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The value of three-dimensional virtual objects are proven in a great variety of applications; their flexibility allowing for a substantial amount of utilization purposes. In cultural heritage this has been used for many years already, and the amount of users continue to grow as acquisition methods and implementations are becoming more approachable. Nonetheless, there are still many apparent issues with making use of all the possible benefits of 3D data in the field, varying from lack of knowledge, infrastructure, or coherent workflows. This review aims to underline the current limitations in implementing 3D workflows for various cultural heritage purposes. 45 projects and institutions are reviewed, along with the most prominent guidelines for workflows and ways of implementing the 3D data on the web. We also cover how each project manage and make their data accessible to the public. Prominent and recurring issues with standardization, interoperability, and implementation is highlighted and scrutinized. The review is concluded with a discussion on the current utilization's of 3D data for cultural heritage purposes, along with suggestions for future developments. [ABSTRACT FROM AUTHOR]

The powdered form of various food products, including dairy-based and sugar-rich, is popular in the market due to their ease of processing and instant application. Spray drying is one of the most popular processing techniques to make food powders. The spray-drying process parameters, especially the drying temperatures and feed rate, have a significant influence on the quality attributes (such as color, moisture content, drying yield, wettability, water activity, proximate composition, and nutrient contents) of different food products. Recent studies revealed that at very high inlet/outlet air temperatures, the properties of the powdered products are adversely affected. Furthermore, sticking is a major problem during the spray-drying process. Keeping all these issues, this review focuses on providing insights on the effects of spray-drying process conditions and optimization of these conditions to overcome the problems associated with the process and ultimately obtain the best quality product with longer storage life. [ABSTRACT FROM AUTHOR]

The main objective of this work was to optimize the spray drying of coconut milk using response surface methodology (RSM). Maltodextrin was added to the feed coconut milk as the carrier agent in the laboratory scale experiments and the same were designed using Box-Behnken design approach. The effect of the chosen input variables on the responses namely product yield, moisture content, hygroscopicity, and angle of repose of the powders were evaluated using 3D surface plots. Among the chosen input variables of the process, the temperature of the inlet air in the spray drying chamber was found to significantly affect the characteristics of the powder. The flowability properties of the synthesized powders were experimentally obtained and the values were found to be satisfactory. The functional and morphological properties, and color of the powder produced at the optimal condition were compared to those of a commercially available coconut milk powder. For the synthesized powder of the optimal condition, an enhancement of 30oC for the glass transition temperature was seen over to that of the commercial powder. [ABSTRACT FROM AUTHOR]

Documentation and analysis of crime scene evidences are of great importance in any forensic investigation. In this paper, we present the potential of hyperspectral imaging (HSI) to detect and analyze the beverage stains on a paper towel. To detect the presence and predict the age of the commonly used drinks in a crime scene, we leveraged the additional information present in the HSI data. We used 12 different beverages and four types of paper hand towel to create the sample stains in the current study. A support vector machine (SVM) is used to achieve the classification, and a convolutional auto-encoder is used to achieve HSI data dimensionality reduction, which helps in easy perception, process, and visualization of the data. The SVM classification model was re-established for a lighter and quicker classification model on the basis of the reduced dimension. We employed volume-gradient-based band selection for the identification of relevant spectral bands in the HSI data. Spectral data recorded at different time intervals up to 72 h is analyzed to trace the spectral changes. The results show the efficacy of the HSI techniques for rapid, non-contact, and non-invasive analysis of beverage stains. [ABSTRACT FROM AUTHOR]

