Visual Appearance Research Articles

Tailored Iridescent Visual Appearance of Self-Assembled Correlated-Disordered Nanostructures

Tailored Iridescent Visual Appearance of Self-Assembled Correlated-Disordered Nanostructures

HISTORICAL ASPECT OF THE EVOLUTION OF THE URBAN VISUAL INFORMATION ENVIRONMENT

The article analyses the nature of changes in the urban visual information environment in the context of historical development of European urban culture from ancient times to the present. The system of periodisation of its evolution is proposed on the basis of the revealed role of outdoor information objects in the system of urban visual communication. The dependence of the visual appearance of the urban environ-ment on information-technical achievements is investigated. The role of visual information objects as a sig-nificant city-forming factor is actualised. The typology of information objects is given and their role in the process of changing the image of the city at different stages of its development is considered.

The scope and limits of fine-grained image and category information in the ventral visual pathway.

Humans can easily abstract incoming visual information into discrete semantic categories. Previous research employing functional MRI (fMRI) in humans has identified cortical organizing principles that allow not only for coarse-scale distinctions such as animate versus inanimate objects but also more fine-grained distinctions at the level of individual objects. This suggests that fMRI carries rather fine-grained information about individual objects. However, most previous work investigating fine-grained category representations either additionally included coarse-scale category comparisons of objects, which confounds fine-grained and coarse-scale distinctions, or only used a single exemplar of each object, which confounds visual and semantic information. To address these challenges, here we used multisession human fMRI (female and male) paired with a broad yet homogenous stimulus class of 48 terrestrial mammals, with 2 exemplars per mammal. Multivariate decoding and representational similarity analysis (RSA) revealed high image-specific reliability in low- and high-level visual regions, indicating stable representational patterns at the image level. In contrast, analyses across exemplars of the same animal yielded only small effects in the lateral occipital complex (LOC), indicating rather subtle category effects in this region. Variance partitioning with a deep neural network and shape model showed that across exemplar effects in EVC were largely explained by low-level visual appearance, while representations in LOC appeared to also contain higher category-specific information. These results suggest that representations typically measured with fMRI are dominated by image-specific visual or coarse-grained category information but indicate that commonly employed fMRI protocols may reveal subtle yet reliable distinctions between individual objects.Significance Statement While it has been suggested that functional MRI (fMRI) responses in ventral visual cortex carry fine-grained information about individual objects, much previous research has confounded fine-grained with coarse-scale category information or only used individual visual exemplars, which potentially confounds semantic and visual object information. Here we address these challenges in a multisession fMRI study where participants viewed a highly homogenous stimulus set of 48 land mammals with 2 exemplars per animal. Our results reveal a strong dominance of image-specific effects and additionally indicate subtle yet reliable category-specific effects in lateral occipital complex, underscoring the capacity of commonly employed fMRI protocols to uncover fine-grained visual information.

Adaptive Granularity-Fused Keypoint Detection for 6D Pose Estimation of Space Targets

Estimating the 6D pose of a space target is an intricate task due to factors such as occlusions, changes in visual appearance, and background clutter. Accurate pose determination requires robust algorithms capable of handling these complexities while maintaining reliability under various environmental conditions. Conventional pose estimation for space targets unfolds in two stages: establishing 2D–3D correspondences using keypoint detection networks and 3D models, followed by pose estimation via the perspective-n-point algorithm. The accuracy of this process hinges critically on the initial keypoint detection, which is currently limited by predominantly singular-scale detection techniques and fails to exploit sufficient information. To tackle the aforementioned challenges, we propose an adaptive dual-stream aggregation network (ADSAN), which enables the learning of finer local representations and the acquisition of abundant spatial and semantic information by merging features from both inter-layer and intra-layer perspectives through a multi-grained approach, consolidating features within individual layers and amplifying the interaction of distinct resolution features between layers. Furthermore, our ADSAN implements the selective keypoint focus module (SKFM) algorithm to alleviate problems caused by partial occlusions and viewpoint alterations. This mechanism places greater emphasis on the most challenging keypoints, ensuring the network prioritizes and optimizes its learning around these critical points. Benefiting from the finer and more robust information of space objects extracted by the ADSAN and SKFM, our method surpasses the SOTA method PoET (5.8°, 8.1°/0.0351%, 0.0744%) by 0.5°, 0.9°, and 0.0084%, 0.0354%, achieving 5.3°, 7.2° in rotation angle errors and 0.0267%, 0.0390% in normalized translation errors on the Speed and SwissCube datasets, respectively.

