Search Results (137)

Deep learning models have demonstrated remarkable success in recognising tipping points and providing early warning signals. However, there has been limited exploration of their application to dynamical systems governed by coloured noise, which characterizes many real-world systems. In this study, we show that it is possible to leverage the normal forms of three primary types of bifurcations (fold, transcritical, and Hopf) to construct a training set that enables deep learning architectures to perform effectively. Furthermore, we showed that this approach could accommodate coloured noise by replacing white noise with red noise during the training process. To evaluate the classifier trained on red noise compared to one trained on white noise, we tested their performance on mathematical models using Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) scores. Our findings reveal that the deep learning architecture can be effectively trained on coloured noise inputs, as evidenced by high validation accuracy and minimal sensitivity to redness (ranging from 0.83 to 0.85). However, classifiers trained on white noise also demonstrate impressive performance in identifying tipping points in coloured time series. This is further supported by high AUC scores (ranging from 0.9 to 1) for both classifiers across different coloured stochastic time series. Full article

This study investigated the impact of spray-drying conditions, specifically inlet air temperature (Tin: 131–159 °C) and feed rate (FR: 4.9–8.4 g/min), on the microencapsulation of oil in a double-layer emulsion stabilised with orange residue flour (ORF) and soy protein. Powders were analysed separately from the drying chamber and the collector, focusing on yield, encapsulation efficiency, moisture, water activity (aw), oil oxidation, colour, and particle size. Chamber powders were more sensitive to Tin, where higher temperatures (155–159 °C) improved yield (up to 47% dry matter (dm)) but also increased oxidation (up to 134% above initial oil). Excessively high FR (8.4 g/min) reduced yield and raised aw (up to 0.39). Collector powders showed more stable yields (average 30 ± 2% dm) but lower encapsulation efficiency (80–86% for chamber vs. 70–77% for collector). Response surface methodology satisfactorily modelled key parameters (R² up to 0.9). Optimisation showed that chamber performance was maximised at 146 °C and 4.9 g/min (predicted yield and aw of 41% and 0.25, respectively), while collector quality improved with slightly higher Tin (150 °C, predicted aw of 0.32). Separately analysing chamber and collector fractions provided novel insights into spray-drying dynamics. These findings highlight ORF as a promising wall material. Full article

Conventional methods of studying houses’ Energy Performance Certificates (EPCs) typically fail to investigate the impact of interrelated contextual elements instead fixating exclusively on the specific attributes of individual houses. This study presents a new method that combines network graph analytics (NGA) with interactive visual analytics to investigate hidden linkages at the individual house level. Our proposed platform collects and analyses data related to housing attributes, creates a network based on the links between these attributes, and employs sophisticated graph algorithms to provide visual representations. Users have the ability to dynamically choose postcodes, metrics, and attributes, which, in turn, generate layouts of networks that provide valuable insights. The visualisation utilises colour gradients and node metrics to improve the comprehensibility of energy performance areas. The platform enables homeowners and stakeholders to comprehend the interrelationships between aspects such as neighbouring housing features, and house infrastructure. The results prove the efficacy of the strategy by giving a collection of case studies that encompass various Energy Performance Certificates (EPCs) ranging from A to G. Each case study demonstrates the evolution of network architectures and visual assessments, showcasing the energy performance linked to certain EPC ratings. The platform offers a user-friendly interface for stakeholders to investigate and understand attribute relationships. Full article

Multi-layer multi-pass welding plays an important role in manufacturing industries such as nuclear power plants, pressure vessel manufacturing, and ship building. However, distortion or welding defects are still challenges; therefore, welding monitoring and quality control are essential tasks for the dynamic adjustment of execution during welding. The aim was to propose a machine vision system for monitoring and surface quality evaluation during multi-pass welding using a line scanner and infrared camera sensors. The cross-section modelling based on the line scanner data enabled the measurement of distortion and dynamic control of the welding plan. Lack of fusion, porosity, and burn-through defects were intentionally generated by controlling welding parameters to construct a defect inspection dataset. To reduce the influence of material surface colour, the proposed normal map approach combined with a deep learning approach was applied for inspecting the surface defects on each layer, achieving a mean average precision of 0.88. In addition to monitoring the temperature of the weld pool, a burn-through defect detection algorithm was introduced to track welding status. The whole system was integrated into a graphical user interface to visualize the welding progress. This work provides a solid foundation for monitoring and potential for the further development of the automatic adaptive welding system in multi-layer multi-pass welding. Full article

