Search Results (8,121)

This article reports on a comparative case study that examined the ground rules used to facilitate a dialogic space in two discrete and diverse research studies: Year 5 & 6 children learning to code with ScratchMaths as part of their mathematics programmes, and crop farmers in rural east Africa developing their practice through various communications. The intention was to see if there were common actions or principles important for the establishment of ground rules in dialogic spaces in general. Understanding the nature of dialogic space has become increasingly important in many areas of education. STEM subjects, particularly when integrated, frequently involve collaborative interaction, and utilise a dialogical approach. Some initial aspects of ground rules were collaboratively identified, with both studies then independently analysed to identify emerging themes related to these ground rules. Several key elements emerged: developing the processes for interaction and communication; developing trust between participants; developing respectful dialogue; teacher roles; and facilitating collaborative work and the co-construction of meaning. The comparative case study suggested that these were important for other education work when establishing dialogic space. Full article

Understanding mechanisms of asphalt in the process of natural aging is crucial for predicting its long-term durability and optimizing performance under diverse environmental conditions. Despite its importance, the microstructural and micromechanical changes induced by natural aging remain poorly understood, particularly under varying climatic influences. This study addresses this gap by analyzing the effects of natural aging on asphalt’s microscopic properties and identifying key indicators that govern its degradation. Asphalt samples were subjected to natural aging across five climatically distinct regions over 6, 12, and 18 months. Atomic force microscopy (AFM) was employed to characterize surface roughness, adhesion forces, and DMT modulus, while correlation analysis and principal component analysis (PCA) were used to identify relationships among micromechanical indicators and streamline the dataset. The results reveal that natural aging induces irreversible transformations in asphalt’s microstructure, driven by the combined effects of temperature, UV radiation, humidity, and oxygen. These processes promote the evolution of “Bee structures,” increase surface roughness, and accelerate phase separation, alongside chemical modifications such as oxidation and polymerization, leading to progressive material hardening and stiffness. Significant regional and temporal variations in adhesion forces and DMT modulus were observed, reflecting the cumulative impact of environmental factors on asphalt’s aging dynamics. Correlation analysis demonstrated strong associations between surface roughness and “Bee structure” area, while mechanical properties such as stiffness and adhesion were largely decoupled from morphological features. Environmental factors interact in complex ways to drive asphalt aging. Humidity enhances adhesion and stiffness via water-induced capillary forces, while temperature reduces surface roughness and adhesion through molecular reorganization. UV radiation accelerates oxidative degradation, promoting surface erosion and stiffness loss, while altitude modulates these dynamics by influencing temperature and UV exposure. Full article

Major depressive disorder (MDD) is a leading cause of global morbidity and mortality. Although pharmacological treatments are widely used, their effects are often limited, and nearly half of patients show resistance to current antidepressants, including those unresponsive to all available therapies. These challenges highlight the need to better understand the neurobiological mechanisms driving MDD and to develop novel therapeutic strategies, especially those involving natural compounds with multitarget actions. Baicalin, a bioactive flavonoid from Scutellaria baicalensis, exhibits antioxidant, anti-inflammatory, and neuroprotective properties and has recently gained attention for its potential to improve cognitive deficits and mood disorders. In this study, we investigated baicalin’s antidepressant potential and its underlying mechanisms across multiple experimental levels. We found that oral administration of baicalin produced antidepressant-like effects in both naïve mice and those subjected to chronic restraint stress (CRS). CRS impaired hippocampal long-term potentiation (LTP), whereas baicalin restored these synaptic deficits. Importantly, intra-dorsal hippocampal microinjection of the TrkB receptor antagonist ANA-12 abolished baicalin’s antidepressant effects, indicating the involvement of BDNF–TrkB signaling. Baicalin also reduced reactive oxygen species (ROS)/H₂O₂ production in a BDNF-associated manner, demonstrating clear antioxidant activity. Molecular docking further suggested that baicalin binds more effectively to the TrkB receptor than ANA-12, supporting its capacity to activate TrkB-mediated signaling. By integrating in vivo, ex vivo, in vitro, and in silico approaches, our study shows that baicalin exerts robust antioxidant in vitro and antidepressant effects in vivo. These benefits are primarily mediated through activation of BDNF–TrkB signaling, leading to reduced ROS/H₂O₂ accumulation and alleviation of CRS-induced depression-like behaviors. Full article

