Search Results (16,395)

“Cashback for positive reviews” is a common form of e-commerce manipulation that may undermine consumer trust and distort the market evaluation system. However, there is a lack of systematic research on how it influences consumers’ willingness to provide evaluations through psychological mechanisms. This study, based on the Stimulus–Organism–Response (S-O-R) framework, integrates the theories of psychological contract and cognitive dissonance. An empirical analysis based on 460 valid questionnaire responses was performed using SPSS and AMOS, yielding the following findings. (1) Negative emotions, including disappointment, anger, and regret, significantly triggered psychological contract breach, both transactional and relational. (2) Psychological contract breach reduced consumers’ willingness to provide positive reviews and lowered their store evaluation behavior, fully mediating the relationship between negative emotions and evaluation behavior. (3) Cognitive dissonance partially moderated the pathway from negative emotions through psychological contract breach to review behavior. This study elucidated the influence mechanism of negative emotions in “cashback for positive review” scenarios on consumers’ evaluation behavior, established a “merchant-user” online review relationship model, and provided practical and managerial implications for fostering mutually beneficial outcomes among platforms, merchants, and consumers. Full article

Political theorists have suggested that democracy is at odds with liberalism. Moreover, with fears about the recent rise in populism, there is growing skepticism about whether liberalism and democracy can continue to survive. In her recent work, Democracy Tamed: French Liberalism and the Politics of Suffrage, political theorist Gianna Englert argues that voters’ political capacity—rather than democratic political rights—kept nineteenth-century French liberalism open to democracy while fostering citizens’ capacity for democracy. The theorists she discusses anticipated the problems we face today, including citizens being manipulated by unscrupulous and unqualified influencers. Thus, the concern over an uninformed public in democracy is not new. In the meantime, students of comparative politics have found that people can rely on elite cues to make reasoned choices “as if” they had sufficient information, even when they are uninformed and inattentive. However, with social media overtaking traditional media as the primary source of information for many people, this democratic safeguard no longer functions as it should. In this article, to tackle the age-old challenge of ensuring that citizens in democracies are well informed enough to make reasoned choices, we first summarize the problems identified by the nineteenth-century French liberal theorists with the capacity of non-elites to make sound political judgments. We then explore how the comparative politics literature has responded to concerns about an uninformed public in democracy, suggesting that the same mechanism would not work if people get information from social media. We examine the impact of social media on the rise of anti-democratic leaders by manipulating public opinion, which has allowed illiberal, populist politicians to come to power. Full article

Innovative pedagogies that nurture higher-order competencies such as autonomy and problem-solving are critical in graduate STEM contexts. This study conceptualizes Thinking Classrooms as a pedagogical framework for graduate engineering education and examines how classroom practices associated with this approach support the development of autonomous learning and complex problem-solving. Drawing on classroom-based evidence collected over multiple academic cohorts in a master’s program in mechanical engineering, we describe patterns of student engagement, instructor adaptations, and evolving learning behaviors. Our findings highlight the potential of Thinking Classroom principles to inform instructional design, foster learner agency, and strengthen disciplinary problem-solving practices in postgraduate engineering education. We discuss implications for curriculum development and future research directions in STEM education. Full article

This contribution examines the key aspects of the aggiornamento of Ignatian spirituality promoted by French Jesuits through the journal Christus between 1954 and 1967. The founding of the journal can be understood as a response to a sense of identity crisis among French Jesuits, likely provoked by the Fourvière crisis and the abrupt end of the worker-priest movement, which was eventually prohibited by Rome. In this context, the call to reconnect with Ignatian sources became imperative to foster theological and spiritual reflection capable of shedding light on the tensions of the present. The generation led by Maurice Giuliani, Michel de Certeau, and François Roustang—who spearheaded this editorial project—distanced itself from the hermeneutics of their predecessors, particularly Joseph de Guibert, as regards the spiritual history of the Society of Jesus. Instead, they emphasized a mysticism of action, the necessary integration of spirituality and apostolic works, the ecclesial implications of Ignatian service, and a bold, increasingly open dialogue between Ignatian tradition and the human sciences. Full article

Against the backdrop of China’s “Dual Carbon” strategy, transitioning to high-quality energy development (HQED) is imperative for balancing decarbonization with economic resilience. This study explores the transformative role of the digital economy as a primary driver of this transition. Using provincial panel data from 2013 to 2023, we employ a two-way fixed effects model to quantify the impact of digital economy on high-quality energy development. Our empirical results demonstrate that the digital economy significantly bolsters high-quality energy development, a finding that holds across rigorous robustness and endogeneity checks. Mechanism analysis reveals three critical transmission pathways: fostering technological innovation, accelerating industrial structure upgrading, and promoting industrial sophistication. Furthermore, heterogeneity analysis indicates a pronounced positive effect in the Eastern and Central regions, whereas the impact in the Western region remains limited, highlighting a “digital divide” in energy transition. These findings suggest that policymakers should prioritize digital infrastructure in lagging regions and leverage digital tools to bridge the gap between industrial upgrading and energy efficiency. Full article