Plant diseases significantly impact agricultural productivity. Early disease identification and diagnosis are critical for plant protection. Recent deep learning approaches have substantially aided detection of plant diseases. However, existing plant leaf disease identification techniques do not provide sufficient disease detection accuracies when the input image resolution is low. Images of grape leaves taken in the field may be low-resolution (LR) in nature due to limited lighting and varying weather conditions. Such LR images may result in incorrect real-time disease diagnosis. Hence super-resolution is a way to solve this problem. This research work proposes a novel Residual Skip Network-based Super-Resolution for Leaf Disease Detection (RSNSR-LDD) in the Grape plant. The input LR image is separated into two subcomponents using the guided filtering technique. Features from the two subcomponents are extracted using single convolutional layer and four layers of the two-channel residual skip network. Concatenation is used to combine the features of two channels. Following this, a decoding block and a convolutional layer are utilized to generate the super-resolution (SR) image. A new collaborative loss function is proposed for training. The obtained SR image is given to the Disease Detection Network (DDN) for grape leaf disease detection. This approach, based on an LR image, assists the farmer in spotting grape plant diseases very early. Proposed model was extensively trained and tested on PlantVillage, Grape 400, Grape Leaf Disease datasets with multiple super-resolution scaling factors for various grape leaves images. For different super-resolution scaling factors such as Χ2, Χ4, Χ6, the proposed model RSNSR-LDD achieved accuracies of 97.19%, 99.37%, and 99.06% for the PlantVillage dataset, 96.88%, 97.12%, and 95.43% for the Grape400 dataset, and 100% for the Grape Leaf Disease dataset. [ABSTRACT FROM AUTHOR]

In a previous article, we modelled the spectral and temporal dimensions of the photodegradation behaviour of pigments in the painting "A Japanese Lantern" by Oda Krohg. In particular, we extracted the endmembers and spectral fading rate of pigments by applying tensor decomposition on a time-series of spectroscopic point measurements. Now, we capture the same painting with a hyperspectral imaging setup and propose an approach to render the fading effects as 2D images. More precisely, from the hyperspectral image, we compute the concentration maps of each previously identified endmember with a least-squares unmixing method. Subsequently, by using tensor algebra, we multiply the concentration maps with the endmembers and their corresponding fading rate and obtain a 4D tensor where each pixel in the image is described by a spectrum and a fading function. This way, we generate past and future spatio-temporal simulations of the painting's appearance by reversing and elevating light exposure, respectively. [ABSTRACT FROM AUTHOR]

Photo-sensitive materials tend to change with exposure to light. Often, this change is visible when it affects the reflectance of the material in the visible range of the electromagnetic spectrum. In order to understand the photo-degradation mechanisms and their impact on fugitive materials, high-end scientific analysis is required. In a two-part article, we present a multi-modal approach to model fading effects in the spectral, temporal (first part) and spatial dimensions (second part). Specifically, we collect data from the same artwork, namely "A Japanese Lantern" by Norwegian artist, Oda Krohg, with two techniques, point-based microfading spectroscopy and hyperspectral imaging. In this first part, we focus on characterizing the pigments in the painting based on their spectral and fading characteristics. To begin with, using microfading data of a region in the painting, we analyze the color deterioration of the measured points. Then, we train a tensor decomposition model to reduce the measured materials to a spectral basis of unmixed pigments and, at the same time, to recover the fading rate of these endmembers (i.e. pure, unmixed chemical signals). Afterwards, we apply linear regression to predict the fading rate in the future. We validate the quality of these predictions by spectrally comparing them with temporal observations not included in the training part. Furthermore, we statistically assess the goodness of our model in explaining new data, collected from another region of the painting. Finally, we propose a visual way to explore the artist's palette, where potential matches between endmembers and reference spectral libraries can be evaluated based on three metrics at once. [ABSTRACT FROM AUTHOR]