Small lakes (<10 km²) provide a range of ecosystem services but are often overlooked in both monitoring efforts and limnological studies. Remote sensing has been increasingly used to complement in situ monitoring or to provide water colour data for unmonitored inland water bodies. However, due to spatial, radiometric, and spectral constraints, it has been heavily focused on large lakes. Sentinel-2 MSI is the first sensor with the capability to consistently retrieve a wide range of essential water quality variables, such as chlorophyll-a concentration (chl-a) and water transparency, in small water bodies, and to provide long time series. Here, we provide and validate a framework for retrieving two variables, chl-a and turbidity, over lakes with diverse optical characteristics using Sentinel-2 imagery. It is based on GRS for atmospheric and sun glint correction, WaterDetect for water detection, and inversion models that were automatically selected based on two different sets of optical water types (OWTs)—one for each variable; for chl-a, we produced a blended product for improved spatial representation. To validate the approach, we compared the products with more than 600 in situ data from 108 lakes located in the Adour–Garonne river basins, ranging from 3 to ∼5000 ha, as well as remote sensing reflectance (Rrs) data collected during 10 field campaigns during the summer and spring seasons. Rrs retrieval (n = 65) was robust for bands 2 to 5, with MAPE varying from 15 to 32% and achieving correlation from 0.74 up to 0.92. For bands 6 to 8A, the Rrs retrieval was much less accurate, being influenced by adjacency effects. Glint removal significantly enhanced Rrs accuracy, with RMSE improving from 0.0067 to 0.0021 sr⁻¹ for band 4, for example. Water quality retrieval showed consistent results, with an MAPE of 56%, an RMSE of 11.4 mg m⁻³, and an r of 0.76 for chl-a, and an MAPE of 47%, an RMSE of 9.7 NTU, and an r of 0.87 for turbidity, and no significant effect of lake area or lake depth on retrieval errors. The temporal and spatial representations of the selected parameters were also shown to be consistent, demonstrating that the framework is robust and can be applied over lakes as small as 3 ha. The validated methods can be applied to retrieve time series of chl-a and turbidity starting from 2016 and with a frequency of up to 5 days, largely expanding the database collected by water agencies. This dataset will be extremely useful for studying the dynamics of these small freshwater ecosystems. Full article

Landscape quality and the productivity of $\mathit{Rhododendron\; simsii}$ are directly related to the maintenance of ecological functions in the alpine region. The specific relationship between the spatial pattern of colour patches and the visual quality of R. simsii landscape recreational forests has been insufficiently explored. In this study, we constructed a model of the relationship between landscape colour patches and the aesthetic value of such a forest, analysing the key factors driving changes in its landscape quality. A total of 1549 participants were asked to assess 16 groups of landscape photographs. The results showed that variations in perceived aesthetic quality were stimulated by colour patch dynamics and spatial heterogeneity. Utilising structural equation modelling (SEM), we identified key indicators synergistically influencing aesthetic quality, including the area percentage, shape, and distribution of colour patches, which demonstrated strong explanatory power ($R^2$ = 0.83). The SEM also revealed that the red patch area, mean perimeter area ratio, and separation index are critical latent variables with standardised coefficients of 0.54, 0.65, and 0.62, respectively. These findings provide actionable design strategies: (1) optimising chromatic contrast through high-saturation patches, (2) controlling geometric complexity, and (3) improving spatial coherence. These results advance the theoretical framework for landscape aesthetic evaluation and offer practical guidance for landscape recreational forest management. Full article

Floral pigmentation contributes directly to reproductive strategies and fitness by shaping pollinator behaviour, and its regulation therefore represents a critical aspect of flower development. Additionally, it is a major determinant of aesthetic and economic value in the ornamental plant industry. This review explores the genetic, biochemical, and ecological bases of floral colour change, focusing on the biosynthesis and regulation of the three major classes of plant pigments: carotenoids, flavonoids (particularly anthocyanins), and betalains. These pigments, derived from primary metabolism through distinct biosynthetic pathways, define the spatial and temporal variability of floral colouration. We discuss the molecular mechanisms underlying flower colour change from opening to senescence, highlighting pigment biosynthesis and degradation, pH shifts, metal complexation, and co-pigmentation. Additionally, we address the regulatory networks, including transcription factors (MYB, bHLH, and WDR) and post-transcriptional control, that influence pigment production. Finally, we provide a comprehensive survey of angiosperm species exhibiting dynamic petal colour changes, emphasizing how these mechanisms are regulated. Full article

