of real samples of acetaminophen tablet were 4.77 and 7.64, ascorbic acid tablet, 4.73 and 1.41, and phenylephrine syrup, 2.44 and − 1.61, respectively. [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]

The article presents a new technique for measuring paper deformation in unidirectional tensile tests, based on recording and analysis of a series of specimen images. The proposed technique differs from the DIC-based deformation measurement in that the cross-correlation of image data has been replaced with linear filtering. For this purpose, a regular grid of markers is printed on the sample. Filtering the image creates local maxima in the places where markers occur. The developed algorithm finds their location with sub-pixel accuracy. Printing a grid of markers on tested paper and use of reference objects visible in the same image as the paper sample, freed from the need to mechanically connect the camera and the universal testing machine and from the necessity to electronically synchronize their work. The obtained deformation distributions and Poisson's ratios are in accordance with the literature data which confirms the correctness of the developed measurement technique. [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]

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]

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]

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]

Within a few decades of development, Internet is been refreshing the world's awareness of its development and potentials at an unexpected speed. In recent years, virtual reality technology has begun to be applied to more and more fields. Especially in instant transmission of information, the applications of VR are incomparable. Akin to the wide-ranged advantages of the technology in education and health, the applications of VR in the art of artistic image designing need to be addressed. With this research work, a comprehensive study is presented about the applications of virtual reality in the art of image visualization. The research intends to analyze the possibility of intermingling modern image visualization with the emerging VR technology. Following a systematic approach, the history and development of display design are reviewed besides studying the artistry techniques used in the technology of art image visualization design. The interdisciplinary association of the two fields is explored with the help of relevant algorithms. The model proposed in the paper for the design of art image is based on the visual interactive process, rigorous assembly sequence, and appropriate equipment mode. As a result, the whole design process is more controllable and feasible. The suggested design concept is verified dynamically. Through the collection and comparison of feedback information, the hypothesis algorithm of the model is updated to accommodate the dynamic information so that to reflect the complete image design process. To assess performance of the model, evaluation was conducted from various perspectives. The three basic image operations such as illumination change, occlusion change, and color change were performed by using the two technologies such as the traditional image design and VR-based image design. From the comparison of experimental data, it was revealed that the effects of traditional art image visualization products produced by the art image visualization and that of VR technology are quite different. For instance, the visualization score achieved for the lighting change operation using the VR technology was 95.48%, whereas 85.57% was obtained for the same operation using the traditional image design technology. Similarly, while adding visual effects using the VR technology, an average of 9% higher score was obtained for the said image operations. The promising results attained for the VR-based design testify that the technology is feasible and suitable to be intermingled with the visual design of art image. As a whole, the findings justify that the proposed approach is quite applicable in visual design of art image systems. In view of the significance of the research, the study can be extended to related domains of computer-based designing and visualization as well. [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]

A novel method combining headspace single-drop microextraction with a paper-based colorimetric assay was developed. Headspace single-drop microextraction using a microdrop containing unmodified gold nanoparticles (AuNPs) as both the extractant and the colorimetric probe was used for the sensitive and selective determination of Se(IV). The method relies on the color change of the microdrop solution caused by the adsorption of in situ-generated hydrogen selenide on the surface of AuNPs. Following extraction, the microdrop was spotted onto cellulose paper, and scanometric-assisted digital image analysis was used for selenium quantification. The analytical variables affecting the method sensitivity, including the drop volume, the concentrations of KBH4, HCl, and AuNP solutions, and the extraction time, were studied. Under the optimal conditions, a linear correlation between the colorimetric signal and Se(IV) concentration in the range from 15–100 μg L−1 with a limit of quantification of 12 μg L−1 was achieved. The repeatability of the method was studied by the calculation of intraday and interday precision for the standard solutions at concentrations of 20 and 70 μg L-1. The batch-to-batch reproducibility of the AuNPs synthesized under the same conditions was also assessed. The relative standard deviations were less than 7%. The method provided satisfactory results for the determination of selenium in real samples. [ABSTRACT FROM AUTHOR]

