Search Results (217)

Artistic style transfer aims to transfer the style of an artwork to a photograph while maintaining its original overall content. Although current style-transfer methods have achieved promising results when processing photorealistic images, they often struggle with brushstroke preservation in artworks, especially in styles such as oil painting and pointillism. In such cases, the extracted style and content features tend to include redundant information, leading to issues such as blurred edges and a loss of fine details in the transferred images. To address this problem, this paper proposes a multi-scale general style-transfer network based on diffusion models. The proposed network consists of a coarse style-transfer module and a refined style-transfer module. First, the coarse style-transfer module is designed to perform mainstream style-transfer tasks more efficiently by operating on downsampled images, enabling faster processing with satisfactory results. Next, to further enhance edge fidelity, a refined style-transfer module is introduced. This module utilizes a segmentation component to generate a mask of the main subject in the image and performs edge-aware refinement. This enhances the fusion between the subject’s edges and the target style while preserving more detailed features. To improve overall image quality and better integrate the style along the content boundaries, the output from the coarse module is upsampled by a factor of two and combined with the subject mask. With the assistance of ControlNet and Stable Diffusion, the model performs content-aware edge redrawing to enhance the overall visual quality of the stylized image. Compared with state-of-the-art style-transfer methods, the proposed model preserves more edge details and achieves more natural fusion between style and content. Full article

This research develops a dual physics-based machine learning system to forecast fuel consumption and CO₂ emissions for a 100 m oil tanker across six operational scenarios: Original, Paint, Advanced Propeller, Fin, Bulbous Bow, and Combined. The combination of hydrodynamic calculations with Monte Carlo simulations provides a solid foundation for training machine learning models, particularly in cases where dataset restrictions are present. The XGBoost model demonstrated superior performance compared to Support Vector Regression, Gaussian Process Regression, Random Forest, and Shallow Neural Network models, achieving near-zero prediction errors that closely matched physics-based calculations. The physics-based analysis demonstrated that the Combined scenario, which combines hull coatings with bulbous bow modifications, produced the largest fuel consumption reduction (5.37% at 15 knots), followed by the Advanced Propeller scenario. The results demonstrate that user inputs (e.g., engine power: 870 kW, speed: 12.7 knots) match the Advanced Propeller scenario, followed by Paint, which indicates that advanced propellers or hull coatings would optimize efficiency. The obtained insights help ship operators modify their operational parameters and designers select essential modifications for sustainable operations. The model maintains its strength at low speeds, where fuel consumption is minimal, making it applicable to other oil tankers. The hybrid approach provides a new tool for maritime efficiency analysis, yielding interpretable results that support International Maritime Organization objectives, despite starting with a limited dataset. The model requires additional research to enhance its predictive accuracy using larger datasets and real-time data collection, which will aid in achieving global environmental stewardship. Full article

Barite, a mineral composed of barium sulphate, holds global significance due to its wide range of industrial applications. It plays a crucial role as a weighting agent in drilling fluids for the oil and gas industry, in radiation shielding, and as a filler in paints and plastics. Although there are significant deposits of the mineral in commercial quantities in Nigeria, the use of barite of Nigerian origin has been low in the industry due to challenges that require further research and development. This research employed nanoindentation experiments using a model Ti950 Tribo indenter instrument equipped with a diamond Berkovich tip. Using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX), we gained information about the structure and elements in the samples. The load–displacement curves were examined to determine the hardness and reduced elastic modulus of the barite samples. The SEM images showed that barite grains have a typical grainy shape, with clear splitting lines and sizes. XRD and EDX analysis confirmed that the main components are chlorite, albite, barium, and oxygen, along with small impurities like silicon and calcium from quartz and calcite. The average hardness of the IB3 and IB4 samples was 1.88 GPa and 1.18 GPa, respectively, meaning that the IB3 sample will need more energy to crush because its hardness is within the usual barite hardness range of 1.7 GPa to 2.0 GPa. The findings suggest further beneficiation processes to enhance the material’s suitability for drilling and other applications. Full article

The Buades Gallery (1973–2003) was not merely a commercial space in Madrid. In the history of art in Spain, it served as a professional and political node for Spanish conceptualism, an art form which, due to its idiosyncrasies, required its own channels of distribution. This article seeks to examine the trajectory of Mercedes Buades in alignment with this movement, re-evaluating her role from a feminist perspective and highlighting the importance of certain agents who have traditionally been invisibilised. To this end, a theoretical approach is adopted, following the sociology of art and the social history of art, paying particular attention to the contributions of Enrico Castelnuovo, Pierre Bourdieu and Núria Peist. These frameworks enable an analysis of the role of the gallerist as a structuring agent within the artistic field, capable of generating symbolic capital and establishing dynamics of production, circulation and consumption in the context of post-Franco Spain, a country that lacked a consolidated museum infrastructure at the time. Even so, Mercedes Buades established a model of gallery practice that, beyond its commercial dimension, contributed decisively to the symbolic configuration of contemporary art in Spain and formed part of a network of artistic visibility that promoted experimental art. Full article

