Search Results (134)

Joint attention, the capacity of two or more individuals to focus on a common event simultaneously, is fundamental to human–human interaction, enabling effective communication. When considering the field of social robotics, emulating this capability might be necessary for promoting natural interactions and thus improving user engagement. Responding to joint attention (RJA), defined as the ability to react to external attentional cues by aligning focus with another individual, plays a critical role in promoting mutual understanding. This study examines how RJA impacts user engagement during human–robot interaction. The participants play a turn-taking game against a social robot under two conditions: with our RJA system active and with the system inactive. Auditory and visual stimuli are introduced to simulate real-world dynamics, testing the robot’s ability to detect and follow the user’s focus of attention. We use a twofold approach to evaluate the system’s impact on the user’s experience during the interaction. On the one hand, we use head pose telemetry to quantify attentional aspects of engagement, including measures of distraction and focus during the interaction. On the other hand, we use a post-experimental questionnaire incorporating the User Engagement Scale Short Form to assess engagement. The results regarding telemetry data reveal reduced distraction and improved attentional consistency, highlighting the system’s ability to maintain attention on the current task effectively. Furthermore, the questionnaire responses show that RJA significantly enhances self-reported engagement when the system is active. We believe these findings confirm the value of attentional mechanisms in promoting engaging human–robot interactions. Full article

Scientific research in Amazonia plays a fundamental role in identifying pathways to sustainable development for the region, addressing the challenges posed by climate change, preserving its unique ecosystems, and aligning with societal challenges and rights advocated by its diverse populations. This paper encompasses a broad range of scientific publications, spanning from 1977 to 2024, and highlights key research areas, analyzing their results and trends to inform future developments. It also identifies areas that require deeper investigation. The results emphasize a focus on agricultural, biological, and environmental sciences. On the other hand, there is a need for more extensive research within the social sciences. As shown, research on indigenous land rights, cultural heritage, and the socio-economic impacts of environmental disruptions is essential for developing comprehensive conservation strategies. Furthermore, research on governance, policy, and socio-political dynamics in Amazonia can provide innovative approaches to addressing the challenges and opportunities for its people, biodiversity, and role in climate regulation, as demonstrated by the findings. The strategic research fields identified in this paper provide a guide for future studies and policy development aimed at protecting the forest and its inhabitants. This study emphasizes the need for approaches that integrate both natural and social sciences as essential for addressing the complex ecological and socio-economic challenges that continue to shape the contemporary research landscape. Furthermore, this paper highlights the importance of unity and cooperation among Amazonian countries and research institutions in achieving these goals. In this context, reinforcing long-term, large-scale research programs such as the LBA (Large-Scale Biosphere–Atmosphere Experiment in Amazonia) and the Scientific Panel for the Amazon (SPA) are crucial to advancing integrated, policy-relevant science for the sustainable future of the region. Full article

In recent years, grain-free pet food has gained increasing attention due to its widespread promotion as a natural and hypoallergenic diet. This trend has prompted us to conduct an in-depth critical assessment of the nutritional implications of such diets. This review systematically analyzed the nutritional components of commercially available grain-free pet food, revealing significant variability in the nutritional composition of commercial pet diets. Moreover, grain-free formulations typically exhibit higher protein and fat levels. On the other hand, this review further explores the multifaceted health impacts of these diets on pets, including digestive function, cardiovascular health, allergic reactions, blood sugar regulation, mycotoxin safety, and palatability. This review points out that grain-free diets may offer potential benefits, such as improved blood sugar control, reduced mycotoxin exposure, and enhanced palatability; however, they also pose clear risks, particularly the potential association with dilated cardiomyopathy (DCM) in dogs. Additionally, the presence or absence of grains in the diet does not mitigate the risk of allergies. A grain-free diet is only intended to help specific individuals (such as those who are sensitive to grains/gluten) avoid allergens. Ultimately, the review emphasizes that nutritional adequacy, balance, and meeting individualized needs are the cornerstones of pet health, aiming to provide valuable insights for pet caregivers, veterinarians, and researchers. Full article

