The Heart of Residency.

Description As part of wellness activities in 2023, our family medicine residents produced individual paintings. Samantha coalesced these 4 × 4 canvases to create this heart. The following quote is also poignant for those of us in family medicine.

Imaging Based Techniques Combined with Color Measurements for the Enhancement of Medieval Wall Paintings in the Framework of EHEM Project.

(1) Background: This paper illustrates an innovative methodological approach chosen to study and map the colors of the medieval wall painting of Santa Maria Antiqua in the Roman Forum, one of the pilot sites of the EHEM project (Enhancement of Heritage Experiences: The Middle Ages). Digital Layered Models of Architecture and Mural Paintings over Time). (2) Methods: Two methods were employed to gather information about colors and mapping. Specifically, colorimetry was utilized for spot measurements, and hypercolorimetric multispectral imaging (HMI) was employed to map the same colors sampled through colorimetry. (3) Results: Chromatic data for all colors in the wall paintings were obtained in the CIELAB color space. Additionally, chromatic similarity maps were generated using the innovative HMI system, a multispectral imaging technique capable of obtaining color data information through advanced calibration software named SpectraPick® (Version 1.1). This comprehensive approach facilitates a thorough understanding of color characteristics and distribution. (4) Conclusions: The color measurements and mapping represent significant advancements in the interpretation of medieval wall paintings, which are often fragmentary and stratigraphically complex. This research sheds new light on the colors used and enhances our understanding of the original appearance of the iconographic patterns. Furthermore, it enables the reconstruction of colors that closely resemble the originals.

Material and Microstructure Analysis of Wood Color Paintings from Shaanxi Cangjie Temple, China.

Cangjie Temple was built to commemorate Cangjie, the legendary inventor of Chinese characters. It stands as one of the few remaining temples in China dedicated to the invention and creation of writing. In this study, the material properties of wooden paintings from the Cangjie temple were characterized using Polarized Light Microscopy (PLM), Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDS), Micro-confocal Raman Spectroscopy, X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC/MS). It was confirmed that the pigments of the paintings included cinnabar, lapis lazuli, lead white, Paris green, and carbon black. The proteinaceous glue was used as an adhesive in the pigment samples, with tung oil likely being utilized as a primer for the wooden structures before painting. This study not only provides valuable data support for the conservation and restoration of the architectural features of Cangjie Temple but also provides useful reference for the maintenance and inheritance of similar ancient buildings.

Non-Destructive Prediction of the Mixed Mineral Pigment Content of Ancient Chinese Wall Paintings Based on Multiple Spectroscopic Techniques.

This study first developed non-destructive and accurate methods to predict the relative contents of mixed mineral pigments in ancient Chinese wall paintings using multiple spectroscopic techniques. The colorimetry, attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR), ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy, and Raman spectroscopy were employed. Analyses were conducted including color difference, spectral reflection, ATR FT-IR spectra, and Raman mapping for simulated samples (malachite-lazurite mixed with rabbit glue samples) before and after aging. Models were then established for predicting the relative pigment contents of samples using UV-Vis-NIR and ATR FT-IR spectral data with Beer-Lambert law, and mathematical methods comprising principal component analysis (PCA) and nonlinear curve fitting. In particular, PCA and empty modeling methods combined with non-negative partial least squares were developed to predict the relative pigment contents based on Raman mapping data. The results demonstrated that approaches comprising PCA, mathematical model, and empty modeling based on the spectral data were effective at predicting the relative pigment contents. The predicted results obtained using the mathematical model based on UV-Vis-NIR spectra had an error of about 2%, and the best prediction based on ATR FT-IR spectra had an error of <3.6% at 1041 cm-1. The errors for the predictions using PCA and empty modeling based on Raman mapping data were 0.01-9.30% and 0.28-7.15%, respectively. However, the predicted relative pigment contents obtained based on ATR FT-IR data combined with the Beer-Lambert law had higher errors. The findings of this study confirm the strong feasibility of using spectroscopic techniques for quantitatively analyzing mixed mineral pigments.

A smartphone image-based method for the colorimetric characterization of historical pigments in mural paintings.

In this article, the detailed description of a smartphone-based analytical method to turn a smartphone into a colorimeter is described and applied to mural painting replicas. The method consists of a camera characterization process, to estimate CIELAB values from RGB camera responses, correcting for potential experimental interferences, like the effect of the lighting/capture geometry or software for color modification and enhancement. Next, the estimated CIELAB descriptors were used to build a chemometric Support Vector Classifier to objectively distinguish among the colors of the different pigments. The method was validated in terms of color reproduction and classification performance.•A smartphone-based method is described to capture mural painting color.•A color gamut-specific camera characterization procedure is developed and the performance of the smartphone-based colorimeter is compared with a spectrophotometer.•A classification method based on the estimated CIELAB descriptors is validated in terms of classification performance.