This study explores the factors that influence Gen Z consumers’ green purchasing behavior, addressing a gap in current research by combining the Theory of Planned Behavior, the Theory of Consumption Values, and Generational Theory, and applying them to the touristic accommodation context. Based on a quantitative survey of Gen Z tourists from Spain, Norway, and Lithuania, the study examined traditional constructs of the Theory of Planned Behavior alongside subjective knowledge, environmental consciousness, perceived value, and green trust. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results indicate a significant role for price-based functional value and emotional value in shaping Gen Z’s attitudes toward sustainable accommodation. Furthermore, subjective knowledge and environmental consciousness strengthen green trust, which in turn contributes to a more positive attitude toward sustainable touristic options. Attitude, subjective norms, and perceived behavioral control significantly predict behavioral intention, while both perceived behavioral control and behavioral intention directly influence actual purchasing behavior. The findings suggest that tourism marketers should focus on enhancing price-related and emotionally meaningful value propositions, while also fostering trust through clear communication of environmental performance. Overall, the study offers a comprehensive understanding of the drivers behind Gen Z’s sustainable accommodation choices and provides practical implications for promoting environmentally responsible tourism. Full article

Understanding consciousness requires bridging theoretical models and clinically measurable brain dynamics. This review integrates three complementary frameworks that converge on a dynamical view of conscious processing: continuous formulations of Integrated Information Theory (IIT), attractor-landscape modeling of brain-state transitions, and perturbational complexity metrics from transcranial magnetic stimulation combined with electroencephalography (TMS-EEG). Continuous-time IIT formalizes how integrated information evolves across temporal hierarchies, while dynamical-systems approaches show that consciousness emerges near criticality, where metastable attractors enable flexible transitions between partially synchronized states. Perturbational-complexity indices capture these properties empirically, quantifying the brain’s capacity for integration and differentiation even without behavioral responsiveness. Across anesthesia, disorders of consciousness, epilepsy, and neurodegeneration, TMS-EEG biomarkers reveal reduced complexity and altered synchronization consistent with structural and functional disconnection. Integrating multimodal data—diffusion MRI, fMRI, EEG, and causal perturbations—is consistent with individualized modeling of consciousness-related dynamics. Standardized protocols, mechanistically interpretable machine learning, and longitudinal validation are essential for clinical translation. By uniting information-theoretic, dynamical, and empirical perspectives, this framework offers a reproducible foundation for consciousness biomarkers that mechanistically link brain dynamics to subjective experience, paving the way for precision applications in neurology, psychiatry, and anesthesia. Full article

Background: Suicide represents a challenging societal question. There is a correlation between multi-comorbidity (mental, addictive, social, and physical) and excess suicide. Aside from recognizing this correlation, our understanding of employment’s impact on psychache in adults with the multi-comorbidity of schizophrenia and multi-substance use disorders remains incomplete. Methods: This individual survey of 88 inpatients (with multi-comorbidity) examined the hypothetical impact of preadmission employment on psychache intensity. Fifty of them (56.8%) reported being employed prior to admission, while thirty-eight of them (43.2%) reported they were not. Written informed consent was obtained from all subjects involved in this survey before inclusion. Results: The findings demonstrated that the connection between general self-efficacy and current psychache intensity is dependent on the subjects’ preadmission employment status, with a stronger negative correlation observed in subjects who worked prior to admission (p < 0.001). Employment status provided the moderator variable in the association between general self-efficacy and current psychache intensity (p < 0.001). Conclusions: These measures are crucial for balancing work and psychache as well as translating the findings regarding the social nature of health and well-being into real-world application of suicide prevention in individuals with multi-comorbidity. Full article