Heavy oil, due to its complex hydrocarbon structure and resistance to degradation, poses significant environmental challenges. There is a lack of knowledge about the biodegradability of heavy oil in the natural environment under aerobic and anaerobic conditions. In this study, we used microbial communities of water and soil samples to investigate the biodegradation of heavy oil. Gas chromatography (GC) analysis was used to measure residual oil. Under aerobic conditions, soil-derived microorganisms demonstrated significantly higher degradation efficiency—achieving up to 80.3% removal—compared to water-derived samples, which showed a maximum degradation of 52.1%. Anaerobic conditions, on the other hand, clearly slowed down degradation; the maximum degradation rates in water and soil samples were 43.7% and 11.1%, respectively. Although no clear linear relationship was found, the correlation between initial microbial populations and degradation performance revealed that higher counts of heterotrophic and oil-degrading bacteria generally enhanced biodegradation. Under anaerobic conditions, especially, persistent hydrocarbon peaks in both environments suggest the presence of recalcitrant heavy oil fractions such as polycyclic aromatic hydrocarbons. In conclusion, this study emphasizes the crucial roles microbial sources and oxygen availability play in maximizing bioremediation techniques for environments contaminated with heavy oil. Full article

Jaboticaba berry is a rich source of polyphenols with bioactive properties. However, polyphenols are known for their high reactivity under environmental conditions, which poses a challenge to producing stable, functional components for the food industry. This study investigated the storage stability and bioaccessibility of polyphenols in microencapsulated jaboticaba juice over 21 days at three storage temperatures: −20 °C, 4 °C, and 25 °C. Additionally, phenolic compounds and antioxidant capacity were evaluated before and after in vitro simulated gastrointestinal digestion. Microencapsulation was performed by spray drying at 160 °C using maltodextrin at different concentrations (10%, 12%, and 15%) as the wall material. The results showed that the stability of polyphenols during storage was significantly influenced by both temperature and the proportion of maltodextrin. Greater degradation of phenolic compounds was observed at 25 °C, particularly in the formulation with 10% maltodextrin. On the other hand, the bioaccessibility of polyphenols was significantly higher in microencapsulated juice after simulated gastrointestinal digestion compared to non-encapsulated jaboticaba juice (p < 0.05). These findings suggest that microencapsulation technique improved the bioaccessibility of phenolic compounds in jaboticaba and promoted better stability with the use of a higher concentration of maltodextrin. In conclusion, microencapsulation is a promising strategy for the development of functional food products enriched with natural bioactive compounds, providing greater protection and efficiency in delivering their health benefits. Full article

Background/Objectives: Optimization algorithms are acknowledged to be critical in various fields and dynamical systems since they provide facilitation in identifying and retrieving the most possible solutions concerning complex problems besides improving efficiency, cutting down on costs, and boosting performance. Metaheuristic optimization algorithms, on the other hand, are inspired by natural phenomena, providing significant benefits related to the applicable solutions for complex optimization problems. Considering that complex optimization problems emerge across various disciplines, their successful applications are possible to be observed in tasks of classification and feature selection tasks, including diagnostic processes of certain health problems based on bio-inspiration. Sepsis continues to pose a significant threat to patient survival, particularly among individuals admitted to intensive care units from emergency departments. Traditional scoring systems, including qSOFA, SIRS, and NEWS, often fall short of delivering the precision necessary for timely and effective clinical decision-making. Methods: In this study, we introduce a novel, interpretable machine learning framework designed to predict in-hospital mortality in sepsis patients upon intensive care unit admission. Utilizing a retrospective dataset from a tertiary university hospital encompassing patient records from January 2019 to June 2024, we extracted comprehensive clinical and laboratory features. To address class imbalance and missing data, we employed the Synthetic Minority Oversampling Technique and systematic imputation methods, respectively. Our hybrid modeling approach integrates ensemble-based ML algorithms with deep learning architectures, optimized through the Red Piranha Optimization algorithm for feature selection and hyperparameter tuning. The proposed model was validated through internal cross-validation and external testing on the MIMIC-III dataset as well. Results: The proposed model demonstrates superior predictive performance over conventional scoring systems, achieving an area under the receiver operating characteristic curve of 0.96, a Brier score of 0.118, and a recall of 81. Conclusions: These results underscore the potential of AI-driven tools to enhance clinical decision-making processes in sepsis management, enabling early interventions and potentially reducing mortality rates. Full article

