Search Results (341)

This contribution explores the role of reflective practice and performative methodologies in the professional development of support teachers, framing reflectivity as a complex and articulated form of thinking that goes beyond intuitive reflection. Drawing on theories of transformative learning and practice-based research, the paper argues that performative approaches—grounded in embodied, emotional, and narrative experience—can effectively foster teachers’ critical awareness, professional identity construction, and capacity for inclusive educational action. The study presents a teacher training experience implemented within the Specialization Course for Support Teaching Activities at Link Campus University, involving a 20-h workshop attended by 200 lower secondary school teachers. Centered on performance art practices, the workshop aimed to promote reflective processes related to themes of exclusion and inclusion through bodily engagement, collective meaning-making, and non-verbal communication. Participants were actively involved in designing and performing activities, thus positioning themselves as protagonists of their own learning trajectories. Data collected through pre- and post-intervention questionnaires highlight participants’ positive perceptions of the experience and its transferability to school contexts. Findings suggest that performative methodologies support emotional sharing, enhance group cohesion, and contribute to the creation of a supportive classroom climate, while also strengthening teachers’ reflective and transformative capacities. The paper concludes by emphasizing the pedagogical value of performative practices as tools for fostering inclusive, reflective, and experience-based teacher education. Full article

Fishways play a critical role in restoring river connectivity and conserving fishery resources, yet their efficiency is often limited by mismatches between hydraulic conditions and species-specific behavioral traits. To quantify the upstream migration behavior of fish under the combined influence of flow heterogeneity and schooling effects, this study examined the endangered species L. elongata in the Yangtze River Basin. Volitional swimming behavior was tested in an open-channel flume under three spatially heterogeneous flow regimes (I: Low–Moderate–High; II: High–Moderate–Low; III: Moderate–High–Low). A video monitoring system recorded the upstream movement of solitary fish and three-individual schools. Swimming trajectories, upstream migration time, preferred flow velocities, and schooling metrics—including nearest neighbor distance (NND) and mean pairwise distance (MPD)—were analyzed. Linear mixed-effects models were employed to account for repeated measures and individual variability. Results showed that schooling behavior significantly enhanced upstream migration efficiency: schooling fish arrived at the target area on average 8.93 s earlier than solitary individuals (p < 0.01), while flow condition alone had no detectable effect on arrival time. L. elongata consistently preferred low-velocity zones (0.20–0.50 m/s) and avoided high-velocity regions (0.75–1.25 m/s), with meandering upstream trajectories predominating. NND showed no significant differences across flow conditions (p > 0.05), indicating stable schooling cohesion. However, MPD increased significantly under Flow III compared to Flows I and II (p < 0.01), suggesting that higher flow heterogeneity leads to more dispersed group spacing while overall cohesion is maintained. Distinct movement strategies were observed: solitary fish predominantly utilized boundary regions as hydraulic refuges (wall-following: 63.8–80.5%), whereas schools exhibited greater spatial exploration and reduced wall-following. These findings demonstrate that schooling enhances migration efficiency while preserving a cohesive group structure and that flow heterogeneity influences within-group spatial organization. To optimize fishway performance for L. elongata, we recommend maintaining flow velocities within 0.20–0.50 m/s. This study provides scientific guidance for hydraulic regulation in fishway design and habitat restoration, emphasizing the combined effects of flow heterogeneity and schooling behavior on migration performance. Full article

This paper examines economic and institutional convergence between EU Core, EU New, and Western Balkan countries over the period 2004–2023 using a comprehensive panel dataset and multiple convergence frameworks. Evidence of absolute β-convergence is found, although at a slow pace, while conditional specifications show that structural and institutional factors explain growth differences; institutional quality appears to affect growth primarily through direct effects rather than through significant interaction-based β-convergence. A Principal Component Analysis-based Institutional Index (PC1) explains 90% of the variance in institutional quality, highlighting its role in shaping cross-country growth differentials rather than directly influencing convergence speed. Group-specific models reveal heterogeneous convergence paths across European regions. EU Core economies exhibit relatively stable convergence patterns, reflecting their proximity to steady-state income levels. In contrast, EU New and Cohesion Economies do not display statistically significant β-convergence, suggesting that catch-up processes are uneven and not uniformly driven by initial income differences. Western Balkan economies show weak and limited convergence patterns, reflecting persistent structural and institutional constraints. Robustness tests (FE/RE, Hausman, VIF, Breusch–Pagan, residual diagnostics) confirm the validity of the results. Findings suggest an important role of institutional quality in supporting long-term growth and the accession process of the Western Balkans. Policy implications highlight the importance of governance reforms, human capital development, and EU integration mechanisms in accelerating convergence. Full article