Prediction of emotion distribution of images based on weighted K-nearest neighbor-attention mechanism.

Existing methods for classifying image emotions often overlook the subjective impact emotions evoke in observers, focusing primarily on emotion categories. However, this approach falls short in meeting practical needs as it neglects the nuanced emotional responses captured within an image. This study proposes a novel approach employing the weighted closest neighbor algorithm to predict the discrete distribution of emotion in abstract paintings. Initially, emotional features are extracted from the images and assigned varying K-values. Subsequently, an encoder-decoder architecture is utilized to derive sentiment features from abstract paintings, augmented by a pre-trained model to enhance classification model generalization and convergence speed. By incorporating a blank attention mechanism into the decoder and integrating it with the encoder's output sequence, the semantics of abstract painting images are learned, facilitating precise and sensible emotional understanding. Experimental results demonstrate that the classification algorithm, utilizing the attention mechanism, achieves a higher accuracy of 80.7% compared to current methods. This innovative approach successfully addresses the intricate challenge of discerning emotions in abstract paintings, underscoring the significance of considering subjective emotional responses in image classification. The integration of advanced techniques such as weighted closest neighbor algorithm and attention mechanisms holds promise for enhancing the comprehension and classification of emotional content in visual art.

Tuning Local Order in Starch Nanoparticles Exploiting Nonsolvency with "Green" Solvents.

Starch is a renewable biopolymer that can be sourced from agricultural waste and used to produce nanoparticles (SNPs). In particular, amorphous SNPs have potential application in numerous fields, including the consolidation of weakened paintings in the cultural heritage preservation. Starch dissolution followed by nanoprecipitation in nonsolvents is an advantageous synthetic route, but new methodologies are needed to feasibly control the physicochemical properties of the SNPs. Here, we explored nanoprecipitation by nonsolvency using a set of "green" solvents to obtain amorphous SNPs, rather than starch nanocrystals already reported in the literature. The effect of the nonsolvent on the ordering of polymer chains in the obtained SNPs was studied. The recovery of local order (e.g., isolated V-type helices) after dissolution was shown to depend on the type of solvents used in the dissolution and precipitation steps, while long-range order (extended arrays of helices) is lost. Aqueous dispersions of the SNPs provided effective consolidation of powdery painted layers, showing that the selection of particle synthetic routes can be dictated by sustainability and scalability criteria. These "green" formulations are candidates as new consolidants in art preservation, and the possibility of tuning local order in amorphous starch assemblies might also impact fields like food chemistry, pharmaceutics, and nanocomposites, where SNPs with tunable amorphousness are more advantageous than nanocrystals.

Public Opinion Through Art: Exploring Chinese University Students' Perspectives on COVID-19 Mass Nucleic Acid Testing.

In the context of the global COVID-19 pandemic, this study focuses on Chinese university students, employing graphic elicitation as a qualitative research method to analyze their hand-drawn paintings and related descriptions. Augmented by A/r/tography and metacognitive methods, the research aims to unveil the participants' collective memory, as well as the perspectives and responses of these students to policies related to the pandemic. By specifically examining this particular demographic, the study incorporates Fairclough's ethical theory, applying deontological ethics, consequentialist ethics, and virtue ethics to establish a comprehensive framework for evaluating adjustments to pandemic response policies. This research not only enhances our understanding of how these university students perceive and adapt to COVID-19 policies but also provides valuable insights for decision-makers. The particular methodology, combining graphic elicitation and metacognitive research, contributes to policy assessment and ethical analysis, offering a nuanced perspective on the interplay between individual perceptions, policy responses, and ethical considerations amid the complexities of a public health crisis.

Microporous electrospun nonwovens combined with green solvents for the selective peel-off of thin coatings from painting surfaces.