Background/Objectives: Lower limb amputation (LLA) negatively affects the physical and psychological health of individuals, leading to a lower quality of life and sedentary lifestyle. The objective of this scoping review is to search for evidence regarding physical activity interventions in individuals with LLA, investigating improvements in specific outcomes related to quality of life and performance. Methods: PRISMA guidelines—extension for scoping reviews—were used to structure the study. The research was conducted between 26 July 2023 and 30 September 2023; it was structured by defining two PICO questions (P = amputation, I = physical exercise, O1 = quality of life, and O2 = performance) through Pubmed, Cochrane, and Pedro databases. The study included subjects with LLA of any etiology, in prosthetic or pre-prosthetic phase, practicing non-competitive physical activity. The results were then subjected to both qualitative and quantitative analysis. Results: Of the 615 studies identified, 18 were included in the review. They consisted of 6 systematic reviews (SR), 5 RCTs, 4 case–control studies, 1 case report (CR), and 2 cross-sectional (CS). Physical activity (PA) interventions were extremely heterogeneous and were, therefore, categorized into 6 modalities: surveys were the most reported strategies (57%), followed by personalized training (23%), strength training (13%), endurance training (13%), combined training (2%), and gait training (5%). Due to the heterogeneity of the studies, the variety of interventions proposed and the different outcomes registered, there is no evidence that one approach is more effective than another, while each group showed benefits on different specific outcomes. In total, five outcome categories were identified: quality of life was the most frequently analysed (42%), followed by cardiovascular fitness (20%), muscular fitness (14%), gait parameters (13%), functionality and disability (11%). Conclusions: PA represents a valuable strategy for improving performance and quality of life in individuals with LLA, offering a variety of interventions. Although there is no evidence that one strategy is better than the others, each activity has proven to be effective on specific outcomes, therefore, the choice must depend on the patient’s necessities. The preferred option should be the personalization of the training according to individual needs, coupled with long-term planning and remote monitoring. Creating meeting places and supporting occasions for sports activities could be a valid option. Further research could help to clarify the benefits of such interventions and enhance the understanding of how to optimize the management of LLA patients. Full article

Plant-based meat alternatives (PBMAs) are gaining increasing attention due to their potential role as substitutes for traditional meat products, driven by sustainability and health concerns related to animal production and consumption. Therefore, investigating and understanding consumer acceptance of less common PBMAs remains crucial. In this context, this research explored sensory expectations and actual experiences of a plant-based hotdog compared to a pork hotdog in a US sample. Using a within-subject design, participants (n = 88) evaluated both products before and after tasting, assessing overall liking, willingness to buy (WTB), and key sensory attributes. Furthermore, Check-All-That-Apply (CATA) batteries were used to explore product descriptors and situational appropriateness for consumption, while open-ended questions were employed to examine what consumers liked and disliked the most about the products in more detail. Results revealed no significant differences in expected liking between the two products before tasting. However, after tasting, the pork hotdog received significantly higher scores for both overall liking and WTB compared to the plant-based hotdog. Despite the plant-based product being associated with situations related to health and sustainability, it did not lead to the same appealing hedonic experience as the animal-based product. In addition, both penalty-lift analysis and text mining of the open-ended responses confirmed that consumers seek meaty characteristics in both animal- and plant-based hotdogs (e.g., “I don’t like how light the meat is” or “would like a more meat flavor”). This research provides valuable implications for policymakers and the food industry in terms of aligning strategies with consumers’ preferences and needs, supporting efforts to reduce red meat consumption and promote healthier, more sustainable dietary choices. Full article

Understanding the long-term dynamics of global tea production is essential for assessing supply stability, climate sensitivity, and producer competitiveness. This study examines annual tea production data for major producing countries—China, India, Kenya, Sri Lanka, Türkiye, Vietnam, and other producer groups—over the period 1961–2023 and provides production forecasts for 2024–2028 using country-specific ARIMA models. Unlike most existing studies focusing on single countries or short-term horizons, this research offers a unified multi-country and long-term comparative framework that integrates time-series forecasting with market concentration indicators. The results reveal pronounced cross-country heterogeneity in production behavior, with China exhibiting strong structural growth, while other producers display more moderate or climate-sensitive patterns. Forecasts suggest a continued increase in global tea production toward 2028, although projections are subject to uncertainty, as reflected by model-based confidence intervals. Overall, the study contributes robust, statistically validated insights to support evidence-based strategies for sustainable tea supply and international market planning. Forecasts suggest a continued increase in global tea production toward 2028, although projections are subject to uncertainty, as reflected by model-based confidence intervals. These forecasts highlight a robust upward trend in global tea supply due to both technological advancements and market expansion. Full article