With advancements in Earth observation capabilities, the demand for large-scale mapping using remote sensing images has increased significantly. However, selecting an optimal image set for the area of interest (AOI) from a large collection of remote sensing images remains challenging. On the one hand, it is crucial to select images with minimal redundancy and low cloud cover to enhance production efficiency and the effective coverage of mapping products. On the other hand, adjacent selected images should transition naturally so that the resulting mapping products appear visually cohesive. Unfortunately, most existing remote sensing image selection algorithms focus only on the former, with little attention to visual consistency. Meanwhile, images from the same swath inherently offer advantages in both redundancy reduction and visual consistency. However, a larger coverage area also carries the potential for greater variation in cloud cover, and cloud distribution within a swath can be highly complex. Managing the relationships among swaths, images, and cloud cover is also challenging. To address these issues, this paper proposes a novel image selection model, SwathSel. Candidate images are grouped through a composite grouping strategy based on swaths, cloud cover, and topological connectivity, thereby expanding the fundamental unit for image selection from individual scenes to connected image subsets. A dynamic adjustment mechanism is introduced to enhance grouping flexibility. Additionally, local and global swath consistency constraints are designed to strengthen visual consistency among images, and a subset evaluation module is used to comprehensively assess swath consistency, coverage, cloud cover, and metadata information. Through a greedy strategy combined with a rapid refinement technique, the final selected image set is obtained. Experiments were conducted on four datasets, and four quantitative metrics were designed to evaluate the visual consistency of the results. Compared with baseline models, SwathSel achieves lower redundancy and cloud cover while delivering superior visual consistency. Full article

Contemporary European societies face overlapping societal challenges—ecological degradation, immigration pressures, and widening economic inequality—which generate a pervasive climate of uncertainty affecting citizens’ perceptions of their own life conditions. This study investigates how social pessimism, conceptualised as a multidimensional orientation reflecting perceived threats across environmental, migratory, and distributive domains, relates to subjective financial insecurity at the individual level. Drawing on harmonised cross-national data from the CRONOS-II panel (N = 8993), covering eleven European countries, we construct a composite pessimism index and analyse its association with perceived financial strain using multivariate and multilevel regression models. Results demonstrate that individuals who express greater societal pessimism report significantly higher levels of financial insecurity, even after controlling for income, education, employment status, and country-level heterogeneity. This relationship is moderated by socioeconomic position; specifically, the pessimism–insecurity link is strongest among lower-income and less-educated groups, suggesting that material precarity and anticipatory anxiety compound one another. Cross-national analysis reveals substantial variation in effect magnitude, with the strongest associations observed in Hungary, Portugal, and the Czech Republic, and the weakest in Slovenia and Iceland. These findings contribute to the interdisciplinary understanding of how macro-level societal concerns permeate individual wellbeing, demonstrating that subjective economic vulnerability is shaped not only by objective circumstances but also by the broader socio-political climate in which citizens interpret their life situations. The results underscore the need for policies that address both material conditions and the affective dimensions of societal uncertainty in order to strengthen social cohesion and reduce perceived economic risk. Theoretically, we frame social pessimism as a formative composite capturing perceived threat to societal stability, offering an integrative perspective on how structurally distinct societal concerns converge to shape economic subjectivities. Full article