The work presented in this paper is part of a wider research project, which aims at documenting and analyzing stained glass windows by means of hyperspectral imaging. This technique shares some similarities with UV-VIS-IR spectroscopy, as they both provide spectral information; however, spectral imaging has the additional advantage of providing spatial information, since a spectrum can be collected in each pixel of the image. Compared to UV-VIS-IR spectroscopy, spectral imaging has rarely been used for the investigation of stained glass windows. One of the objectives of this paper is, thus, to compare the performance of these two instruments to validate the results of hyperspectral imaging. The second objective is to evaluate the potential of analyzing colored-glass pieces in reflectance modality and compare the results with those obtained in transmittance, in order to highlight the differences and similarities between the two approaches. The geometry of the systems and the backing material for the glass, as well as the characteristics of the glass pieces, are discussed. L*a*b* values obtained from the spectra, as well as the calculated color difference ΔE00, are provided, to show the degree of agreement between the instruments and the two measurement modalities. [ABSTRACT FROM AUTHOR]

We study the relationship between reflectance and the degree of linear polarization of radiation that bounces off the surface of an unvarnished oil painting. We design a VNIR-SWIR (400 nm to 2500 nm) polarimetric reflectance imaging spectroscopy setup that deploys unpolarized light and allows us to estimate the Stokes vector at the pixel level. We observe a strong negative correlation between the S0 component of the Stokes vector (which can be used to represent the reflectance) and the degree of linear polarization in the visible interval (average -0.81), while the correlation is weaker and varying in the infrared range (average -0.50 in the NIR range between 780 and 1500 nm, and average -0.87 in the SWIR range between 1500 and 2500 nm). By tackling the problem with multi-resolution image analysis, we observe a dependence of the correlation on the local complexity of the surface. Indeed, we observe a general trend that strengthens the negative correlation for the effect of artificial flattening provoked by low image resolutions. [ABSTRACT FROM AUTHOR]

The virtual inpainting of artworks provides a nondestructive mode of hypothesis visualization, and it is especially attractive when physical restoration raises too many methodological and ethical concerns. At the same time, in Cultural Heritage applications, the level of details in virtual reconstruction and their accuracy are crucial. We propose an inpainting algorithm that is based on generative adversarial network, with two generators: one for edges and another one for colors. The color generator rebalances chromatically the result by enforcing a loss in the discretized gamut space of the dataset. This way, our method follows the modus operandi of an artist: edges first, then color palette, and, at last, color tones. Moreover, we simulate the stochasticity of the lacunae in artworks with morphological variations of a random walk mask that recreate various degradations, including craquelure. We showcase the performance of our model on a dataset of digital images of wall paintings from the Dunhuang UNESCO heritage site. Our proposals of restored images are visually satisfactory and they are quantitatively comparable to state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Ink analysis is an important tool in forensic science and document analysis. Hyperspectral imaging (HSI) captures large number of narrowband images across the electromagnetic spectrum. HSI is one of the non-invasive tools used in forensic document analysis, especially for ink analysis. The substantial information from multiple bands in HSI images empowers us to make non-destructive diagnosis and identification of forensic evidence in questioned documents. The presence of numerous band information in HSI data makes processing and storing becomes a computationally challenging task. Therefore, dimensionality reduction and visualization play a vital role in HSI data processing to achieve efficient processing and effortless understanding of the data. In this paper, an advanced approach known as t-Distributed Stochastic Neighbor embedding (t-SNE) algorithm is introduced into the ink analysis problem. t-SNE extracts the non-linear similarity features between spectra to scale them into a lower dimension. This capability of the t-SNE algorithm for ink spectral data is verified visually and quantitatively, the two-dimensional data generated by the t-SNE showed a better visualization and a greater improvement in clustering quality in comparison with Principal Component Analysis (PCA). [ABSTRACT FROM AUTHOR]