The 2024 cut-off low-pressure (DANA) event had a devastating impact on the province of Valencia (Spain), resulting in 227 fatalities. This extreme weather event highlighted the urgent need to enhance education on flood risk and prevention, particularly through geography lessons in schools. This paper presents a didactic experience conducted during the 2024–2025 academic year at a primary school in Alicante (Valencian Community, Spain), within the sixth-grade subject of “Natural, Social, and Cultural Environment Studies”. The initiative aimed to increase knowledge of the causes of flooding and safety measures, with a particular focus on the DANA event of 29 October 2024. Through hands-on and collaborative activities, the project sought to raise awareness of the importance of risk prevention and management. Ultimately, this educational approach aspires to foster a more resilient society, one that is better prepared to face the challenges posed by current and future climate change scenarios. Full article

The increasing consumer demand for minimally processed foods (MPFs) has highlighted the need for innovative preservation methods that ensure both safety and quality. Among promising biocontrol tools, bacteriophages—viruses that selectively destroy bacteria—have gained significant attention. This review explores the dual role of bacteriophages in the food industry. On one hand, they offer a natural, highly specific, and environmentally friendly means of controlling both pathogenic and spoilage bacteria in MPFs, contributing to improved food safety, extended shelf life, and reduced reliance on antibiotics and chemical preservatives. Their use spans primary production, bio-sanitization, and biopreservation. On the other hand, phages pose significant risks in fermentation-based industries such as dairy, where they can disrupt starter cultures and impair production. This review also examines the regulatory, technological, and safety challenges involved in phage application, including concerns about antibiotic resistance gene transfer, the presence of endotoxins, and scale-up limitations. Ultimately, this paper argues that with proper strain selection and regulation, bacteriophages can become valuable allies in sustainable food systems, despite their potential drawbacks. The application of strictly virulent bacteriophages as part of “green biotechnology” could enhance food quality and improve consumer health safety. By implementing the “farm to fork” strategy, bacteriophages may contribute to the production of health-promoting and sustainable food. Full article

Ice accumulation poses a significant hazard to aviation safety, particularly in cold weather conditions, as it can compromise aerodynamic performance, increase structural weight, and diminish lift, occasionally resulting in severe stall incidents. At present, such risks are managed through the use of energy-demanding active ice protection systems (IPSs), which operate either by inhibiting ice formation (anti-icing) or by removing existing ice (de-icing). Nonetheless, in the context of future sustainable aviation, there is a pressing need to develop IPSs with lower energy requirements. A promising approach involves hybrid IPSs that integrate conventional active systems with passive superhydrophobic or icephobic surface treatments, which are capable of preventing, delaying, or minimizing ice buildup. These systems offer the potential to substantially decrease the energy consumption and consequently the CO₂ emissions. Furthermore, in accordance with FAA regulations, active IPSs are not permitted to operate during takeoff and initial flight stages to prevent any reduction in engine thrust. These two reasons emphasize the critical importance of developing efficient coatings that, on the one hand, promote the mobility of water droplets, hereby preventing ice formation, as achieved by superhydrophobic surfaces, and on the other hand, facilitate ice detachment, as required for icephobic performance. In this context, the primary objective of the present work is to emphasize the icephobic properties of two superhydrophobic coatings. To achieve this, an extensive characterization is first conducted, including wettability, Surface Free Energy (SFE), and surface roughness, to confirm their superhydrophobic nature. This is followed by an assessment of their icephobic performance, specifically in terms of ice adhesion strength, with comparisons made against a commercial aeronautical coating. The results revealed a significant reduction in both the wettability and SFE of the developed coatings compared to the reference, along with a marked decrease in ice adhesion strength, thereby demonstrating their icephobic properties. Future activities will focus on the combination of coatings with active IPS in order to assess the energy efficiency under extensive icing conditions where both superhydrophobic and icephobic properties are required. Full article