Enhancing grape preservation: The synergistic effect of curry leaf essential oil in buckwheat starch-chitosan composite coatings

A novel edible composite coating composed of buckwheat starch (BS) and chitosan (CH) with varying levels of curry leaf essential oil (CLEO) was synthesized in the present study. Initially, starch was extracted from buckwheat groats, and its proximate analysis revealed a high amylose content (21.91 ± 0.32%), which makes it an excellent base material for coating formation. The composite coatings were created by blending BS and CH with CLEO in different concentrations. The coatings underwent a comprehensive evaluation, including physico-chemical, functional, thermal analyses, and microstructural characterization. Cytotoxicity tests on human cell lines (Caco-2) confirmed that the coatings were non-toxic. Among the various formulations, the coating with 2.0% CLEO (referred to as F5) exhibited the highest antimicrobial activity, maximum antioxidant properties, and the lowest water solubility. Following this, the coatings were applied to green grapes (Vitis vinifera) via dip coating technique. The performance of coatings was assessed by storing the grapes under room temperature (25 ± 1 °C) and refrigeration conditions (4 ± 1 °C). From visual appearance and physio-chemical tests, it was concluded that the F5 coating was potentially active in extending the shelf life of grapes to 12 days at room temperature and to 20 days under refrigeration storage. Overall, the BS-CH-CLEO composite coating emerges as a refined and eco-conscious bioactive packaging solution, elegantly extending the shelf life of grapes while providing both sustainability and cost-efficiency.

Kárpátalja egyházi fenntartású iskoláinak virtuális nyelvi tájképe

We live in an age where everywhere we look, thousands of pieces of information are streaming towards us. This fact in itself highlights the importance of the linguistic landscape in our everyday lives, as everything that surrounds us, everything we perceive influences our thinking and therefore our use of language. In the 21st century, we need to pay particular attention to the virtual world, as a large percentage of the younger and even older generations receive a significant proportion of their stimuli through some types of electronic communication tools or social platforms. Schools have a particularly important role in language development and formation, as young people, the future generation, are most shaped within their walls. In the present study, we analysed a sample of posts published in the last few years on the social platforms (official website and Facebook) of the ecclesiastical schools of Transcarpathia. We relied on statistical and comparative analysis of the textual content of these entries. In addition, we examined the meta-linguistic information of the entries. The overall visual appearance of the website was also taken into consideration, i.e., the types of images published were also investigated. In the research, it was assumed that all the official webpages of the schools under investigation contain entries in both Ukrainian and Hungarian. We also assessed whether a higher percentage of entries in Hungarian appeared on the schools’ online interfaces. Results showed that the number of interactions by people who followed the sites was higher for Hungarian language posts, advertisements and articles. We assumed that religious posts and symbols regularly appeared on the websites and Facebook pages, and that a higher percentage of these posts and symbols appeared in Hungarian. It was also hypothesized that the volume of texts in Ukrainian was smaller than the amount of texts in Hungarian. The research has confirmed that both Ukrainian and Hungarian entries are found on the websites, with a higher share of entries in Hungarian. It also confirmed our hypothesis that followers of the websites tend to respond more frequently to posts in Hungarian, due to the fact that the majority of followers use Hungarian as their mother tongue. Last but not least, the research revealed that religious posts and symbols regularly appear on the official websites and Facebook pages of the lyceums, and the language of these posts is mostly Hungarian.

Two-ways regulation of the emulsion gel properties of curdlan by dry ball milling treatment and their relationships with the microstructures, emulsification characteristics and gel properties of ball milled curdlan

Ball milling treatment could affect the microstructures, improve the emulsification properties of curdlan (CL) and regulate the emulsion gel properties of CL based emulsion gel in two-ways. With increasing ball milling time (1 h–8 h), the particle size first decreased and then increased, the relative crystallinity decreased, and the contact angle increased. Ball milled curdlan (BMCL)-6 h showed the best emulsifying property and stability, which was the combined effects of decreased particle size and increased hydrophobic property. Ball milling 1 h and 2 h significantly improved the hardness and chewiness of CL-based emulsion gels, while, ball milling 4 h–8 h could make the emulsion gels much softer and ice cream-like. When the emulsion gels were heated twice consecutively, the visual appearance and texture properties did not change significantly, indicating the excellent thermal stability of these emulsion gels. The BMCL based emulsion gel with adjustable gel properties and good thermal stability has a wide range of uses in the food system.