Critical thinking (CT) is essential for navigating the complex socio-scientific issues in contemporary biomedicine. These issues cross disciplinary boundaries and involve multiple societal stakeholders. Interdisciplinary and transdisciplinary (ITD) education therefore provides a valuable context for developing CT by confronting students with diverse forms of knowledge and prompting reflection on their disciplinary assumptions. In this study, boundary crossing is used as a pedagogical framework, with a focus on identification (understanding alternative perspectives) and reflection (examining one’s own assumptions). We examine how such ITD education can foster CT by enhancing students’ appreciation of disciplinary and societal viewpoints. Data from a pre- and post-course assignment were analyzed using a convergent mixed-methods approach. Students ranked the relevance and effectiveness of sessions engaging with different perspectives and identified educational design elements that contributed to broadening their biomedical outlook. Findings indicate shifts in how students perceived the relevance of different perspectives. Particularly, appreciation of the legal perspective increased. Sessions were considered most effective when involving interaction with perspective owners, interactive learning methods, and clear instructional design. The results suggest that boundary-crossing pedagogies can support CT in higher education by engaging students in reflective engagement with different disciplinary and societal perspectives. Full article

The ocean constitutes the largest actively exchangeable carbon reservoir in Earth’s surface system, with the ocean–atmosphere system functioning as an integrated entity that modulates atmospheric CO₂ concentrations over geological timescales. While carbonate and organic-rich sedimentary carbon sinks have been the subject of extensive research, their synergistic roles in long-term carbon–climate feedback loops, as well as the degree to which microbial mediation links ocean hydrographic states to basin-scale carbon sequestration efficiency, remain poorly synthesized. Here, we develop a mechanistic framework comprising five intercoupled components: (1) driving factors (tectonic–climatic forcing and anthropogenic analogs); (2) ocean state controls (basin restriction, water column stratification, and redox conditions); (3) microbial processes (microbial carbon pump-mediated transformation of dissolved organic carbon and the modulating influence of microbial carbonate formation); (4) sedimentary carbon sinks (carbonate platforms versus organic-rich shales underpinning organo-mineral stabilization); and (5) Earth system feedback expressions (e.g., carbon isotope excursions and sustained perturbations in atmospheric CO₂ levels). This framework is validated across three contrasting sedimentary basins, including the Western Tethys rift basins, the Cambrian South China platform system, and the Toarcian Lower Saxony restricted basin, and via three falsifiable propositions. Converging evidence from these case studies corroborates three key conclusions: (1) basin restriction and diminished water mass renewal foster water column stratification and hypoxic/anoxic conditions, thereby enhancing organic carbon preservation (P1); (2) the tectonic and depositional setting of a basin modulates the relative predominance of carbonate and organic carbon sinks (P2); and (3) post-extinction anachronistic facies record amplified microbial control over carbon burial pathways (P3). By emphasizing the context dependence of carbon sequestration processes and the significance of organo-mineral stabilization alongside particulate organic carbon export, this synthesis provides a transferable analytical framework for interpreting deep-time carbon cycle transitions and for contextualizing the impacts of modern ocean warming and deoxygenation on natural carbon sinks. Full article

This study analysed the role of risk perception and business self-efficacy feeling through entrepreneurial education acquired by higher specialised studies on the emergence of entrepreneurial intentions. The quantitative research method included a questionnaire measured on a Likert scale, which was used to collect data from high school and university students from educational institutions with an economic profile in Romania. The evaluation of the model proposed in this study and the testing of the hypotheses postulated was performed through structural equation modelling (SEM). Our findings indicated that the role of risk perception and the self-efficacy feeling acquired through entrepreneurial education have a direct positive and statistically significant impact on entrepreneurial intentions. In the context of the growing relevance of sustainability-oriented entrepreneurship, this study aims to examine how entrepreneurship education fosters sustainable entrepreneurial intentions among young people. Thus, the importance of entrepreneurial education (EE) on entrepreneurial intentions among high school and university students in Romania was confirmed. This study is to investigate how entrepreneurship education encourages sustainability-oriented entrepreneurial intents among young people in light of the growing significance of sustainable entrepreneurial intentions. Full article