Over the last decade, hyperspectral imaging has become a popular technique for the non-invasive identification and mapping of painting materials in many typologies of artworks, thanks to the possibility of obtaining spectral information over the spatial region. A few attempts have also been made on stained-glass windows to identify the chromophore elements responsible for glass color. Hyperspectral imaging of stained glass can be complex; in most cases, stained-glass windows are an integral part of buildings, and sunlight represents the natural light source for illuminating these artifacts. While it may be considered an advantage, sunlight is not homogeneous throughout the day, and different weather conditions can affect the quality of the hyperspectral images. In addition, the presence of buildings and vegetation in the background could also modify the colors of the stained-glass windows and consequently alter the characteristic peaks of the chromophores in the spectra. This work aims to solve some of these issues and proposes different strategies to improve the results obtainable in situ. The methodology was tested on stained-glass panels displayed in the windows of the Swiss National Museum. Stained-glass panels located in windows of an internal wall were also analyzed, developing a lighting setup to account for the lack of natural light. Hyperspectral images of the selected stained glass were acquired multiple times, choosing different transmittance references for the preprocessing and exposure time to evaluate differences in the collected spectral images. The use of a diffuser sheet to mitigate the effect of external factors was also tested on some panels exposed to sunlight. Results from representative case studies will be presented to discuss the feasibility and limitations of in-situ hyperspectral imaging applications on stained glass and provide some general recommendations to consider during the acquisitions. [ABSTRACT FROM AUTHOR]

Graphical representation of fluorescence turn-on detection of BNP antigen-by-BNP specific antibody tagged gold nanoclusters – MoS 2 nanosheet nano couple. [Display omitted] • An easy and prompt method for the detection of heart failure biomarker was achieved with gold nanocluster / 2D MoS 2 nanosheets. • A stable fluorescence turn - on response was observed with the probe in presence of BNP in physiologically significant serum concentration levels. • The development of the probe and detection of BNP antigen can be achieved within minutes without any high-end instruments. • The probe exhibited a low detection limit of 0.165 pg/mL. In the context of elevated morbidity and mortality risk of heart failure (HF), the establishment of prompt and sensitive diagnosis of HF is vital. A nanostructured fluorescence immuno sensing probe was constructed out of noble metal nanoclusters / two-dimensional transition metal dichalcogenide nano couple to target brain natriuretic peptide (BNP) antigen, a potential multi-utility heart failure biomarker. The green fluorescence of BNP-specific monoclonal antibody-conjugated gold nanoclusters was pre-quenched by a MoS 2 two-dimensional nanosheet, which is subsequently enhanced in the presence of BNP antigen via target-specific antigen–antibody interaction. The probe is free from interferences by other potentially interfering possible co-existing biomolecules and offers easy, low-cost linear detection of BNP in the concentration range 0 to 360.82 pg/mL. [ABSTRACT FROM AUTHOR]

Schematic Representation of developed fluorescent "Turn-off" sensor for the detection of bilirubin. [Display omitted] • Bright green Tb-DPA luminescent complex was designed. • Tb-DPA act as a luminescent probe for the detection of bilirubin. • Selectivity and sensitivity with other coexisting biomolecules were evaluated. • Real sample analysis is performed in human serum and urine samples and obtained satisfactory result. The sensitive and selective fluorescent probes for biomolecule detection have significant application in clinical diagnosis and bioanalysis. Hyperbilirubinemia is a disease condition in which the excessive or less production of bilirubin in blood resulting in jaundice. In this work, we have synthesised Terbium based bright green, fluorescent lanthanide complex (Tb-DPA) with emission at λ em = 544 nm for the detection of Bilirubin. A one-step synthesis approach was adopted with 2,6-pyridine dicarboxylic acid (DPA) as ligand and Sodium dodecyl sulphate (SDS) as surfactant. The green fluorescence of Tb-DPA was quenched with the addition of bilirubin due to the inner filter effect mechanism. The fluorescence intensity of Tb-DPA decreases as bilirubin concentration increases and a linear " turn-off " response is obtained. Even in presence of other coexisting biomolecules and ions, the Tb-DPA probe exhibited good selectivity and sensitivity for the detection of bilirubin. The limit of detection (LOD) of 2.6 mg/dL was obtained. Furthermore, the proposed fluorescent probe was applied in Human serum and urine samples with satisfactory recoveries in the range of 92–122 %. Based on the result obtained, it has probability to be used as a rapid detection method for bilirubin in biological samples at bedside. [ABSTRACT FROM AUTHOR]