Artificial intelligence (AI) is now embedded across many aspects of healthcare, yet most implementations remain fragmented, task-specific, and layered onto legacy workflows. This paper does not review AI applications in healthcare per se; instead, it examines what an AI-first healthcare system would look like, one in which AI functions as a foundational organizing principle of care delivery rather than an adjunct technology. We synthesize evidence across ambulatory, inpatient, diagnostic, post-acute, and population health settings to assess where AI capabilities are sufficiently mature to support system-level integration and where critical gaps remain. Across domains, the literature demonstrates strong performance for narrowly defined tasks such as imaging interpretation, documentation support, predictive surveillance, and remote monitoring. However, evidence for longitudinal orchestration, cross-setting integration, and sustained impact on outcomes, costs, and equity remains limited. Key barriers include data fragmentation, workflow misalignment, algorithmic bias, insufficient governance, and lack of prospective, multi-site evaluations. We argue that advancing toward AI-first healthcare requires shifting evaluation from accuracy-centric metrics to system-level outcomes, emphasizing human-enabled AI, interoperability, continuous learning, and equity-aware design. Using hypertension management and patient journey exemplars, we illustrate how AI-first systems can enable proactive risk stratification, coordinated intervention, and continuous support across the care continuum. We further outline architectural and governance requirements, including cloud-enabled infrastructure, interoperability, operational machine learning practices, and accountability frameworks—necessary to operationalize AI-first care safely and at scale, subject to prospective validation, regulatory oversight, and post-deployment surveillance. This review contributes a system-level framework for understanding AI-first healthcare, identifies priority research and implementation gaps, and offers practical considerations for clinicians, health systems, researchers, and policymakers. By reframing AI as infrastructure rather than isolated tools, the AI-first approach provides a pathway toward more proactive, coordinated, and equitable healthcare delivery while preserving the central role of human judgment and trust. Full article

Aluminum, the primary structural material used in spacecraft, operates in low Earth orbit (LEO). It is subjected to high-energy electron irradiation with energies ranging from 0.1 to 10 MeV, which produces significant irradiation damage. Understanding the characteristics of irradiation defects with crystallographic orientations is crucial for analyzing the failure of spacecraft components and for developing aerospace materials with improved irradiation resistance. In this study, pure aluminum was irradiated in situ at room temperature using 200 kV transmission electron microscopy. The irradiation defects were comparatively analyzed for four crystallographic orientations, focusing on the size, density, and interstitial content of <111> and <110> dislocation loops. For all four irradiation directions, the interstitial atom density (IAD) within <111> loops is significantly higher than that in <110> loops. Notably, under [110]-direction irradiation, IAD in <111> loops is approximately 55 times that in <110> loops. This phenomenon is attributed to the one-dimensional migration of <110> loops. Among the four irradiation directions, the total IAD in the two types of loops decreases in the order: [110] > [111] > [310] > [100]. The threshold displacement energy (E_d) of aluminum at room temperature is inferred to follow the relationship: [110] < [111] < [310] < [100]. Full article

In the context of climate change and the general trend toward a healthy lifestyle, reducing the alcoholic strength of wines poses a major challenge for producers. In order to obtain quality low-alcohol wines (LAWs), Muscat Ottonel conventional wine was subjected to reverse osmosis followed by vacuum concentration of the hydroalcoholic permeate (ROVC) or to two-step vacuum concentration (TSVC), with the recovery of aromas as the first alcoholic fraction (F1). Beverages with alcoholic concentrations of 3.50, 5.50, and 8.50% vol. were obtained, with compositional characteristics and sensory properties varying significantly with alcoholic strength and dealcoholization technique applied. ROVC produced wines with organic acids, volatile constituents, extract, and color intensity decreasing progressively with the reduction in alcohol concentration. At similar alcohol concentration, TSVC LAW showed a significantly higher phenolic content, antioxidant activity, volatile compounds (including esters and terpenes), and overall structural balance, maintaining better the typicity of wines. In both processes, reducing alcohol below 5.50% vol. significantly affected the quality and acceptability of the final product. Hierarchical cluster analysis indicated that TSVC LAWs were statistically closer to the conventional wine (control). These findings improve the understanding of how dealcoholization technologies affect the composition of wine, improving product quality, sustainability, and operational efficiency. Full article

