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Hydroxyapatite (HAp) is the most important constituent of biological tissues such as bone and teeth and exhibits several characteristic features. HAp nanoparticles (NPs) are good host materials and can be functionalized with various kinds of dopants and substrates. By endowing HAp NPs with desired properties in order to render them suitable for biomedical applications including cellular imaging, non-invasive and quantitative visualisation of molecular process occurring at cellular and subcellular levels becomes possible. Depending on their functional properties, HAp based nanoprobes can be divided into three classes, i.e., luminescent HAp NPs (for both downconversion and upconversion luminescence), magnetic HAp NPs, and luminomagnetic HAp NPs. Luminomagnetic HAp NPs are particularly attractive in terms of bimodal imaging and even multimodal imaging by virtue of their luminescence and magnetism. Functionalised HAp NPs are potential candidates for targeted drug delivery applications. This review (with 166 references) spotlights the cellular imaging applications of three types of HAp NPs. Specific sections cover aspects of molecular imaging and the various imaging modes, a comparison of the common types of nanoprobes for bioimaging, synthetic methods for making the various kinds of HAp NPs, followed by overviews on fluorescent NPs for bioimaging (such as quantum dots, gold nanoclusters, lanthanide-doped or fluorophore-doped NPs), magnetic HAp NPs for use in magnetic resonance imaging (MRI), luminomagnetic HAp NPs for bimodal imaging, and sections on drug delivery as well as cellular imaging applications of HAp based nanoprobes (including targeted imaging). Graphical Abstract Hydroxyapatite nanoparticles (HAp NPs) with different functional properties such as luminescence and magnetism are potential candidates for drug delivery as well as multimodal imaging. The review spotlights such applications of luminescent, magnetic and luminomagnetic HAp NPs and discussed their synthesis and characterization.

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.

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.

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.

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.

For a suspected forgery that involves the falsification of a document or its contents, the investigator will primarily analyze the document’s paper and ink in order to establish the authenticity of the subject under investigation. As a non-destructive and contactless technique, Hyperspectral Imaging (HSI) is gaining popularity in the field of forensic document analysis. HSI returns more information compared to conventional three channel imaging systems due to the vast number of narrowband images recorded across the electromagnetic spectrum. As a result, HSI can provide better classification results. In this publication, we present results of an approach known as the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm, which we have applied to HSI paper data analysis. Even though t-SNE has been widely accepted as a method for dimensionality reduction and visualization of high dimensional data, its usefulness has not yet been evaluated for the classification of paper data. In this research, we present a hyperspectral dataset of paper samples, and evaluate the clustering quality of the proposed method both visually and quantitatively. The t-SNE algorithm shows exceptional discrimination power when compared to traditional PCA with k-means clustering, in both visual and quantitative evaluations.

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 S 0 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.

Carbon dots doped with sulfur and nitrogen (S,N-CDs) were utilised to design a paper-stripe based fluorescent probe for the detection of bilirubin. The S,N-CDs were synthesized through a microwave assisted route by using citric acid as carbon source and L-cysteine as a source of nitrogen and sulfur. The S,N-CDs exhibit bright blue fluorescence emission with a peak at 452 nm. Fluorescence is quenched by Fe(III) but selectively restored by bilirubin. The quenched fluorescent probe exhibit significant selectivity and sensitivity for bilirubin in the 0.2 nM to 2 nM concentration range, with a 0.12 nM detection limit. The method was applied to the determination of bilirubin in spiked human serum and urine samples. The method was used to design a paper based test stripe as a point of care device for visual bilirubin detection. Graphical abstract Schematic representation of sulphur and nitrogen doped carbon dots whose fluorescence is quenched by Fe(III) and turned on by bilirubin. Photograph of the corresponding system under day light and UV shows the feasibility of the phenomenon. The applicability of the assay was further extended by impregnating the probe on a filter paper.

Dry eye significantly impacts visual function, productivity, and quality of life. The personal and economic burden of modern dry eye management is substantial. Yoga, known for its physical and mental health benefits, includes practices such as Jyothi Trataka, a visual concentration exercise that may alleviate dry eye symptoms. Given its minimal resource requirements and ease of implementation, Jyothi Trataka may serve as a cost-effective, accessible adjunct to the management of dry eye. This study aimed to evaluate the effectiveness of a 12-week Jyothi Trataka practice in alleviating the signs and symptoms of dry eye. A randomized controlled trial with an open-label, parallel-group design was conducted in adults with mild-to-moderate dry eye. A total of 49 participants of both genders, aged 20 to 40 years, with mild-to-moderate dry eye, were randomly assigned to either a yoga group (  = 25) or a control group (  = 24). Three participants discontinued the intervention, including one from the yoga group and two from the control group, resulting in a final sample of 24 participants in the yoga group and 22 in the control group. All participants provided a medical history and underwent ocular surface and symptom evaluation using standardized protocols at baseline and at the end of the 12-week intervention. The yoga group practiced Jyothi Trataka online for 25 min, 3 days per week, for 12 weeks. The control group received no intervention. Dry eye symptoms were assessed using the Ocular Surface Disease Index (OSDI) score, and the three dry eye signs analyzed were tear breakup time (TBUT), Schirmer's score, and tear meniscus height (TMH). Between-group comparisons using the Mann-Whitney U-test revealed significant improvements in the OSDI score ( < 0.01) and TBUT ( < 0.01) in the yoga group. No significant changes were observed in Schirmer's score or TMH. Yoga, specifically Jyothi Trataka, positively affects dry eye symptoms and may be considered a complementary therapy for their management. Longer-duration studies are warranted to explore additional benefits. https://ctri.nic.in/Clinicaltrials/login.php. Clinical Trial Registry of India (CTRI No. REF/2021/07/045631).

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.