Development of paper-based microfluidic devices that perform colorimetric measurements requires quantitative image analysis. Because the design geometries of paper-based microfluidic devices are not standardized, conventional methods for performing batch measurements of regularly spaced areas of signal intensity, such as those for well plates, cannot be used to quantify signal from most of these devices. To streamline the device development process, we have developed an open-source program called ColorScan that can automatically recognize and measure signal-containing zones from images of devices, regardless of output zone geometry or spatial arrangement. This program, which measures color intensity with the same accuracy as standard manual approaches, can rapidly process scanned device images, simultaneously measure identified output zones, and effectively manage measurement results to eliminate requirements for time-consuming and user-dependent image processing procedures. [ABSTRACT FROM AUTHOR]

The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed. [ABSTRACT FROM AUTHOR]

We have developed a new method for characterizing paper coating structure using FIB milling technique and FE-SEM. A new image analysis method combining smart blur and locally adaptive thresholding technique was applied. Compared to conventional method, this method preserved the edge of target and gave better automatic image segmentation of pores. We applied this method for the measurement of the pore structure in pigment coating layers. Staining with OsO4and resin-embedding treatments were used for the sample preparation of coated papers for image analysis. A control sample without any treatment was also used in analysis. BSE images of osmium stained and resin-embedded coated paper gave the clearest image segmentation of coating components. The results showed that three sample preparation methods gave similar z-directional porosities. Lower porosity and smaller pore size was obtained from the top surface layer with the osmium stained and resin embedded samples. [ABSTRACT FROM AUTHOR]

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]

Purpose: Historical newspaper collections provide a wealth of information about the past. Although the digitization of these collections significantly improves their accessibility, a large portion of digitized historical newspaper collections, such as those of KBR, the Royal Library of Belgium, are not yet searchable at article-level. However, recent developments in AI-based research methods, such as document layout analysis, have the potential for further enriching the metadata to improve the searchability of these historical newspaper collections. This paper aims to discuss the aforementioned issue. Design/methodology/approach: In this paper, the authors explore how existing computer vision and machine learning approaches can be used to improve access to digitized historical newspapers. To do this, the authors propose a workflow, using computer vision and machine learning approaches to (1) provide article-level access to digitized historical newspaper collections using document layout analysis, (2) extract specific types of articles (e.g. feuilletons – literary supplements from Le Peuple from 1938), (3) conduct image similarity analysis using (un)supervised classification methods and (4) perform named entity recognition (NER) to link the extracted information to open data. Findings: The results show that the proposed workflow improves the accessibility and searchability of digitized historical newspapers, and also contributes to the building of corpora for digital humanities research. The AI-based methods enable automatic extraction of feuilletons, clustering of similar images and dynamic linking of related articles. Originality/value: The proposed workflow enables automatic extraction of articles, including detection of a specific type of article, such as a feuilleton or literary supplement. This is particularly valuable for humanities researchers as it improves the searchability of these collections and enables corpora to be built around specific themes. Article-level access to, and improved searchability of, KBR's digitized newspapers are demonstrated through the online tool (https://tw06v072.ugent.be/kbr/). [ABSTRACT FROM AUTHOR]

Metallographic image analysis is vital in the field of metal science due to its potential to automate the sensing process for grain and particle size estimation. To ensure the good quality and reliability of metal products, analysis of the integrity of metallic components is required. In contemporary manufacturing processes, microscopic analysis is a crucial step, mainly when complex systems like gearboxes, turbines, or engines are assembled using various components from multiple suppliers. A final product's quality, durability, and lifespan are determined via the quality analysis of properties of a material with proper tolerances. A flaw in a single component can cause the breakdown of the entire finished product. To ensure the good quality of a material, micro-structural analysis is necessary, which includes the routine measurement of inclusions. The particle and grain sizes of particulate samples are the most crucial physical characteristics of metals. Their measurement is routinely conducted across various industries, and they are frequently considered essential parameters in the creation of many products. This paper discusses the role of sensors in enhancing the accuracy and efficiency of metallographic image analysis, as well as the challenges and limitations associated with this technology. The paper also highlights the potential applications of sensor-assisted metallographic image analysis in various industries, such as aerospace, automotive, and construction. The paper concludes by identifying future research directions for this emerging field, including the development of more sophisticated algorithms for grain and particle size estimation, the integration of multiple sensors for more accurate measurements, and the exploration of new sensing modalities for metallographic image analysis. [ABSTRACT FROM AUTHOR]