Background: Adult females with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) are frequently underdiagnosed due to gender bias, overlapping symptoms, and limited awareness among healthcare professionals. The scarcity of research on this subject—particularly in the UK context—underscores the need for further investigation. Accordingly, the aim of this study was to explore the lived experiences of adult females receiving a late diagnosis of ASD and/or ADHD and to identify key barriers within the UK diagnostic pathway. This study addresses a critical knowledge gap by examining the factors contributing to delayed diagnosis within the United Kingdom. Study Design and Method: The study employed a qualitative approach, utilising an anonymous online questionnaire survey comprising nine open-ended questions. Responses were obtained from 52 UK-based females aged 35–65 years who had either received or were awaiting a diagnosis of ASD and/or ADHD. Data were analysed thematically within a constructivist framework. Findings: The analysis revealed three overarching themes: (i) limited understanding and lack of empathy among healthcare professionals, (ii) insufficient post-diagnostic support, with most participants reporting no follow-up care, and (iii) a complex, protracted diagnostic process, often involving waiting periods exceeding three years. Gender bias and frequent misdiagnosis were recurrent issues, contributing to significant psychological distress. These findings underscore the need for systemic reforms and align closely with gaps identified in the existing literature. Conclusions: The findings emphasise the urgent need for gender-sensitive diagnostic frameworks, enhanced professional training, and a person-centred approach to care. Key recommendations include shortening diagnostic waiting times, strengthening healthcare professionals’ knowledge base, and ensuring equitable and consistent post-diagnostic support. Full article

Pleurotus pulmonarius is a high-value, commercially cultivated edible fungus whose primordium formation is a critical phase for yield and commercial value. To better understand the developmental processes of P. pulmonarius, samples from four key developmental stages were collected and subjected to transcriptome analysis. A total of 6530 DEGs were identified, including 50 transcription factors from 10 families. Among these, the PpZCP11 gene, encoding a Zn₂Cys₆ transcription factor, was found to be specifically highly expressed during the primordium stage. We cloned PpZCP11 gene and confirmed its nuclear localization. The OE-PpZCP11 strains produced abundant primordia, while primordium formation in the RNAi-PpZCP11 strains was severely suppressed. Moreover, RNA-seq and yeast-one-hybrid analysis suggested that PpZCP11 may regulate cell wall synthesis. These findings indicate that the PpZCP11 transcription factor acts as a positive regulator of primordium formation by regulating the expression of cell wall-related genes. This study provides a theoretical reference for elucidating the molecular mechanism underlying primordium formation in P. pulmonarius. Full article

Wildfires profoundly impact carbon cycles, climate, and human societies. However, a comprehensive understanding of the long-term spatiotemporal characteristics and influencing factors of global wildfires remains limited. This study analyzes the spatiotemporal patterns and influencing factors of wildfires from 1982 to 2018 using a global satellite-derived burned area (BA) product. We classified fire-prone regions into four types based on climate: Tropical dry season (Tr-ds), Arid fuel-limited (Ar-fl), Boreal hot season (Bo-hs), and Temperate dry and hot season (Te-dhs). Major fire hotspots include Africa, northern Australia, South America’s Brazilian highlands, the Indochina Peninsula, and Central Asia. The global multi-year average BA is 4.59 × 10⁸ ha yr⁻¹, with Africa (3.04 × 10⁸ ha yr⁻¹) and northern Australia (2.83 × 10⁷ ha yr⁻¹) being the most affected. Fire activity peaks annually in July–September and December–January. From 1982 to 2018, both the global and sub-regional BA show significant increasing trends, except northern and temperate areas, though reduced burn-down areas from shorter periods have been reported during the MODIS era. At both the global scale and in the Tr-ds region, wildfire activity is strongly associated with hot and dry conditions in combination with abundant fuel availability. Fire activity in the Ar-fl region is mainly constrained by fuel availability. Surface dryness plays a dominant role in fire activity in the Bo-hs. In contrast, fire activity in the Te-dhs region shows no clear pattern. The influence of different factors on the BA is subject to threshold effects. These findings contribute to a deeper understanding of long-term wildfire dynamics across different regions globally. Full article