Style transfer technology has seen substantial attention in image synthesis, notably in applications like oil painting, digital printing, and Chinese landscape painting. However, it is often difficult to generate migrated images that retain the essence of paper-cutting art and have strong visual appeal when trying to apply the unique style of Chinese paper-cutting art to style transfer. Therefore, this paper proposes a new method for Chinese paper-cutting style transformation based on the Transformer, aiming at realizing the efficient transformation of Chinese paper-cutting art styles. Specifically, the network consists of a frequency-domain mixture block and a multi-level feature contrastive learning module. The frequency-domain mixture block explores spatial and frequency-domain interaction information, integrates multiple attention windows along with frequency-domain features, preserves critical details, and enhances the effectiveness of style conversion. To further embody the symmetrical structures and hollowed hierarchical patterns intrinsic to Chinese paper-cutting, the multi-level feature contrastive learning module is designed based on a contrastive learning strategy. This module maximizes mutual information between multi-level transferred features and content features, improves the consistency of representations across different layers, and thus accentuates the unique symmetrical aesthetics and artistic expression of paper-cutting. Extensive experimental results demonstrate that the proposed method outperforms existing state-of-the-art approaches in both qualitative and quantitative evaluations. Additionally, we created a Chinese paper-cutting dataset that, although modest in size, represents an important initial step towards enriching existing resources. This dataset provides valuable training data and a reference benchmark for future research in this field. Full article

The genus Salvia L. (Lamiaceae) is characterized by complex taxonomy and controversial phylogeny. This genus includes about a thousand species with worldwide distribution and high ecological, structural, functional and morphological diversity. Because of their high content of essential oils, various Salvia plants are widely used in medicine, as well as in the food, perfume, cosmetic, and paint industries; they also are valuable melliferous resources. The present study reviews the taxonomic history of the genus Salvia and the phylogenetic relationships between the taxa within the subgenera Salvia, Sclarea, and Glutinaria. Among the Salvia species, three basic chromosome numbers, x = 7, x = 8, and x = 11, were most common, although other basic chromosome numbers (x = 6–19) were determined, which was probably due to events of dysploidy, aneupoidy, and/or polyploidy occurring during speciation. Recent molecular cytogenetic studies based on Next Generation Sequencing technologies have clarified the chromosomal organization of several Salvia species. The patterns of chromosome distribution of 45S rDNA, 5S rDNA, and satellite DNAs made it possible to assess their intra- and interspecific chromosome diversity. However, further cytogenetic studies are needed to characterize the chromosomes in the genomes of other Salvia species and specify the genomic relationships among them. Full article

Human development has led to increased production of oil and gas, mainly as energy sources, which, however, are responsible for contamination and metal corrosion in industrial, marine, and terrestrial environments. Lubricating oil, in particular, is widely used in generators and industrial machines in the electric sector and is responsible for contamination not only in industrial environments but also in many terrestrial and aquatic ecosystems. In this context, this study aimed to apply the Starmerella bombicola ATCC 222214 biosurfactant to inhibit metal corrosion in seawater and in an Accelerated Corrosion Chamber (ACC). For this purpose, its toxicity against the microcrustacean Artemia salina, its dispersion capacity, and its ability to promote oil biodegradation in a saline environment were investigated. The biosurfactant, when applied at twice its Critical Micellar Concentration (CMC), caused low mortality (30.0%) of microcrustaceans in a saline environment, and, in its crude form, the biosurfactant ensured the dispersion of no less than 77.56% of residual engine oil in seawater. Oil biodegradation by autochthonous microorganisms reached 94.39% in the presence of the biosurfactant in seawater. Furthermore, the biosurfactant, when used at twice its CMC, acted satisfactorily as a corrosion inhibitor by reducing the mass loss of galvanized iron specimens (plates) in seawater in a static system to only 0.36%. On the other hand, when the biosurfactant was added at the CMC as an atmospheric corrosion inhibitor, the reduction in mass loss of carbon steel plates treated in the ACC was 17.38% compared to the control containing only a biodegradable matrix based on vegetable resin. When the biosurfactant was incorporated into different paints applied to galvanized iron plates placed in contact with the salt spray produced in the ACC, the best result was obtained using the biomolecule at a concentration of 3% in the satin paint, ensuring a plate mass loss (29.236 g/m²) that was almost half that obtained without surfactant (52.967 g/m²). The study indicated the use of yeast biosurfactant as a sustainable alternative in combating the contamination of marine environments and metal corrosion, with the aim of preserving the environment and improving the quality of life in aquatic and terrestrial ecosystems. Full article