Over the last few decades, significant research efforts have been devoted to developing new cleaning systems aimed at preserving cultural heritage. One of the main objectives is to selectively remove aged or undesirable coatings from painted surfaces while preventing the cleaning solvent from permeating and engaging with the pictorial layers. In this work, we propose the use of electrospun polyamide 6,6 nonwovens in conjunction with a green solvent (dimethyl carbonate). By adjusting the electrospinning parameters, we produced three distinct nonwovens with varying average fiber diameters, ranging from 0.4 µm to 2 µm. These samples were characterized and tested for their efficacy in removing dammar varnish from painted surfaces. In particular, the cleaning process was monitored using macroscale PL (photoluminescence) imaging in real-time, while post-application examination of the mats was performed through scanning electron microscopy. The solvent evaporation rate from the different nonwovens was evaluated using gravimetric analysis and Proton Transfer Reaction- Time-of-Flight. It was observed that the application of the nonwovens with small or intermediate pore sizes for the removal of the terpenic varnish resulted in the swollen resin being absorbed into the mats, showcasing a peel-off effect. Thus, this protocol eliminates the need for further potentially detrimental removal procedures involving cotton swabs. The experimental data suggests that the peel-off effect relates to the microporosity of the mats, which enhances the capillary rise of the swollen varnish. Furthermore, the application of these systems to historical paintings underwent preliminary validation using a real painting from the 20th century.

Deep learning assisted XRF spectra classification.

EDXRF spectrometry is a well-established and often-used analytical technique in examining materials from which cultural heritage objects are made. The analytical results are traditionally subjected to additional multivariate analysis for archaeometry studies to reduce the initial data's dimensionality based on informative features. Nowadays, artificial intelligence (AI) techniques are used more for this purpose. Different soft computing techniques are used to improve speed and accuracy. Choosing the most suitable AI method can increase the sustainability of the analytical process and postprocessing activities. An autoencoder neural network has been designed and used as a dimension reduction tool of initial [Formula: see text] data collected in the raw EDXRF spectra, containing information about the selected points' elemental composition on the canvas paintings' surface. The autoencoder network design enables the best possible reconstruction of the original EDXRF spectrum and the most informative feature extraction, which has been used for dimension reduction. Such configuration allows for efficient classification algorithms and their performances. The autoencoder neural network approach is more sustainable, especially in processing time consumption and experts' manual work.

Degradation Potential of Xerophilic and Xerotolerant Fungi Contaminating Historic Canvas Paintings.

Fungi are important contaminants of historic canvas paintings worldwide. They can grow on both sides of the canvas and decompose various components of the paintings. They excrete pigments and acids that change the visual appearance of the paintings and weaken their structure, leading to flaking and cracking. With the aim of recognizing the most dangerous fungal species to the integrity and stability of paintings, we studied 55 recently isolated and identified strains from historic paintings or depositories, including 46 species from 16 genera. The fungi were categorized as xero/halotolerant or xero/halophilic based on their preference for solutes (glycerol or NaCl) that lower the water activity (aw) of the medium. Accordingly, the aw value of all further test media had to be adjusted to allow the growth of xero/halophilic species. The isolates were tested for growth at 15, 24 °C and 37 °C. The biodeterioration potential of the fungi was evaluated by screening their acidification properties, their ability to excrete pigments and their enzymatic activities, which were selected based on the available nutrients in paintings on canvas. A DNase test was performed to determine whether the selected fungi could utilize DNA of dead microbial cells that may be covering surfaces of the painting. The sequestration of Fe, which is made available through the production of siderophores, was also tested. The ability to degrade aromatic and aliphatic substrates was investigated to consider the potential degradation of synthetic restoration materials. Xerotolerant and moderately xerophilic species showed a broader spectrum of enzymatic activities than obligate xerophilic species: urease, ß-glucosidase, and esterase predominated, while obligate xerophiles mostly exhibited ß-glucosidase, DNase, and urease activity. Xerotolerant and moderately xerophilic species with the highest degradation potential belong to the genus Penicillium, while Aspergillus penicillioides and A. salinicola represent obligately xerophilic species with the most diverse degradation potential in low aw environments.

From Perugino to Picasso revisited: Electrophysiological responses to faces in paintings from different art styles.

Behavioral research (Ventura, et al., 2023) suggested that pictorial representations of faces varying along a realism-distortion spectrum elicit holistic processing as natural faces. Whether holistic face neural responses are engaged similarly remains, however, underexplored. In the present study, we evaluated the neural correlates of naturalist and artistic face processing, by exploring electrophysiological responses to faces in photographs versus in four major painting styles. The N170 response to faces in photographs was indistinguishable from that elicited by faces in the renaissance art style (depicting the most realistic faces), whilst both categories elicited larger N170 than faces in other art styles (post-impressionism, expressionism, and cubism), with a gradation in brain activity. The present evidence suggest that visual processing may become finer grained the more the realistic nature of the face. Despite behavioral equivalence, the neural mechanisms for holistic processing of natural faces and faces in diverse art styles are not equivalent.

Database of Expressionist, Impressionist, and Post-Impressionist paintings: Affective norms for 60 art pieces.