Background/Objectives: In recent years, research on psychosis has increasingly focused on prevention, aiming to implement early interventions that mitigate or reduce its impact. Within this framework, the analysis of linguistic markers in individuals with at-risk mental states (ARMS) has proven valuable for identifying those at risk and predicting psychosis onset. Artificial intelligence tools, particularly natural language processing (NLP), have emerged as effective resources for detecting these language-based indicators. This study aims to synthesize the existing scientific evidence on linguistic markers analyzed through NLP techniques in individuals with ARMS. Methods: A systematic review following the PRISMA 2020 protocol was conducted. Three databases (PubMed, PsycInfo, and Scopus) were searched for published articles from their inception to October 2025. Rayyan software was used to manage references and article downloads. Out of ninety initial search results, fifteen studies involving 1313 participants from diverse groups were included in the review. Results: The findings indicated that alterations in semantic coherence, syntactic complexity, referential cohesion, and speech/content poverty differentiated ARMS individuals from healthy controls. Several of these markers, analyzed with NLP methods, predicted the onset of psychosis with accuracy levels ranging from 79% to 100%, although these findings should be interpreted with caution due to the significant methodological heterogeneity and variability in sample sizes across the included studies. Conclusions: NLP techniques offer a powerful approach for detecting language alterations that distinguish ARMS individuals and provide meaningful predictions of psychosis onset, highlighting their potential as a complement to traditional clinical assessments for early identification and prevention. Full article

This study investigates the inhibitory effects of alkali metal chlorides lithium chloride, sodium chloride and potassium chloride (LiCl, NaCl, and KCl) on sodium dodecyl sulfate (SDS) foams, focusing on the transition from interfacial to bulk-driven destabilization mechanisms. The research demonstrates that foam collapse at high electrolyte concentrations is governed by a massive increase in bulk cohesive pressure and specific ion-pairing (SIP), which leads to interfacial dehydration and the mechanical decoupling of the surface from the bulk phase. It is shown that while surface adsorption reaches a plateau, the thermodynamic state of the solvent becomes the primary driver for film drainage. The results indicate that KCl acts as the most potent defoamer due to its optimal matching of water affinities with the surfactant head groups. These findings provide a new theoretical framework for understanding foam stability in concentrated electrolytic environments, emphasizing the role of bulk cohesive stress over traditional interfacial elasticity. Full article

Cultivation substrate critically affects the quality of Tremella fuciformis. Five substrates, including cottonseed hulls (MZKs), Machilus pauhoi Kanehira sawdust (BNM), lotus seed hulls (LZKs), Corethrodendron scoparium sawdust (HB), and palm fiber (ZL), were evaluated for their effects on agronomic traits, nutritional composition, texture, and taste characteristics. Untargeted metabolomics was applied to elucidate substrate-associated metabolic variations, and polysaccharide monosaccharide composition was quantitatively analyzed. The results showed that the BNM group exhibited the highest fresh weight, whereas the LZK group presented the highest dry weight and crude polysaccharide content. The ZL group displayed the greatest ear piece thickness and fruiting body elevation. Higher protein contents were observed in the ZL and LZK groups, with no differences in crude fiber content. Texture analysis indicated that hardness was highest in the LZK group, whereas the MZK group showed better springiness, cohesiveness, and chewiness. Regarding taste characteristics, the MZK group exhibited the strongest sweetness, the LZK group showed a markedly higher bitterness, and umami levels were comparable across all groups. Metabolomic analysis revealed that substrate-induced variations in amino acids, saccharides, and taste-related metabolites were significantly associated with nutritional quality and taste attributes of T. fuciformis. Polysaccharides of fruiting bodies cultivated on the five substrates consisted of six monosaccharides, with composition ratios similar to those of spore extracellular polysaccharides; among them, differences in glucuronic acid (GlcA) proportion represented a key indicator distinguishing fruiting body polysaccharides from spore polysaccharides. This study revealed the metabolic basis and polysaccharide composition underlying substrate-dependent quality of T. fuciformis, supporting substrate optimization for high-quality production. Full article