A Real-Time and Interactive Fluid Modeling System for Mixed Reality.

Within the realm of mixed reality, the capability to dynamically render environmental effects with high realism plays a crucial role in amplifying user engagement and interaction. Fluid dynamics, in particular, stand out as essential elements for crafting immersive virtual settings. This includes the simulation of phenomena like smoke, fire, and clouds, which are instrumental in enriching the virtual experience. This work showcases a cutting-edge system developed to produce dynamic and interactive fluid effects that mirror real captured data in real-time for mixed reality applications. This innovative system seamlessly incorporates fluid reconstruction alongside velocity estimation processes within the Unity engine environment. Our approach leverages a novel physics-based differentiable rendering technique, grounded in the principles of light transport in participating media, to simulate the intricate behaviors of fluid while ensuring high fidelity in visual appearance. To further enhance realism, we have expanded our framework to include the estimation of velocity fields, addressing the critical need for fluid motion simulation. The practical application of these techniques demonstrates the system's capacity to offer a robust platform for fluid modeling in mixed reality environments. Through extensive evaluations, we illustrate the effectiveness of our approach in various scenes, underscoring its potential to transform mixed reality content creation by providing developers with the tools to incorporate highly realistic and interactive fluid seamlessly.

A Simple Production Process for Prolonging the Microbiological Shelf-Life and Improving the Sensorial Quality of Refrigerated Shucked Mussel (Mytilus galloprovincialis) Products Marketed in Greece

ABSTRACT Commercial production of refrigerated shucked mussels (SM) in Greece presents several challenges that are associated with short shelf-life, lack of taste and development of brown color in the filling medium. To overcome these problems an alternative mussel body recovery process in combination with different filling media, namely brines and white vinegar solutions of various concentrations, was used for the production of SM. A 2-fold to 5-fold increase in the shelf-life of the various SM products was observed when compared against control, while significant improvements were also found in both taste and visual appearance of the products.

The Potential Application of Visible-Near Infrared (Vis-NIR) Hyperspectral Imaging for Classifying Typical Defective Goji Berry (Lycium barbarum L.).

Goji berry is acknowledged for its notable medicinal attributes and elevated free radical scavenger properties. Nevertheless, its susceptibility to mechanical injuries and biological disorders reduces the commercial diffusion of the fruit. A hyperspectral imaging system (HSI) was employed to identify common defects in the Vis-NIR range (400-1000 nm). The sensorial evaluation of visual appearance was used to obtain the reference measurement of defects. A supervised classification model employing PLS-DA was developed using raw and pre-processed spectra, followed by applying a covariance selection algorithm (CovSel). The classification model demonstrated superior performance in two classifications distinguishing between sound and defective fruit, achieving an accuracy and sensitivity of 94.9% and 96.9%, respectively. However, when extended to a more complex task of classifying fruit into four categories, the model exhibited reliable results with an accuracy and sensitivity of 74.5% and 77.9%, respectively. These results indicate that a method based on hyperspectral visible-NIR can be implemented for rapid and reliable methods of online quality inspection securing high-quality goji berries.

A newton interpolation network for smoke semantic segmentation

Smoke has large variances of visual appearances that are very adverse to visual segmentation. Furthermore, its semi-transparency often produces highly complicated mixtures of smoke and backgrounds. These factors lead to great difficulties in labelling and segmenting smoke regions. To improve accuracy of smoke segmentation, we propose a Newton Interpolation Network (NINet) for visual smoke semantic segmentation. Unlike simply concatenating or point-wisely adding multi-scale encoded feature maps for information fusion or re-usage, we design a Newton Interpolation Module (NIM) to extract structured information by analyzing the feature values in the same position but from encoded feature maps with different scales. Interpolated features by our NIM contain long-range dependency and semantic structures across different levels, but traditional fusion of multi-scale feature maps cannot model intrinsic structures embedded in these maps. To obtain multi-scale structured information, we repeatedly use the proposed NIM at different levels of the decoding stages. In addition, we use more encoded feature maps to construct a higher order Newton interpolation polynomial for extracting higher order information. Extensive experiments validate that our method significantly outperforms existing state-of-the-art algorithms on virtual and real smoke datasets, and ablation experiments also validate the effectiveness of our NIMs.