Pupil cycle time (PCT) estimates the dynamics of a biofeedback loop established between pupil size and stimulus luminance, size or colour. The PCT is useful for probing the functional integrity of the retinopupillary circuits, and is therefore potentially applicable for assessing the effects of damage due to retinopathies or neuropathies. In previous studies, PCT was measured by manually counting the number of pupil oscillations during a fixed period to calculate the PCT. This method is scarce, requires a good expertise and cannot be used to estimate several PCT parameters, such as the oscillation amplitude or variability. We have developed a computerised setup based on eye-tracking that expands the possibilities of characterising PCT along several dimensions: oscillation frequency and regularity, amplitude and variability, which can be used with a large palette of stimuli (different colours, sizes, shapes or locations), and further allows measuring blinking frequency and eye movements. We used this method to characterise the PCT in young control participants as well as in patients with several pathologies, including age-related macular degeneration (AMD), diabetic retinopathy (DR), retinitis pigmentosa (RP), Stargardt disease (SD), and Leber hereditary optic neuropathy (LHON). We found that PCT is very regular and stable in young healthy participants, with little inter-individual variability. In contrast, several PCT features are altered in older healthy participants as well as in ocular diseases, including slower dynamics, irregular oscillations, and reduced oscillation amplitude. The distinction between patients and healthy participants based on the calculation of the area under the curve of the receiver operating characteristics (AUC of ROC) were dependent on the pathologies and stimuli (0.7 < AUC < 1). PCT nevertheless provides relevant complementary information to assess the physiopathology of ocular diseases and to probe the functioning of retino-pupillary circuits. Full article

Traditional park designs no longer meet the diverse needs of young users amid rising visitor numbers and environmental challenges. Exploring the impact of mountain city parks on youth is crucial, yet localised studies on their spatial perceptions in such unique environments are lacking. Landscape design based on spatial perception evaluation offers a promising approach for renewing mountain parks to address these complex needs. Therefore, a pilot study was conducted in Chongqing’s Pipa Mountain and Eling Parks, involving questionnaire surveys and on-site spatial data collection. Using principal component analysis to select the visual and auditory indicators most related to environmental satisfaction in the overall park and various types of gathering spaces, the results showed that the first principal component of the visual environment in the entrance platform and key nodes (r = 0.41, r = 0.45), as well as the first principal component of the auditory environment in the entrance platform, path platform, and elevated points (r = 0.67, r = 0.85, r = 0.68), all showed significant positive correlations with environmental satisfaction (p < 0.01). Moreover, naturalness and aesthetics were identified as the main factors influencing environmental satisfaction. A random forest model analysed nonlinear relationships, ranking spatial factors by importance. Simultaneously, SHAP analysis highlighted the effects of key factors like elevation changes, green view index, colour diversity, and natural elements. Elevation changes were positively correlated with satisfaction at elevated points but showed a negative correlation in the overall park environment and other gathering spaces. This study explored space-perception dynamics in mountain city parks, proposing strategies to improve environmental quality in various gathering spaces and the park. These findings support creating liveable mountainous environments and guide “human-centred health,” quality enhancement, and sustainable development in renewing mountain city parks. Full article

The challenge of accurately representing diverse visual experiences from the real world through image rendering, especially in High Dynamic Range (HDR) imaging, persists due to limitations in conveying luminosity and colour depth on standard displays. In this study, we explore luminosity and Wide Colour Gamut (WCG) in HDR and investigate prevalent HDR/WCG frameworks like hybrid log-gamma (HLG). The focus lies in overcoming the hurdle of displaying transformed HDR images on Standard Dynamic Range (SDR) screens through HDR tone mapping (TM). Despite numerous TM operators available, the need for a detailed comparative analysis remains the same. This study aims to convert HDR images into HLG-transformed images using ISO 22028-5 and transform these to SDR using various TM methods, followed by encoding them into standard displays. Another objective of the study is to also identify the optimal TM method for preserving image quality and artistic integrity on SDR screens, complemented by evaluating content dependencies and optimizing visualization using gain maps. This paper’s comprehensive evaluation involves subjective experiments to discern the most effective TM methodology, providing insights into the transformative potential of HDR images for broader display compatibility. The results indicate that content-aware TM methods combined with gain map optimization provide superior visual fidelity and are recommended for high-quality HDR-to-SDR rendering. Full article

The ability of a virus to be propagated within a host cell is dependent on a multitude of dynamic virus–host interactions. Live-cell imaging is an invaluable approach in the study of virus replication cycles and virus–host interactions as it can allow for the direct visualisation of key events and interactions in real time. These details can provide unique insights into many aspects of viral infections including the cellular pathways that are exploited by viruses, the evasion of host immune defences, and viral pathogenesis. This review summarises the live-cell fluorescence imaging approaches that have been developed and applied to study Flaviviridae virus family members that are responsible for significant public health burdens and outbreaks which, in many instances, are increasing in frequency and severity. We discuss how these approaches have expanded our understanding of fundamental stages of viral replication cycles by enabling the direct visualisation of the localisation, trafficking, and interactions of virus particles, proteins, and genomes at distinct stages. The strategies that can be employed to enhance the biological relevance of live-cell fluorescence imaging acquisitions are discussed, along with how live-cell imaging approaches can be further developed to increase resolution, enable multi-colour imaging, and support the long-term visualisation of multiple stages of a viral replication cycle. Full article