Several studies have been focusing on alloying and structural modification of aluminium alloy sacrificial anodes using different activators including intermetallic compounds. With a novel approach, the present work explore and evaluate the feasibility of effective aluminium activation by RuO2 in 95 + 5 Al–Zn alloy substrates. The electrodes prepared in the present work, by making RuO2 film on the substrate, were found to possess good surface interaction, low surface resistivity and facilitate interlayer diffusion of aluminium ions. The electrodes showed excellent galvanic performance under different experimental conditions in 3% NaCl electrolyte. The RuO2 layer was found to persist on the electrode surface even after the electrode size was reduced to one-third of its original size due to long period of galvanic exposure, evidencing its mobile character. The electrodes are economically efficient, convenient to prepare as other conventional hanging electrodes, tolerable to very aggressive media and highly efficient even under high current load. [Copyright &y& Elsevier]

The radiation captured in spectral imaging depends on both the complex light–matter interaction and the integration of the radiant light by the imaging system. In order to obtain material-specific information, it is important to define and invert an imaging process that takes into account both aspects. In this article, we investigate the use of several mixing models and evaluate their performances in the study of oil paintings. We propose an evaluation protocol, based on different features, i.e., spectral reconstruction, pigment mapping, and concentration estimation, which allows investigating the different properties of those mixing models in the context of spectral imaging. We conduct our experiment on oil-painted mockup samples of mixtures and show that models based on subtractive mixing perform the best for those materials. [ABSTRACT FROM AUTHOR]

The direct detection of dopamine (DA) in human body fluids is a great challenge for medical diagnostics of neurological disorders like Parkinson's disease, Alzheimer's disease, senile dementia, and schizophrenia. In this work, a simple and turn off luminescence sensing of DA based on bovine serum albumin (BSA)-capped manganese-doped zinc sulphide quantum dots (Mn:ZnS/BSA QDs) is developed. The Mn:ZnS/BSA QDs were synthesized by a chemical co-precipitation method. Due to the special interaction of DA with BSA and metal ions, Mn:ZnS/BSA QDs can serve as an effective sensing platform for DA. The luminescence of Mn:ZnS/BSA QDs decreased linearly with increasing concentration of DA in the range from 6.6 to 50.6 nM. The limit of detection is 2.02 nM. The driving force for the luminescence quenching is partly provided by ground-state complex formation of QDs with DA. The photo-induced electron transfer from the conduction band of QDs to oxidized dopamine (quinone) also favors quenching. The Mn:ZnS/BSA QDs are barely interfered with by other competing biomolecules except catecholamine neurotransmitter like epinephrine. Moreover, this method is used in the analysis of DA-spiked human serum and human urine samples and good recovery percentages are found. To assess the utility of the developed sensor, paper strip assay was also successfully conducted. [ABSTRACT FROM AUTHOR]

Trinitrotoluene (TNT) is a widely used explosive belonging to the family of nitroaromatic compounds, and its misuse poses a significant threat to society. Herein, we propose a Tb-BSA-AuNC fluorescent and colorimetric sensing probe for the selective onsite detection of TNT in the aqueous phase. Tb-doped BSA-protected gold nanoclusters (Tb-BSA-AuNCs) were synthesized by a microwave-assisted method, and TNT detection was carried out utilizing the chemistry of Meisenheimer complex formation. Tb doping of gold nanoclusters was demonstrated to facilitate better electron shuttling effects and thereby improve the efficiency of complex formation between the TNT and gold nanoclusters. A paper strip assay was also developed for TNT detection with the designed probe. Limits of detection and quantification of 0.2136 mM and 0.7120 mM, respectively, were achieved. [ABSTRACT FROM AUTHOR]