Modern painters' art is not only different from canvas created earlier, but also shows high internal variability. Being aware of the conditions arising from art history, we used paintings from three art movements-Impressionism, Post-Impressionism, and Expressionism, to see if we are able to respond to claims made by art theorists by using methods specific to social sciences, and validate the paintings as stimuli which might evoke different emotional reaction based on the movement they were created in. We wanted to conduct an exploratory analysis comparing the mean assessment of valence, arousal, and dominance among the three art movements. A total of 60 different paintings were selected (20 for each art movement) showing figurative works and visible human figures. They were assessed on five different affective scales: valence, arousal, dominance, origin, and subjective significance with use of Self-Assessment Manikins. The results showed expected differences in affective reactions to Expressionist paintings compared with those of Impressionist and Post-Impressionist ones. Therefore, we provided the very first dataset of emotional stimuli with validated affective norms, categorised by the art movement that they were created in and ready to be used in future experimental studies.

Combined macro X-ray fluorescence (MA-XRF) and pulse phase thermography (PPT) imaging for the technical study of panel paintings.

Museum staff usually relies on a proven combination of X-ray radiography (XRR) and infrared reflectography (IRR) to study paintings in a non-destructive manner. In the last decades, however, the research toolbox of heritage scientists has expanded considerably, with a prime example being macro X-ray fluorescence (MA-XRF), producing element-specific images. The goal of this article is to illustrate the added value of augmenting MA-XRF with pulse phase thermography (PPT), a variant of active infrared thermographic imaging (IRT), which is an innovative diagnostic method that is able to reveal variations between or in materials, based on a different response to minor fluctuations in temperature when irradiated with optical radiation. By examining three 16th- and 17th-century panel paintings we assess the extent in which combined MA-XRF and PPT contributes to a better understanding of two commonly encountered interventions to panel paintings: (a) Anstückungen (enlargement of the panel) or (b) substitutions (replacement of part of the panel). Yielding information from different depths of the painting, these two techniques proved highly complementary with IRR and XRR, expanding the understanding of the build-up, genesis, and material history of the paintings. While MA-XRF documented the interventions to the wooden substrate indirectly by revealing variations in painting materials, paint handling and/or layer sequence between the original part and the extended or replaced planks, PPT proved beneficial for the study of the wooden support itself, by providing a clear image of the wood structure quasi-free of distortion by the superimposed paint or cradling. XRR, on the other hand, revealed other features from the wood structure, not visible with PPT, and allowed looking through the wooden panels, revealing e.g. the dowels used for joining the planks. Additionally, IRR visualised dissimilarities in the underdrawings. In this way, the results indicate that PPT has the potential to become an acknowledged add-on to the expanding set of imaging methods for paintings, especially when used in combination with MA-XRF, IRR and XRR.

Xerophilic fungi contaminating historically valuable easel paintings from Slovenia.

Historically valuable canvas paintings are often exposed to conditions enabling microbial deterioration. Painting materials, mainly of organic origin, in combination with high humidity and other environmental conditions, favor microbial metabolism and growth. These preconditions are often present during exhibitions or storage in old buildings, such as churches and castles, and also in museum storage depositories. The accumulated dust serves as an inoculum for both indoor and outdoor fungi. In our study, we present the results on cultivable fungi isolated from 24 canvas paintings, mainly exhibited in Slovenian sacral buildings, dating from the 16th to 21st centuries. Fungi were isolated from the front and back of damaged and undamaged surfaces of the paintings using culture media with high- and low-water activity. A total of 465 isolates were identified using current taxonomic DNA markers and assigned to 37 genera and 98 species. The most abundant genus was Aspergillus, represented by 32 species, of which 9 xerophilic species are for the first time mentioned in contaminated paintings. In addition to the most abundant xerophilic A. vitricola, A. destruens, A. tardicrescens, and A. magnivesiculatus, xerophilic Wallemia muriae and W. canadensis, xerotolerant Penicillium chrysogenum, P. brevicompactum, P. corylophilum, and xerotolerant Cladosporium species were most frequent. When machine learning methods were used to predict the relationship between fungal contamination, damage to the painting, and the type of material present, proteins were identified as one of the most important factors and cracked paint was identified as a hotspot for fungal growth. Aspergillus species colonize paintings regardless of materials, while Wallemia spp. can be associated with animal fat. Culture media with low-water activity are suggested in such inventories to isolate and obtain an overview of fungi that are actively contaminating paintings stored indoors at low relative humidity.

Life on the wall: the diversity and activity of microbes on 13th - century AD. Lan Na mural painting.