One of the emerging services provided by roadside green infrastructure is its contribution to the quality of landscape phenology, which is measured through the succession of colours and forms throughout the seasons. In the seasonal dynamics of space, flowering phenological patterns play a key role, particularly in early blooming species such as Cornus mas L. Therefore, this paper aims to highlight the significance of the Cornelian cherry as a component of roadside green infrastructure in the southwestern suburban zone of Belgrade. Through an integrative approach to phenological and climatic elements, and by means of a specific case study covering the period from 2007 to 2025, under climate change conditions, the influence of air temperature and precipitation on local flowering patterns of the Cornelian cherry has been assessed. Based on 1140 phenological observations conducted over 19 consecutive years, from January to April, key flowering elements were identified—those that influence pollination, fruiting, and the species’ practical potential. The Mann–Kendall, Sen’s slope, Rayleigh, and Watson–Williams tests were used to examine spatio-temporal changes in flowering patterns, while the Spearman Rank test and circular statistics were applied to quantify correlations among the analysed parameters. The results confirm that Cornelian cherry is an adaptive and sustainable species that continuously provides visual identity during its flowering period, while simultaneously reflecting climate change through phenological responses. These phenological responses are closely linked to local climatic conditions. In addition to enriching landscape phenology with vibrant visual features during the colder months, Cornelian cherry also enhances biodiversity by providing ecosystem services as a nectar-producing species, with its pollen serving as an early and valuable food source for bees. The study also confirms that the seasonal dynamics of landscape phenology can be used as a scientifically valid criterion for assessing the ecological quality of roadside green infrastructure. Full article

Numerous studies have explored the role of colour in classroom environments and its effects on learning, cognition and motivation. However, research on coloured lighting remains limited, with most studies focusing only on correlated colour temperature (CCT). Addressing this gap, our study examines various chromatic lighting conditions that enhance learning outcomes while allowing for dynamic applications in educational settings. Conducted over three academic years in six primary classrooms, this quasi-experimental study employed a pretest and a control group to assess the effects of three chromatic lighting scenarios (orange, green and purple) on cognitive processes, emotional responses and basic instrumental learning. Descriptive, variance and comparative analyses revealed conclusive evidence of coloured lighting’s impact, though effects varied across different variables. The study highlights the potential of dynamic lighting approaches to support learning and suggests that AI-assisted lighting adjustments could aid teachers. The findings support the broader implementation of coloured lighting in primary classrooms, advocating for cost-effective, sustainable and adaptive solutions beyond conventional lighting. Such advancements are expected to enhance students’ learning, cognition and motivation while providing greater flexibility in educational environments. Full article

This study investigates the interaction between thermochromic liquid crystal (TLC) inks and bacterial nanocellulose (BNC), emphasizing their compatibility for smart packaging applications. While the chiral nematic structure of TLC pigments dictates their dynamic colour changing behaviour, this research focuses on how TLC inks interact with BNC, a biodegradable and eco-friendly substrate. This study examines material compatibility, colorimetric properties, and the influence of substrate characteristics on the thermally induced colour transitions of TLC inks. Screen printing was employed to deposit TLC inks onto BNC-based films and black uncoated paper, followed by spectrometric analysis to evaluate the temperature-dependent colour response. The results indicate that BNC serves as a promising platform for TLC ink integration, enhancing its potential for intelligent packaging and indicator systems. These findings contribute to the advancement of sustainable, responsive materials for next-generation smart packaging solutions. Full article

Background: Right ventricular thrombosis (RVT) is rarely detected in clinical practice. Depending on its aetiology, RVT may originate from a deep venous thrombosis (type A) or in situ (type B). Type A is characterized by increased mobility and frequent pulmonary embolization, whereas type B is nonmobile and is associated with significant right ventricular (RV) dilatation and dysfunction. Methods: A type B RVT complicated by subsegmental pulmonary embolism (PE) was diagnosed in a 46-year-old man with acute-on-chronic respiratory failure secondary to acute exacerbation of interstitial lung disease. He underwent a multimodality imaging assessment of the RV mass that comprehensively incorporated TTE, TEE, contrast-enhanced chest CT, and LGE-CMR. Results: During the clinical course, a serial echocardiographic assessment of the RV mass allowed for a dynamic evaluation of its features and cardiac haemodynamics. Conventional TTE was implemented with colour tissue Doppler imaging (TDI) and pulsed wave (PW) TDI to improve the visualization of the RV mass and to objectively measure its mobility. The increased RVT mass peak antegrade velocity (>10 cm/s) was predictive of subsequent RVT fragmentation and PE. Conclusions: Colour TDI and PW-TDI may aid in the differential diagnosis of RV masses and may improve the prognostic risk stratification of patients with right-sided intracardiac masses. Full article