Graphical abstract depicting detection of dopamine based on BSA stabilised copper nanocluster. • Rapid detection of dopamine is achieved by using insitu synthesized blue emitting CuNC. • Dopamine showed fast response towards H2O2 added BSA CuNC with a limit of detection 0.1637 pM. • Dopamine detection is further validated with real sample matrices such as human blood serum samples and urine samples. • Dopamine detection is further validated with real sample matrices such as human serum samples and human urine samples. • A portable paper strip detection method is developed for the onsite detection of dopamine. Rapid and real-time monitoring of catecholamine neurotransmitter dopamine receives immense importance since it plays a crucial role as a local chemical messenger for interneuronal communications in mammalian central and peripheral nervous systems. In the present study, blue emitting copper nanocluster was synthesized in presence (BSA CuNC1) and absence (BSA CuNC2) of hydrogen peroxide and fluorescence response of the two systems towards dopamine was analysed. At an excitation of 355 nm, fast response towards dopamine detection was obtained for BSA CuNC1 system having limit of detection 0.1637 pM. The fast interaction of dopamine with BSA CuNC1 can be attributed to the intrinsic peroxidase like activity of CuNC in presence of H 2 O 2. On the other hand, the response of dopamine towards BSA CuNC2 was very slow with a limit of detection 0.024 nM. Encouraged by the fast response and low limit of detection, the BSA CuNC1 system was effectively applied for dopamine detection in real sample matrices. The recovery percentage for serum sample obtained was in the range 90–98.33% and for urine sample was in the range 89–96.66%. In addition to that, a paper test strips using BSA CuNC1 was developed which exhibited colour change as well as fluorescence quenching, creates a low cost approach for the fast monitoring of dopamine. [ABSTRACT FROM AUTHOR]

Dopamine being a neurotransmitter and chemical messenger plays a vivacious role in a number of significant medical conditions like Parkinson's disease, Attention Deficit Hyperactivity Disorder, Schizophrenia, and drug addiction. As turn-on sensors have a superior level of selectivity than fluorescence quenching based sensors, we developed a fluorescence retrieval strategy for dopamine sensing. Here, highly fluorescent amino phenyl boronic acid ( APBA)-conjugated gold nanocluster ( Au-BSA-APBA probe) has been synthesised from bovine serum albumin-protected gold nanocluster ( Au-BSA NCs). Boronic acid forms boronate ester with disaccharides such as lactose due to its affinity to polyols. Hence fluorescence of Au-BSA-APBA probe is quenched when it binds with lactose molecules through boronate ester formation. The fluorescence of Au-BSA-APBA-lactose system can be retrieved (turn-on) with dopamine by the competitive displacement of lactose from the probe surface which suggests the higher affinity of boronic acid to the catechol group of dopamine. Furthermore, real samples spiked with dopamine including human serum and urine were analysed using this turn-on sensor and showed excellent recovery percentage. The developed fluorescent sensor offered high selectivity for dopamine over other catecholamines and aminoacids with detection limit as low as 0.7 μM. [ABSTRACT FROM AUTHOR]

In this study, the results from a round-robin test of hyperspectral imaging systems are presented and analyzed. Fourteen different pushbroom hyperspectral systems from eight different institutions were used to acquire spectral cubes from the visible, near infra-red and short-wave infra-red regions. Each system was used to acquire a common set of targets under their normal operating conditions with the data calibrated and processed using the standard processing pipeline for each system. The test targets consisted of a spectral wavelength standard and of a custom-made pigment panel featuring Renaissance-era pigments frequently found in paintings from that period. The quality and accuracy of the resulting data was assessed with quantitative analyses of the spectral, spatial and colorimetric accuracy of the data. The results provide a valuable insight into the accuracy, reproducibility and precision of hyperspectral imaging equipment when used under routine operating conditions. The distribution and type of error found within the data can provide useful information on the fundamental and practical limits of such equipment when used for applications such as spectral classification, change detection, colorimetry and others. [ABSTRACT FROM AUTHOR]