Diverse microorganisms from the three domains of life (Archaea, Bacteria, and Eukaryota) cause deterioration in mural paintings worldwide; however, few studies have simultaneously targeted these three domains. This study aims to survey the microbiome and its potential for biodeterioration on unpreserved Lan Na mural paintings in Sean Khan temple, Chiang Mai, Thailand. The overview of the archaeal, bacterial, and fungal communities was reported by Illumina sequencing, whereas the potential for deterioration was revealed by culturable techniques and a literature search. The abundant microbes reported in this study were also found in other ancient mural paintings worldwide. Halococcus, a salt-tolerant archaeon, as well as the eubacterial genus Crossiella dominated the prokaryotic community. On the other hand, the main fungal group was the genus Candida (Ascomycota). However, a low number of fungi and bacteria were isolated. Most of the isolates showed the ability to survive in the drought conditions of mural paintings but could not perform discoloration activities. The deterioration activity mainly affected calcium compounds, which are the main components of painting substrates. Aspergillus and several bacterial isolates could dissolve calcium compounds, but only Trichaptum species could induce crystal formation. These results suggest that deterioration of painting substrate should be taken into consideration in addition to deterioration of color in mural paintings. For the Lan Na painting in Sean Khan temple, the plaster is the prime target for biodeterioration, and thus we suggest that the preservation effort should focus on this component of the mural painting.

The Effect of Prior Viewing Position and Spatial Scale on the Viewing of Paintings.

The visual inspection of scenes is disrupted when participants are forced to begin inspection away from the centre of an image. The present study explored the effect of the starting point on the visual inspection of paintings. Eye movements were recorded while participants viewed paintings for later identification in a yes/no discrimination task. The viewing of each painting was preceded by the presentation of a pseudo-randomly positioned Navon figure. Participants were instructed using a cue to attend to either the local or global level of the Navon figure. Each painting was split into regions of interest (ROIs) defined by face, theme, and context to allow the analysis of eye movements. These data were directly compared with a subset of those initially reported in our previous study in which the same experiment was run but without the inclusion of the Navon figure. The inclusion of the Navon task lowered the discrimination accuracy in the yes/no discrimination task. More importantly, eye movements to the paintings were disrupted across the entire period over which they were viewed and not just in the period following the offset of the Navon figure. The results show the sensitivity of eye movements to the conditions present at the beginning of viewing. The results have implications for the viewing of paintings (and other images) in the real world, where the starting conditions for inspection cannot be controlled.

A Computational Approach to Hand Pose Recognition in Early Modern Paintings.

Hands represent an important aspect of pictorial narration but have rarely been addressed as an object of study in art history and digital humanities. Although hand gestures play a significant role in conveying emotions, narratives, and cultural symbolism in the context of visual art, a comprehensive terminology for the classification of depicted hand poses is still lacking. In this article, we present the process of creating a new annotated dataset of pictorial hand poses. The dataset is based on a collection of European early modern paintings, from which hands are extracted using human pose estimation (HPE) methods. The hand images are then manually annotated based on art historical categorization schemes. From this categorization, we introduce a new classification task and perform a series of experiments using different types of features, including our newly introduced 2D hand keypoint features, as well as existing neural network-based features. This classification task represents a new and complex challenge due to the subtle and contextually dependent differences between depicted hands. The presented computational approach to hand pose recognition in paintings represents an initial attempt to tackle this challenge, which could potentially advance the use of HPE methods on paintings, as well as foster new research on the understanding of hand gestures in art.

Reflectance Spectroscopy as a Novel Tool for Thickness Measurements of Paint Layers.

A major challenge in heritage science is the non-invasive cross-sectional analysis of paintings. When low-energy probes are used, the presence of opaque media can significantly hinder the penetration of incident radiation, as well as the collection of the backscattered signal. Currently, no technique is capable of uniquely and noninvasively measuring the micrometric thickness of heterogeneous materials, such as pictorial layers, for any painting material. The aim of this work was to explore the possibility of extracting stratigraphic information from reflectance spectra obtained by diffuse reflectance spectroscopy (DRS). We tested the proposed approach on single layers of ten pure acrylic paints. The chemical composition of each paint was first characterised by micro-Raman and laser-induced breakdown spectroscopies. The spectral behaviour was analysed by both Fibre Optics Reflectance Spectroscopy (FORS) and Vis-NIR multispectral reflectance imaging. We showed that there is a clear correlation between the spectral response of acrylic paint layers and their micrometric thickness, which was previously measured by Optical Coherence Tomography (OCT). Based on significant spectral features, exponential functions of reflectance vs. thickness were obtained for each paint, which can be used as calibration curves for thickness measurements. To the best of our knowledge, similar approaches for cross-sectional measurements of paint layers have never been tested.