Object detection in unmanned aerial vehicle (UAV) images poses significant challenges due to complex scale variations and class imbalance among objects. Existing methods often address these challenges separately, overlooking the intricate nature of UAV images and the potential synergy between them. In response, this paper proposes AD-Det, a novel framework employing a coherent coarse-to-fine strategy that seamlessly integrates two pivotal components: adaptive small object enhancement (ASOE) and dynamic class-balanced copy–paste (DCC). ASOE utilizes a high-resolution feature map to identify and cluster regions containing small objects. These regions are subsequently enlarged and processed by a fine-grained detector. On the other hand, DCC conducts object-level resampling by dynamically pasting tail classes around the cluster centers obtained by ASOE, maintaining a dynamic memory bank for each tail class. This approach enables AD-Det to not only extract regions with small objects for precise detection but also dynamically perform reasonable resampling for tail-class objects. Consequently, AD-Det enhances the overall detection performance by addressing the challenges of scale variations and class imbalance in UAV images through a synergistic and adaptive framework. We extensively evaluate our approach on two public datasets, i.e., VisDrone and UAVDT, and demonstrate that AD-Det significantly outperforms existing competitive alternatives. Notably, AD-Det achieves a $37.5\%$ average precision (AP) on the VisDrone dataset, surpassing its counterparts by at least $3.1\%$. Full article

At the beginning of the third millennium, human civilization faces a paradox of significant proportions: on one hand, industrial and technological growth is causing extensive environmental degradation, threatening both current and future generations. On the other hand, the acceleration of industrial and technological development is essential, requiring a profound transformation of society as the only viable solution. With the advent of the Fourth Industrial Revolution and shifts in the economy, especially regarding sustainability, the process of transformative tourism becomes crucial. Transformative tourism not only aligns with sustainable principles but also fosters a deeper connection between economic development and the preservation of natural resources, ensuring that progress benefits both humanity and the planet. The goal of this research is to identify how the key factors of Industry 4.0 can contribute to the development of sustainable and transformative tourism. The methodological approach of this study uses a systematic literature review (SLR), which allows for a detailed analysis of existing scientific papers and the identification of key trends and challenges in this field. The literature review included scientific papers published between 2013 and 2025, applying predefined criteria of relevance, quality, and focus on sustainability and digitalization in tourism. The key findings of the research indicate that digitalization and automation contribute to improving tourist experiences, optimizing destination management and reducing the ecological footprint of tourism. This research analyses how changes prompted by the Fourth Industrial Revolution can contribute to the sustainability of tourism as the fastest-growing global economic activity. The findings of this paper stem from a literature review that focuses closely on the key aspects of Industry 4.0, including digitization, automation, and the use of innovative technologies in tourism. The results indicate that the benefits arising from the Fourth Industrial Revolution include improvements in tourist experiences, the enhancement of management and marketing activities in tourism, and implications through the ecological impacts of tourism. The paper provides an overview of how the effects of Industry 4.0 are transforming tourism, enabling it to become more resilient and sustainable in the face of the challenges posed by the modern world. Full article

Faced with environmental challenges posed by traditional building materials and the management of agricultural waste, this study uses dwarf hulls, an abundant waste product in West Africa, as a natural stabilizer for earth bricks. Three mixtures were studied: soil + water (reference), soil + néré husk decoction, and soil + decoction with weekly sprinkling. The results show a significant improvement in compressive strength with the decoction. At 28 days, it increases from 0.967 MPa (reference) to 1.251 MPa with decoction and 1.360 MPa with sprinkling. At 90 days, these values reach 1.060 MPa, 1.39 MPa, and 1.502 MPa, respectively, confirming the beneficial effect of tannins and humidification. On the other hand, the tensile strength decreased from 0.10 MPa for the reference mixture to 0.08 MPa and 0.08 MPa with decoction and sprinkling. This study highlights the potential of using néré husk as a durable stabilizer. However, further research is needed, particularly on the addition of plant fibers, to improve tensile strength. Full article