International survey of young adults’ opinions on tobacco endgame measures & e-cigarette regulations

Abstract In the last decade, while tobacco consumption has decreased, there has been a significant rise in e-cigarette usage particularly among young people. Tobacco-free generations and other endgame strategies are being considered in several countries, moving from tobacco control towards ending the tobacco epidemic. This online survey of 18-34-year-olds evaluated opinions on potential endgame measures and e-cigarette regulations, to generate evidence to inform policy decisions. The survey was developed with input from the World Federation of Public Health Associations and Tobacco-Free Ireland, asking participants about support (yes/no) for 20 endgame measures in 4 domains and attitudes towards e-cigarettes. Utilising convenience sampling, the survey was distributed through international networks. Of 295 responses in 34 countries, 72% were never smokers and 56% were never e-cigarette users. 31% were aware of tobacco endgame. 68% supported increasing tobacco purchasing age to 21. 70% supported restricting tobacco sales to a limited number of licenced shops. 73% supported reducing nicotine content in cigarettes. 74% supported tobacco companies having to pay for health costs from smoking. 73% would like to see tobacco-free generation legislation in their country, but only 31% expected it would be successful. Regarding e-cigarettes, they were judged as more desirable than cigarettes mostly due to different flavours and visual appearance (both 74%). They were perceived to be an important health risk (82%) and as or more addictive than cigarettes (78%). 65% believed overall harms from e-cigarettes outweigh benefits for society. 86% felt they should be subjected to the same advertising restrictions as cigarettes and 66% supported increasing their cost. There was strong support for various tobacco endgame measures and tobacco-free generation legislation in this 18-34-year-old cohort. The majority recognised health risks of e-cigarettes and favoured stricter regulation of these products. Key messages • An international survey of 295 young adults in 34 countries demonstrated strong support for various tobacco endgame measures including tobacco-free generation legislation. • For e-cigarettes, there was wide acknowledgement of addictiveness and health risk, and support for increased education and warnings, lower nicotine content and reduced advertising and availability.

Pengaruh Kombinasi Amelioran Vinasse dan Pupuk Kalium Terhadap Pertumbuhan dan Pigmen Warna Daun Aglaonema sp.

Vinasse is an ameliorant that can improve the chemical and physical properties of soil, but its use needs to be combined with inorganic fertilizer. One fertilizer can be used is potassium fertilizer which can increase the growth and colour pigment of Aglaonema sp. This research aims to obtain the best combination of Ameliorant Vinasse and Potassium fertilizer on the growth and leaf colour piment of Agalonema sp. This research on screen house at Campakasari Village, Campaka District, Purwakarta Regency, West Java from February 2024 to April 2024. The method used was a single-factor Randomized Block Design (RBD) with 8 treatments and 4 replications, resulting 32 experimental units consisting of: A (Control KCl 300kg/ha), B (Control Vinasse 10ml/l), C (Vinasse 10ml/l + KCl 200kg/ha), D (Vinasse 10ml/l + KCl 300kg/ha), E (Vinasse 10ml/l + KCl 400kg/ha), F (Vinasse 20ml/l + KCl 200kg/ha), G (Vinasse 20ml/l + KCl 300kg/ha), H (Vinasse 20ml/l + KCl 400kg/ha). The experimental result will be tested with an F-test, and if significant, will be further tested with Duncan Multiple Range Test (DMRT) at the 5% level. The method for leaf colour pigments uses questionnaire data scoring and analysed using multiple linear regression. The result showed that treatments significant affected on the growth and leaf colour pigment of Aglaonema sp. Treatment F (Vinasse 20 ml/l + KCl 200 kg/ha) give the highest yield for plant height(38,8 cm), number of leaves (9,50 leaves), number of shoots (2,25 shoots) and provides a strong correlation regression the visual appearance of leaf colour pigment and supporting factors of Aglaonema sp. on cosumer interest. Keywords: aglaonema sp., ameliorant vinasse, potassium fertilizer

Stability of Sodium Pentobarbital 5w/v% Aqueous Solution During Short-Term Chilled and Ambient-Temperature Storage.

The COVID-19 pandemic made it difficult to obtain pharmaceutical-grade injectable anaesthetics used in animal experiments in Japan. To address this problem, it is worth the effort to evaluate whether the use of non-pharmaceutical-grade sodium pentobarbital (PBNa) water solution can be an alternative one from the perspective of stability, physicochemical properties, bioavailability and so on. In this article, as a first step, we examined the stability of PBNa 5w/v% aqueous solution (PBNa 5% AS). PBNa 5% AS sample was prepared simply by dissolving non-pharmaceutical-grade PBNa into water and was stored at 25°C and 5°C for 15 days. Visual appearance, pH, osmolality and assay (contents of PBNa and related substances) were tested. The stability test results indicated that there was no profound change in these test items of the PBNa 5% AS under either storage condition, suggesting that the formulation was sufficiently stable in such a short term. The only observable change was an increase of an impurity under 25°C storage; however, it was at a negligible level. Moreover, as the pH of the formulation remained <10.0 throughout the storage period in both conditions, the irritant level of the pH is considered to be acceptable. Therefore, from the viewpoint of the stability and physicochemical properties, PBNa 5% AS can be an alternative injectable anaesthetic when access to pharmaceutical-grade anaesthetics is limited, as long as used in short-term from its preparation.