In this study, the effect of temperature on thermal-assisted glass delamination was investigated using two treatment conditions differing in the set temperature of the process (100 °C vs. 140 °C). Thermogravimetric Analysis (TGA) confirmed that ethylene-vinyl acetate (EVA) remains thermally stable up to about 280 °C, with degradation onset near 300 °C, ensuring that both treatments operate below decomposition. Differential Scanning Calorimetry (DSC) analysis identified an endothermic transition attributable to the melting of crystalline regions in EVA within the thermal range of 35–65 °C, indicating enhanced polymer chain mobility at elevated temperatures. This endothermic transition corresponds to the melting of polyethylene crystallites within the EVA copolymer and should not be interpreted as a glass transition, since the Tg of EVA is typically located at approximately −30 to −35 °C. Fourier Transform Infrared (FTIR) analysis verified preservation of ester functional groups, confirming the absence of chemical degradation. The morphological analysis performed via Scanning Electron Microscopy (SEM) revealed a clear temperature-dependent morphology of EVA after thermal-assisted delamination. At 140 °C, enhanced polymer softening and viscous flow led to smoother surfaces and more uniform interfacial separation, whereas at 100 °C, limited mobility resulted in heterogeneous, fragmented residues and predominantly cohesive failure. These results highlight that optimizing temperature is key to balancing effective delamination with residue minimization, supporting more sustainable PV recycling. Full article

This qualitative study analyzes the perceived effects of the Quiero Mi Barrio—I love my neighborhood—(PQMB) urban regeneration program on the physical and social environments and residents’ quality of life in two deprived neighborhoods in Temuco, Chile, where PQMB was implemented in 2007 and 2015, using a phenomenological approach and a gender perspective. PQMB is a state-led program that combines improvements in urban infrastructure with participatory processes aimed at strengthening community life. Data were collected through interviews, focus groups, and non-participant observations. The findings indicate improvements in public spaces, increased social interaction, and enhanced community cohesion, although these effects were unevenly distributed. Women and older adults experienced greater benefits due to higher participation and leadership in neighborhood organizations, while younger residents’ involvement was more limited and focused on the use of sports facilities. Differences between neighborhoods highlight the importance of time and institutional continuity in maintaining program-related effects. The study shows that changes in the built environment interact with participation patterns and community organization, shaping how residents experience improvements in quality of life. However, the sustainability of these effects depends on long-term institutional support and communities’ capacity to sustain collective action and influence local decision-making beyond the formal closure of interventions. Full article

Community detection is a key task in the analysis of complex networks, particularly in social network analysis, where uncovering cohesive and well-separated groups is essential for understanding structural organization and interaction patterns. Many existing centroid-based community detection methods rely primarily on node degree for centroid selection, which often leads to centroid crowding and insufficient spatial separation among communities. To address these limitations, this paper proposes Degree–Distance Centroid–Community Detection with Influential Nodes (DDC-CDIN), a distance-driven and influence-aware community detection framework. In the proposed approach, nodes are first ranked according to an Enhanced Degree Centrality measure that incorporates degree information, neighbourhood structure, and local clustering characteristics to identify structurally influential nodes. Centroids are then selected iteratively from the top-ranked influential nodes by maximizing shortest-path distances, ensuring that the chosen centroids are both representative and well dispersed within the network. Once the centroids are determined, the remaining nodes are assigned to communities based on the minimum geodesic distance, yielding compact, clearly separated clusters. Extensive experiments across multiple real-world networks show that DDC-CDIN achieves competitive performance compared to traditional centroid-based and modularity-driven methods in terms of modularity, community cohesion, and boundary clarity. The results indicate that jointly incorporating influence-aware node ranking with distance-based centroid dispersion effectively mitigates centroid crowding and enhances overall community detection quality. These findings demonstrate the effectiveness and robustness of DDC-CDIN for detecting well-structured and topologically coherent communities in complex networks. Full article

This study presents the results of a Proof of Concept developed within the framework of the Amygdala Project, aimed at exploring the relationship between electronic music and emotional well-being among young people with and without a diagnosis of adjustment disorders (anxiety, depression, and distress). The fieldwork was conducted during the live concert of DJ Steve Aoki (Cosquín Rock 2024, Valladolid), combining psychophysiological measurements using Sociograph technology, self-reported questionnaires, and performative and contextual analyses. The results reveal significant differences between the two groups: participants with a diagnosis exhibited a more constant and profound emotional connection, interpreting the experience as a form of “emotional escape” and an opportunity for affective regulation; whereas those without a diagnosis experienced more fluctuating levels of attention and perceived the event primarily as entertainment. The triangulation of biometric, observational, and narrative data suggests that electronic music in collective contexts may operate as a tool for emotional containment and transformation, fostering group cohesion and reducing psychological distress. These findings open new avenues for interdisciplinary research into the biosocial effects of contemporary music and its potential in the design of cultural and educational strategies to promote psychological well-being among young people. Full article