With the advent of several tools and web engines trained for finding journal articles out of billions of research papers on millions of topics in different databases with a high degree of generalizability, it often leads to a loss of specificity. Scientific pursuits need a tool to extract data from selected resources for performing domain-specific tasks. Current algorithms and generalized tools lack specificity and are challenged by errors in analysing data from a bundle of specific documents selected eclectically. Current work addresses the need for such a tool, which focuses on specificity based on users' input keywords and phrases to find relevant information from bundles of articles from the web. Reseractor is based on a customized algorithm, Whitespace, in synergy with output from open-access tools for document image analysis and focused domain data extraction using NLP. The current tool is designed for the material science domain with the features of adopting various generalized and scientific corpora as layers. It is tested on two sets of different bundles of papers and gives an accuracy of 81.12% along with a recall of 78.38% and a precision of 84.06%. Owing to the simple and direct applicability of algorithms, users from other domains can directly use their corpora in algorithms and remodel the tool for their purpose. Current work fulfills the need for domain-specific experimental data extraction stored in organized and structured databases for upcoming computational researchers. [ABSTRACT FROM AUTHOR]

Cables are vital load-bearing components of cable-stayed bridges. Surface defects can lead to internal corrosion and fracturing, significantly impacting the stability of the bridge structure. The detection of surface defects from bridge cable images faces numerous challenges, including shadow disturbances due to uneven lighting and difficulties in addressing multiscale defect features. To address these challenges, this paper proposes a novel and cost-effective deep learning segmentation network, named Trans-DCN, to detect defects in the surface of the bridge cable. The network leverages an efficient Transformer-based encoder and integrates multiscale features to overcome the limitations associated with local feature inadequacy. The decoder implements an atrous Deformable Convolution (DCN) pyramid and dynamically fuses low-level feature information to perceive the complex distribution of defects. The effectiveness of Trans-DCN is evaluated by comparing it with state-of-the-art segmentation baseline models using a dataset comprising cable bridge defect images. Experimental results demonstrate that our network outperforms the state-of-the-art network SegFormer, achieving a 27.1% reduction in GFLOPs, a 1.2% increase in mean Intersection over Union, and a 1.5% increase in the F1 score. Ablation experiments confirmed the effectiveness of each module within our network, further substantiating the significant validity and advantages of Trans-DCN in the task of bridge cable defect segmentation. The network proposed in this paper provides an effective solution for downstream cable bridge image analysis. [ABSTRACT FROM AUTHOR]

Supervised learning has been the cornerstone of many successful medical imaging applications. However, its reliance on large labeled datasets poses significant challenges, especially in the medical domain, where data annotation is time-consuming and expensive. In response, self-supervised learning (SSL) has emerged as a promising alternative, leveraging unlabeled data to learn meaningful representations without explicit supervision. This paper provides a detailed overview of supervised learning and its limitations in medical imaging, underscoring the need for more efficient and scalable approaches. The study emphasizes the importance of the area under the curve (AUC) as a key evaluation metric in assessing SSL performance. The AUC offers a comprehensive measure of model performance across different operating points, which is crucial in medical applications, where false positives and negatives have significant consequences. Evaluating SSL methods based on the AUC allows for robust comparisons and ensures that models generalize well to real-world scenarios. This paper reviews recent advances in SSL for medical imaging, demonstrating their potential to revolutionize the field by mitigating challenges associated with supervised learning. Key results show that SSL techniques, by leveraging unlabeled data and optimizing performance metrics like the AUC, can significantly improve the diagnostic accuracy, scalability, and efficiency in medical image analysis. The findings highlight SSL's capability to reduce the dependency on labeled datasets and present a path forward for more scalable and effective medical imaging solutions. [ABSTRACT FROM AUTHOR]