Evaluating the synergistic effects of sesame cake powder and soy protein isolate on rheological, textural, nutritional, and phenolic profiles of high-moisture extrusion processed meat analogs.

In this study, the high-moisture meat analogs (HmMAs) were developed by incorporating defatted sesame cake powder (DSP) in soy protein isolate (SyPI). The quality attributes of HmMA like visual appearance, specific mechanical energy (SME), mass flow rate (MFR), phenolic profile, textural and rheological properties were assessed after varying DSP concentrations (0%, 20%, 40%, and 60% w/w) and feed moisture (FM) levels (55% and 60%). The HmMA1 (derived solely from SyPI) exhibited higher hardness, chewiness, gumminess, cohesiveness, and springiness. The HmMA prepared from SyPI-DSP blends (HmMA2-8) demonstrated significant improvements in nutritional composition, and their visual characteristics indicated noticeable anisotropy. The interaction between SyPI and DSP influenced the quality of HmMA. Thehigher DSP concentration led to higher MFR and deeper curvatures of U-shaped structures, whereas lower SMS, textural and rheological properties. The DSP incorporation and 55% FM adjustments allowed mimicking meat cuts with thick fiber, influenced color, and proved advantageous in developing white meat analogs with higher free phenolics. The findings of the study suggest avenues for exploring DSP at a suitable level in SyPI for the development of better quality meat analogs.

Unirrigated extensive green roofs in humid subtropics – Plant selection and substrate design for low maintenance and climate resilience

Low-maintenance extensive green roofs hold the potential for adapting to climate change, but there is a limited understanding of their effective design in humid subtropical regions. In this study, we aimed to investigate low-maintenance green roof ecosystems capable of thriving under heat stress. Plant growth performance was evaluated in the second year of an experimental green roof in southwest China. This green roof was unirrigated and involved two plant communities (forbs and grasses) cultivated in four substrate types. Metrics of growth performance, including plant survival, green coverage, visual appearance, leaf stomatal conductance, and substrate volumetric water content were used to analyze the impact of substrate on plant growth. ESP substrate, comprising 30 %v (percent of volume) expanded shale, 25 %v perlite, 25 %v vermiculite, and 20 %v compost, featured the highest porosity and optimal growth of forbs, achieving an average green coverage of 66.76 % and average visual appearance value of 3.56 throughout the monitoring period. The high total porosity of this substrate could be critical in facilitating root development and drainage. Moreover, during the summer’s heat and drought, while substrate water content is not a limiting factor for the survival of some established forbs, it remains crucial for the growth of grasses. Additionally, the same substrate impacts different plant communities variably. Four particularly well-performing forb species, namely Lycoris chinensis, Tradescantia pallida, Liriope muscari, and Salvia farinacea, demonstrated survival rates closed to 100 % and an average visual appearance value exceeding 3 was noted, and thus, they are recommended as plant candidates for unirrigated green roofs. The distinguished performance of these species is attributable to their adaptation to heat and drought through specific physiological traits. Our findings provide insights into vegetation selection and substrate optimization for the successful establishment of extensive green roofs that could be feasibly developed without irrigation in the humid subtropical regions.

GS‐Octree: Octree‐based 3D Gaussian Splatting for Robust Object‐level 3D Reconstruction Under Strong Lighting