In computer-aided design/computer-aided manufacturing (CAD/CAM) restorations for severely damaged teeth, the cavity floor or proximal margins may be elevated with composite resin to improve adhesion. This in vitro study investigated how different surface pretreatment methods affect the shear bond strength (SBS) of hybrid CAD/CAM materials to dentin or composite surfaces, simulating clinical situations of composite elevation. Hybrid CAD/CAM samples were bonded to dentin or composite substrates following different surface pretreatment protocols and cemented using a dual-cure adhesive resin cement. The samples were thermocycled and subjected to shear bond strength testing, and failure modes were analyzed. The SBS in the sandblasting (SB)+Dentin group and hydrofluoric acid (HF)+Dentin was significantly higher than that in the SB+Composite and HF+Composite groups (p < 0.05). Untreated+composite and untreated+dentin groups showed significantly lower SBS (p < 0.05). Failure mode analysis revealed a predominance of cohesive failures in the SB+Dentin group, while adhesive failures were more frequently observed in most of the other groups. SB-treated and HF-etched hybrid CAD/CAM materials showed more favorable bonding behavior to dentin than to composite, highlighting that bonding to the elevated composite layer may be less effective than bonding directly to prepared dentin. Full article

A major drawback of many proposed biobased alternatives of the most commonly used petroleum-based packaging materials is their relatively poor physical properties. In order to develop more viable alternative packaging materials, these properties need to be modified, while maintaining and improving the other desired characteristics. An investigation was done on corona-charged curcumin-containing PLA films to determine how the addition of the polyphenol impacts its physical properties. Measurements of the surface potential of the films were performed, as was the impact of low pressure on the electret properties. The effect of the corona discharge treatment on the physicochemistry of the surface of composite PLA films was investigated systematically using some complementary surface analytical techniques, such as surface wettability and morphology by scanning electron microscopy. The mechanical properties and conductance of the films were also investigated. A dependency of the decay of the surface potential on the film type and the polarity of the corona was found. It was also established that modifying the surface of the films with corona discharge can cause an increase in their wettability and surface free energy, while also improving their adhesion properties. This is caused by the creation of polar functional groups on the film surface during the charging process. It was also determined that the introduction of curcumin in the PLA films decreases their stiffness, which may be caused by a decrease in intramolecular cohesion. Full article

This study aimed to investigate the effects of dietary tryptophan (Trp) on growth performance and muscle quality of Procambarus clarkii. Six experimental diets with graded Trp concentrations (0.05%, 0.13%, 0.29%, 0.43%, 0.56%, 0.69%; designated Trp0.05 to Trp0.69) were fed to crayfish for 8 weeks. Growth parameters, muscle proximate composition, texture, histology, related gene expression, and intestinal microbiota were measured. Compared with the Trp0.05 group, the Trp0.43 group significantly increased FW, WGR, SGR, and muscle crude protein content, while decreasing FCR. It also improved muscle texture (hardness, springiness, cohesiveness, gumminess, chewiness), increased muscle fiber diameter, and reduced fiber density and the proportion of fibers < 30 μm. Additionally, the Trp0.43 group upregulated mRNA expression of MEF2A, MEF2B, MLC1, MyHC, mTOR, S6K1, AKT, LARP6, Col1α1, Col1α2, TGF-β1, and Smad, and downregulated MSTN, 4EBP1, FOXO, and LC3. It reduced Proteobacteria and Shewanella abundance, and increased Bacteroidota and Firmicutes. In conclusion, appropriate dietary Trp improves P. clarkii growth, muscle quality, and intestinal microbiota. Based on quadratic regression analysis of WGR and SGR, the dietary Trp requirement of P. clarkii was estimated to be 0.39%, corresponding to 1.22% of feed protein. Full article