Video processing is the most emergent area of image processing in Research and Development. This paper, we present some advanced technology interrelated to video and image processing, which will provide a super-resolution high-quality most prominent visible light video for better human visualization and background motions or gesticulations of the human brain. There are two approaches for increasing the current resolution level of an image. The first one is the improvement of spatial resolution by reducing the size of pixels through the techniques of sensor manufacturing by about 40 $ {\mathcal{M}}{\textrm{m}^2} $ M m 2 for a 0.35 $ {\mathcal{M}}\textrm{m} $ M m CMOS process and the second approach is the enhancement of chip size that also enhances the capacitance. In video processing, we mainly focus on object images, i.e. any form of signal processing in which the input is an image and the output is a photograph or a frame of video. So, it will be better to converge over techniques of digital image processing. In the proposed algorithm (MHI Simulink model), edge extraction is performed to find the precious area of MRI and CT-Scan images. Using FPGA, edge detection methods have been implemented over scanned images to get better accuracy. The accuracy of the proposed method has been compared with Prewitt and Sobel's edge detection techniques. The proposed method has given better accuracy than Prewitt and Sobel methods. Finally, this paper shows future directions for researchers to enhance the characteristics of digital image and video processing. [ABSTRACT FROM AUTHOR]

The deep sea has abundant resources and is regarded as the "sixth continent" that humans can use. Although research on the deep sea has made some progress, its exploration is not deep enough. The acquisition and analysis of deep-sea images can provide important technical means for deep-sea exploration and the acquisition of information. However, there is currently no complete underwater image dataset. For this reason, this paper is the first deep-sea visual dataset of the South China Sea, contains over 100 TB videos and 1 million high quality images. This paper also applies the dataset to underwater image enhancement and image superresolution, and the experiment proves the effectiveness of the dataset. [ABSTRACT FROM AUTHOR]

In insecure communication environments where the communication bandwidth is limited, important image data must be compressed and encrypted for transmission. However, existing image compression and encryption algorithms suffer from poor image reconstruction quality and insufficient image encryption security. To address these problems, this paper proposes an image-compression and encryption scheme based on a newly designed hyperchaotic system and two-dimensional compressed sensing (2DCS) technique. In this paper, the chaotic performance of this hyperchaotic system is verified by bifurcation diagrams, Lyapunov diagrams, approximate entropy, and permutation entropy, which have certain advantages over the traditional 2D chaotic system. The new 2D chaotic system as a pseudo-random number generator can completely pass all the test items of NIST. Meanwhile, this paper improves on the existing 2D projected gradient (2DPG) algorithm, which improves the quality of image compression and reconstruction, and can effectively reduce the transmission pressure of image data confidential communication. In addition, a new image encryption algorithm is designed for the new 2D chaotic system, and the security of the algorithm is verified by experiments such as key space size analysis and encrypted image information entropy. [ABSTRACT FROM AUTHOR]

This paper aims to provide a review of the basis for application of AI in radiology, to discuss the immediate ethical and professional impact in radiology, and to consider possible future evolution. Even if AI does add significant value to image interpretation, there are implications outside the traditional radiology activities of lesion detection and characterisation. In radiomics, AI can foster the analysis of the features and help in the correlation with other omics data. Imaging biobanks would become a necessary infrastructure to organise and share the image data from which AI models can be trained. AI can be used as an optimising tool to assist the technologist and radiologist in choosing a personalised patient's protocol, tracking the patient's dose parameters, providing an estimate of the radiation risks. AI can also aid the reporting workflow and help the linking between words, images, and quantitative data. Finally, AI coupled with CDS can improve the decision process and thereby optimise clinical and radiological workflow. [ABSTRACT FROM AUTHOR]

This paper aims to provide a review of the basis for application of AI in radiology, to discuss the immediate ethical and professional impact in radiology, and to consider possible future evolution. Even if AI does add significant value to image interpretation, there are implications outside the traditional radiology activities of lesion detection and characterisation. In radiomics, AI can foster the analysis of the features and help in the correlation with other omics data. Imaging biobanks would become a necessary infrastructure to organise and share the image data from which AI models can be trained. AI can be used as an optimising tool to assist the technologist and radiologist in choosing a personalised patient's protocol, tracking the patient's dose parameters, providing an estimate of the radiation risks. AI can also aid the reporting workflow and help the linking between words, images, and quantitative data. Finally, AI coupled with CDS can improve the decision process and thereby optimise clinical and radiological workflow. [ABSTRACT FROM AUTHOR]