AbstractThe 3D Gaussian Splatting technique has significantly advanced the construction of radiance fields from multi‐view images, enabling real‐time rendering. While point‐based rasterization effectively reduces computational demands for rendering, it often struggles to accurately reconstruct the geometry of the target object, especially under strong lighting conditions. Strong lighting can cause significant color variations on the object's surface when viewed from different directions, complicating the reconstruction process. To address this challenge, we introduce an approach that combines octree‐based implicit surface representations with Gaussian Splatting. Initially, it reconstructs a signed distance field (SDF) and a radiance field through volume rendering, encoding them in a low‐resolution octree. This initial SDF represents the coarse geometry of the target object. Subsequently, it introduces 3D Gaussians as additional degrees of freedom, which are guided by the initial SDF. In the third stage, the optimized Gaussians enhance the accuracy of the SDF, enabling the recovery of finer geometric details compared to the initial SDF. Finally, the refined SDF is used to further optimize the 3D Gaussians via splatting, eliminating those that contribute little to the visual appearance. Experimental results show that our method, which leverages the distribution of 3D Gaussians with SDFs, reconstructs more accurate geometry, particularly in images with specular highlights caused by strong lighting. The source code can be downloaded from https://github.com/LaoChui999/GS-Octree.

Sulfate attack on portland-dolomite cement exposed to sodium sulfate solution at 5 ℃ and 20 ℃

The purpose of the study is to investigate the sulfate resistance of portland-dolomite cement (PDC) with varying dolomite contents, when exposed to sodium sulfate solution at 5 ℃ and 20 ℃. Visual appearance, expansion, mass change, and compressive strength of PDC mortars were tested, and XRD, FTIR, and SEM analyses were conducted to examine deterioration products and microstructure. Results indicate that at 20 ℃, the incorporation of 10 % dolomite in PDC had a negligible impact on sulfate resistance, whereas higher dolomite replacements of 20 % and 30 % notably diminished it. In contrast, exposure at 5 °C led to more severe deterioration in all PDC samples, regardless of dolomite content, and the higher dolomite content, the poorer resistance to sulfate attack. The increased formation of ettringite and gypsum resulted in reduced sulfate resistance of PDC at 20 ℃. However, at 5 ℃, the presence of dolomite significantly promoted the formation of thaumasite at later stages, which caused initial ettringite and subsequent late-stage thaumasite sulfate attack, ultimately leading to the failure of PDC. The findings suggest that PDC should be carefully considered when used in sulfate-rich environments, particularly at low temperatures.

Decomposed Prototype Learning for Few-Shot Scene Graph Generation

Today's scene graph generation (SGG) models typically require abundant manual annotations to learn new predicate types. Therefore, it is difficult to apply them to real-world applications with massive uncommon predicate categories whose annotations are hard to collect. In this paper, we focus on Few-Shot SGG (FSSGG) , which encourages SGG models to be able to quickly transfer previous knowledge and recognize unseen predicates well with only a few examples. However, current methods for FSSGG are hindered by the high intra-class variance of predicate categories in SGG: On one hand, each predicate category commonly has multiple semantic meanings under different contexts. On the other hand, the visual appearance of relation triplets with the same predicate differs greatly under different subject-object compositions. Such great variance of inputs makes it hard to learn generalizable representation for each predicate category with current few-shot learning (FSL) methods. However, we found that this intra-class variance of predicates is highly related to the composed subjects and objects. To model the intra-class variance of predicates with subject-object context, we propose a novel Decomposed Prototype Learning (DPL) model for FSSGG. Specifically, we first construct a decomposable prototype space to capture diverse semantics and visual patterns of subjects and objects for predicates by decomposing them into multiple prototypes. Afterwards, we integrate these prototypes with different weights to generate query-adaptive predicate representation with more reliable semantics for each query sample. We conduct extensive experiments and compare with various baseline methods to show the effectiveness of our method.

The effect of Vitamin C in the therapy of haemolactia in dairy cows

The aim of this study was to evaluate the effects of intravenous administration of vitamin C in the therapy of haemolactia in dairy cows. Haemolactia is often of unknown origin, and it can occur due to vitamin C deficiency. The research was carried out on twenty-eight dairy cows having clinical signs of haemolactia, with a clinical score of 2 or 3. The cows of the group A (n=10) were treated intravenously with 2000 mg vitamin C, those of the Group B (n=10) with 3000 mg vitamin C intravenously, whereas cows of group C (n=8) were served as controls and remained untreated. The vitamin C application was once per day intravenously until symptoms disappeared. The appearance of milk and the therapeutic effects of vitamin C were monitored during milking, based on the visual appearance of milk. The average duration of haemolactia in both treated groups A and B was significantly lower (72 h and 68 h, respectively) compared to the control group C (102 h) (p&lt;0.05 for both). Vitamin C was shown to be beneficial in the therapy of haemolactia; no statistical difference was observed regarding the administered doses of vitamin C (2000 vs. 3000 mg). The results prove the importance of vitamin C administration to shorten the duration of haemolactia in dairy cows