Automatic classification of oil-painting styles holds significant promise for art history, digital archiving, and forensic investigation by offering objective, scalable analysis of visual artistic attributes. In this paper, we introduce a deep conditional information bottleneck (CIB) framework, built atop ResNet-50, for fine-grained style classification of oil paintings. Unlike traditional information bottleneck (IB) approaches that minimize the mutual information $I(X;Z)$ between input X and latent representation Z, our CIB minimizes the conditional mutual information $I(X;Z\mid Y)$, where Y denotes the painting’s style label. We implement this conditional term using a matrix-based Rényi’s entropy estimator, thereby avoiding costly variational approximations and ensuring computational efficiency. We evaluate our method on two public benchmarks: the Pandora dataset (7740 images across 12 artistic movements) and the OilPainting dataset (19,787 images across 17 styles). Our method outperforms the prevalent ResNet with a relative performance gain of $13.1\%$ on Pandora and $11.9\%$ on OilPainting. Beyond quantitative gains, our approach yields more disentangled latent representations that cluster semantically similar styles, facilitating interpretability. Full article

This study investigates Hispano-Muslim plasterworks, exemplified by the Cuarto Real de Santo Domingo, the Madraza, and the Alhambra in Granada, focusing on cleaning methods to remove oil-based repaintings without damaging the original polychromies. To this end, samples replicating traditional materials (gypsum coating, pigments, and binders) and techniques (tempera painting) were prepared and subjected to an artificial ageing protocol (AAP). Subsequently, cleaning tests aimed at removing the oil repaintings were performed to recover the original polychromies. Analytical techniques, including Fourier Transform Infrared Spectroscopy (FTIR), Gas Chromatography–Mass Spectrometry (GC–MS), and colorimetry, were employed to evaluate ageing effects and cleaning efficacy. Results revealed significant chromatic alterations in vermilion and azurite bound with animal glue, while ochre remained comparatively stable. Chemical analyses indicated marked binder deterioration, including protein denaturation in animal glue and oxidation/polymerization in linseed oil. Cleaning tests demonstrated that both a heptane–acetone gel and a novel polyamidoamine–glycine (PAAGLY) treatment effectively removed oil-based repaintings while preserving the original layers. These findings highlight the critical role of pigment–binder interactions in conservation strategies and advocate for selective, minimally invasive restoration methods. Full article

Hatchett’s Brown, also known as Van Dyck Rose, was a unique pigment used in the 19th century, discovered and described by Charles Hatchett in 1803. This article presents the results of research on the identification of this pigment in the works of Henryk Siemiradzki and a 17th-century painting that was overpainted in the 19th century. Advanced analytical techniques, such as XRF, SEM-EDS, and Raman spectroscopy, were used to analyze pigments from the painter’s palette and the paint layers. This study sheds light on the use of Hatchett’s Brown in painting and its potential impact on the interpretation of historical overpainting. Full article

This study focuses on the nameplate of Vila D. Bosco, a modern building in Macau from the time of Portuguese rule, and looks at the types of metal materials and surface coatings used, as well as how they corrode due to the tropical marine climate affecting the building’s metal parts. The study uses different techniques, such as X-ray fluorescence spectroscopy (XRF), scanning electron microscopy/energy dispersive spectroscopy (SEM-EDS), X-ray diffraction (XRD), attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR), and cross-sectional microscopic analysis, to carefully look at the metal, corrosion products, and coating of the nameplate. The results show that (1) the nameplate matrix is a resulfurized steel with a high sulfur content (Fe up to 97.3% and S up to 1.98%), and the sulfur element is evenly distributed inside, which is one of the internal factors that induce corrosion. (2) Rust is composed of polycrystalline iron oxides such as goethite (α-FeOOH), hematite (α-Fe₂O₃), and magnetite (Fe₃O₄) and has typical characteristics of atmospheric oxidation. (3) The white and yellow-green coatings on the nameplate are oil-modified alkyd resin paints, and the color pigments are TiO₂, PbCrO₄, etc. The surface layer of the letters is protected by a polyvinyl alcohol layer. The paint application process leads to differences in the thickness of the paint in different regions, which directly affects the anti-rust performance. The study reveals the deterioration mechanism of resulfurized steel components in a subtropical polluted environment and puts forward repair suggestions that consider both material compatibility and reversibility, providing a reference for the protection practice of modern and contemporary architectural metal heritage in Macau and even in similar geographical environments. Full article