Plant root system architecture (RSA) has an important role in crop production, particularly for water and nutrient uptake under limiting conditions. In the last few years, several root phenotyping methods have been developed. Here we present a new technique which has been developed for non-destructive, inexpensive and high-throughput root growth studies and RSA analyses. To illustrate the potential applications, this method was tested in an experiment with nitrogen and phosphorous deficiencies in a nutrient solution, affecting RSA parameters of two spring barley varieties (Bojos and Barke). This technique is based on root growth on vertically positioned black filter paper (30 × 60 cm) placed between two black plastic (PVC-P) foils and micro-irrigation systems providing the recirculation of nutrient solution. The pre-germinated seeds were placed in the slit between two plastic bars which carry the filter paper and plastic sheets and fix the plant in the vertical position. This system allows easy repeated non-invasive access to roots for their measuring and sampling. Eighteen days after transplanting the root imaging was done using an RGB digital camera. To evaluate the root architecture parameters the "SmartRoot" software was used. The results revealed that the system is able to detect changes in RSA which are caused mainly by P deficiency (particularly changes in lateral root length and total root area). It can be concluded that this technique has a great potential for non-destructive root growth studies, RSA measurement and root sampling. [ABSTRACT FROM AUTHOR]

The formation index of filter paper is one of the most important characteristics used in industrial quality control. Its estimation is often based on subjective comparison chart rating or, more objective, on the power spectrum of the paper structure observed on a transmission light table. It is shown that paper formation can be modeled by means of Gaussian random fields with a well-defined class of correlation functions, and a formation index which is derived from the density of the Bartlett spectrum estimated from image data: the mean of the Bessel transform of the correlation function taken for wave lengths between 2 and 5mm. Furthermore, it is shown that a considerable variation of the local grammage can be observed also in cases where the the fibers are uniformly and independently scattered in the paper sheet. [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]

To attain an improved knowledge about ink–paper coating adhesion during offset printing, we have developed a laboratory procedure to measure adhesion failure between ink and coated paper during ink setting. This paper describes the technique and a special case where two ground calcium carbonate (GCC)-based coatings have been printed, one normal coating containing the delivered amount of dispersing agent already present in a typical GCC slurry and another coating made from the same GCC slurry but with excess additional free dispersant in the form of sodium polyacrylate. The areas where the ink–paper coating adhesion had failed at the pull-off points after tack testing were characterized by determining white spots in the retained print using image analysis. The white spots represent areas where ink has detached from the coating after contact with a rubber coated cylinder. This area is referred to as ink–paper coating adhesion failure area (IPCAFA). A minimum in IPCAFA at the point of maximum in tack force was found for both coatings where the print was applied onto dry coating. When the coatings, however, were pre-damped, IPCAFA increased on the normal coating over a short time period, independent of the dampening level. For the coating with excess dispersant, on the other hand, the higher dampening level strongly increased the IPCAFA. The strong impact of excess dispersing agent in this work may be explained by a number of related effects, including increased polarity of the coating surface, an associated moisture layer and an effective reduction of fine pores due to water-swelling polyacrylate that blocks these pores. [ABSTRACT FROM AUTHOR]

Environmental monitoring and biomedical diagnostics have attracted a lot of interest in the research community in recent years. Efforts are being made to develop technologies for sensors and diagnostic kits that provide a rapid and on-the-spot response. Microfluidics based lab-on-a-chip systems offer a promising solution in this direction. In the present study, we employ a simple method to fabricate labon- a-chip device or platform using commonly available materials, including cellulose paper and wax. Hydrophilic wells surrounded by hydrophobic boundaries are created by wax impregnation through the paper on heat treatment. We further demonstrate the application of these devices in the detection of iron contamination in water using colourimetric chemical reactions. Our results show that these devices can be used for obtaining qualitative as well as quantitative outcomes. We make use of image analysis tools to quantify the concentration of iron in the samples. The platform offers an affordable, accessible and versatile option for sensing applications in resource-limited settings. [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]

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]

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]