We describe the quark substructure of hadrons and the equation of state of high-density neutron star matter by using the Nambu–Jona-Lasinio (NJL) model, which is an effective quark theory based on QCD. The interaction between quarks fully respects the chiral and flavor symmetries. Guided by the success of various low-energy theorems, we assume that the explicit breaking of these symmetries occurs only via the current quark masses, and all other symmetry breakings are of dynamical nature. In order to take into account the effects of the finite quark core sizes of the baryons on the equation of state, we make use of an excluded volume framework that respects thermodynamic consistency. The effects generated by the swelling quark cores generally act repulsively and lead to an increase in the pressure with increasing baryon density. On the other hand, in neutron star matter, these effects also lead to a decrease in the density window where hyperons appear because it becomes energetically more favorable to convert the faster moving nucleons into hyperons. Our quantitative analysis shows that the net effect of the excluded volume is too small to solve the long-standing “hyperon puzzle”, which is posed by the large observed masses of neutron stars. Thus, the puzzle persists in a relativistic effective quark theory which takes into account the short-range repulsion between baryons caused by their finite and swelling quark core sizes in a phenomenological way. Full article

The rapid growth of the dairy industry has resulted in a significant increase in the generation of effluents, which are characterized by a high organic content that poses environmental challenges. In alignment with sustainable practices and the principles of the circular economy, this study investigates the valorization of cheese whey (CW) effluents through the cultivation of the microalga Dunaliella tertiolecta under mixotrophic conditions. The research aims to utilize cheese whey effluents as a supplemental growth medium to enhance the production of algal biomass and extracellular polymeric substances (EPSs). The results reveal that CW facilitated a 37% improvement in D. tertiolecta growth and led to an approximately eight times greater biomass productivity compared to under photoautotrophic conditions, while the EPS production increased by 30%. Chemical and techno-functional analyses of the microalgal biomass and EPSs suggest promising applications as natural product additives for the food industry. Biomass derived from photoautotrophic culture demonstrated greater antioxidant activity and total polyphenols content. Additionally, the lipid profile revealed 16 distinct fatty acids. On the other hand, biomass from the mixotrophic culture exhibited higher protein levels and eight fatty acids, indicating the influence of the cultivation mode on the biochemical composition. Regarding the EPSs, mixotrophic cultivation resulted in elevated antioxidant activity and total polyphenols content, as well as higher protein and sugar levels. Furthermore, the EPSs produced under mixotrophic conditions exhibited superior techno-functional properties compared to those of the photoautotrophic culture, making them ideal candidates for use as alternative natural food additives. Full article

Accurate identification of growth and development stages is critical for orthodontic diagnosis, treatment planning, and post-treatment retention. While hand–wrist radiographs are the traditional gold standard, the associated radiation exposure necessitates alternative imaging methods. Lateral cephalometric radiographs, particularly the maturation stages of the second, third, and fourth cervical vertebrae (C2, C3, and C4), have emerged as a promising alternative. However, the nonlinear dynamics of these images pose significant challenges for reliable detection. This study presents a novel approach that integrates chaotic functional connectivity (FC) matrices and fractal dimension analysis to address these challenges. The fractal dimensions of C2, C3, and C4 vertebrae were calculated from 945 lateral cephalometric radiographs using three methods: fast Fourier transform (FFT), box counting, and a pre-processed FFT variant. These results were used to construct chaotic FC matrices based on correlations between the calculated fractal dimensions. To effectively model the nonlinear dynamics, chaotic maps were generated, representing a significant advance over traditional methods. Feature selection was performed using a wrapper-based approach combining k-nearest neighbors (kNN) and the Puma optimization algorithm, which efficiently handles the chaotic and computationally complex nature of cervical vertebrae images. This selection minimized the number of features while maintaining high classification performance. The resulting AI-driven model was validated with 10-fold cross-validation and demonstrated high accuracy in identifying growth stages. Our results highlight the effectiveness of integrating chaotic FC matrices and AI in orthodontic practice. The proposed model, with its low computational complexity, successfully handles the nonlinear dynamics in C2, C3, and C4 vertebral images, enabling accurate detection of growth and developmental stages. This work represents a significant step in the detection of growth and development stages and provides a practical and effective solution for future orthodontic diagnosis. Full article