In this article, for the first time on this topic, we analyze the historical color palettes of Renaissance oil paintings by using machine-learning methods and digital images. Our work has two main parts: we collect data on their historical color palettes and then use machine learning to predict the original colors of paintings. This model studies color ratios, enhancement levels, symbolic meanings, and historical records. It looks at key colors, measures their relationships, and learns how they have changed. The main contributions of this work are as follows: (i) we develop a model that predicts a painting’s original color palette based on multiple factors, such as the color ratios and symbolic meanings, and (ii) we propose a framework for using cognitive computing tools to recover the original colors of historical artworks. This helps us to rediscover lost emotional and cultural details. Full article

This study focuses on investigating the stability of modern and contemporary paints based on manganese violet pigment PV16 (NH₄MnP₂O₇) when exposed to atmospheric pollutants, specifically sulfur dioxide (SO₂) in the presence of high relative humidity. In particular, this study aims to investigate the role of PV16 in increasing the degradation processes of various modern binders. Therefore, the objectives of this research can be divided into (i) evaluating the chemical modifications involving PV16, (ii) investigating the degradation processes that occur in different organic matrices (i.e., drying oil, alkyd resin, and acrylic and styrene–acrylic emulsions), and (iii) comparing the chemical stability of model and commercial paints. The paints were analyzed by 3D Optical Microscopy, Attenuated total Reflection–Fourier-Transform Infrared spectroscopy (ATR-FTIR) and μ-Raman Spectroscopy, Scanning Electron Microscope coupled with Energy Dispersive X-Ray spectroscopy (SEM-EDX), X-Ray Powder Diffraction (XRPD), Fiber Optic Reflectance Spectroscopy (FORS), Pyrolysis–Gas Chromatography–Mass Spectrometry (Py-GC/MS), and Thermally assisted Hydrolysis and Methylation (THM) of Py-GC/MS (THM-Py-GC/MS). The results show that when exposed to high relative humidity and SO₂, PV16 presents a colorimetric change from violet to grey; several compounds crystallize on the surface; and, depending on the binder, various degradation reactions occur. This study highlights the susceptibility of manganese violet pigment PV16 under certain environmental conditions, which may be considered to define adequate conservation strategies for works of art containing this specific pigment. Additionally, the results obtained within this investigation point out the need to expand the chemical knowledge of this material for engineering, sensing, and industrial applications. Full article

Zinc is an essential trace metal element in the human body, but it also constitutes a variety of proteins in the body of the important elements necessary; this element plays an important role in physiological metabolism. Disturbances in the metabolism of zinc ions in the body can significantly threaten human health, especially neurological diseases. Therefore, developing a rapid and straightforward method for determining zinc ions is important. Fluorescent probe technology has been widely used for detecting and labeling zinc ions. Among many fluorescent probes, the rhodamine derivative LPDQ fluorescent probe has unique application scenarios, for example, it plays an important role in the detection of zinc white in oil colors, and its advantages are simplicity, rapidity, and real-time operation. This paper introduces the types of fluorescent probes for zinc ions and the three main mechanisms of fluorescent probe detection. The characteristics, design strategies, and application effects of the three fluorescent probes for zinc ions, as well as their advantages and limitations, are reviewed and summarized, which are intended to provide valuable references for the development of new probes for zinc ions detection in the future and for the future direction of research in this field. Full article

One of the key problems in the billet and shaped casting of aluminum alloys is the presence of various undesirable inclusions and impurities in the melt, which can serve as stress concentrators in the finished product, as well as dissolved hydrogen, which contributes to the formation of porosity. The interaction of aluminum with other gases produced by the combustion of fuel particles, oil, and paint materials brought into the furnace together with charge and scrap increases the amount of nitrides, oxides, carbides, and sulfides in the melt. Flux treatment is widely used as protection of aluminum alloys from oxidation and removal of impurities. The present paper reports the data of a comparative analysis of five widely used flux compositions based on sodium, potassium, and magnesium chlorides. The study covers the following aspects: chemical composition, moisture content, melting temperature and melting range, particle size distribution, and refining ability as measured by the change in Na, Ca, and H₂ content after melt treatment. Full article