Direct-acting antiviral therapies can cure most people with hepatitis C virus (HCV) infection with little need for testing or monitoring. A major challenge to eliminating HCV is ensuring patients complete all steps of care, including confirmation of cure. We assessed the concordance of sustained virologic response (SVR) at 4 weeks (SVR4) and 12 weeks (SVR12) post-treatment to evaluate the viability of SVR4 as a predictor of cure in patients treated with sofosbuvir (SOF)/velpatasvir (VEL). We conducted a retrospective analysis of patients from the Phase 3 ASTRAL-1, -2, and -3 programs and a historical cohort from the Louisiana Department of Health Sexually Transmitted Infection (STI)/HIV/Hepatitis Program claims database. Concordance analyses were performed for patients with both SVR4 and SVR12 data. The concordance analysis in the ASTRAL studies included 1015 patients; 1005 and 1002 achieved SVR4 and SVR12, respectively. Among SVR4 achievers, 3 failed to maintain SVR12, while all (10/10) patients who did not achieve SVR4 also failed SVR12. In the real-world cohort, 479/509 (94%) patients achieved SVR4 and 485/509 (95%) achieved SVR12. Of those with SVR4, 7 failed SVR12; 17 of 30 patients who did not achieve SVR4 also failed SVR12. High concordance between SVR4 and SVR12 was observed in both ASTRAL and the real-world dataset, supporting the use of SVR4 as a predictor of long-term SVR in patients with HCV infection treated with SOF/VEL. Streamlining cure confirmation by shifting SVR determination from week 12 to week 4 post-treatment may reduce patient loss to follow-up. Full article

The proliferation of Unmanned Aerial Vehicles (UAVs) equipped with multispectral imaging sensors has revolutionized data collection in precision agriculture. These platforms provide high-resolution, temporally dense data crucial for monitoring crop health, optimizing resource management, and predicting yield. However, the development and validation of robust data-driven algorithms, from vegetation index analysis to complex deep learning models, are contingent upon the availability of high-quality, standardized, and publicly accessible datasets. This review systematically surveys and characterizes the current landscape of available datasets containing multispectral imagery acquired by UAVs in agricultural contexts. Following guidelines for reporting systematic reviews and meta-analyses (PRISMA methodology), 39 studies were selected and analyzed, categorizing them based on key attributes including spectral bands (e.g., RGB, Red Edge, Near-Infrared), spatial and temporal resolution, types of crops studied, presence of complementary ground-truth data (e.g., biomass, nitrogen content, yield maps), and the specific agricultural tasks they support (e.g., disease detection, weed mapping, water stress assessment). However, the review underscores a critical gap in standardization, with significant variability in data formats, annotation quality, and metadata completeness, which hampers reproducibility and comparative analysis. Furthermore, we identify a need for more datasets targeting specific challenges like early-stage disease identification and anomaly detection in complex crop canopies. Finally, we discuss future directions for the creation of more comprehensive, benchmark-ready open datasets that will be instrumental in accelerating research, fostering collaboration, and bridging the gap between algorithmic innovation and practical agricultural deployment. This work serves as a foundational guide for researchers and practitioners seeking suitable data for their work and contributes to the ongoing effort of standardizing open data practices in agricultural remote sensing. Full article

Artificial intelligence (AI) is rapidly transforming language education. However, its pedagogical and sociocultural impacts on Japanese business writing remain underexplored. This study aims to examine how ChatGPT4o-based automated feedback functions within Japanese business writing education for adult learners in online higher education, with particular attention to both its instructional impact and learners’ sociocultural awareness. Situated in a cyber university context where the proportion of adult learners is increasing, the study explores the potential of AI-mediated feedback to address learners’ diverse educational and cultural needs. It employed a mixed-methods design, combining a survey of 27 participants and in-depth interviews with 11 participants. The interviews were transcribed and thematically coded to gain deeper insights into learners’ perceptions. The findings indicate that ChatGPT feedback contributed to learners’ planning of study strategies, the provision of immediate and personalized corrections, the reinforcement of error awareness, and the acquisition of honorific and polite expressions. On the one hand, learners reported that they could quickly understand regional language practices and communication conventions in business contexts, thereby deepening their cultural sensitivity. On the other hand, some learners expressed concern that increased reliance on AI could weaken exploratory and critical learning. These results suggest that ChatGPT can serve not merely as a correction tool but also as an educational resource that simultaneously fosters self-directed learning and sociocultural competence. However, to ensure reliability and cultural appropriateness, hybrid feedback incorporating instructor guidance is necessary. This study has academic significance in demonstrating the potential of extending AI-based feedback to Japanese business communication education, thereby constructing an integrated language and culture learning environment. Full article

The transition toward carbon-neutral energy systems has revived interest in nuclear technologies, particularly small and micro modular reactors (SMRs and MMRs) as flexible, safe and efficient alternatives to conventional large-scale power plans. In the Czech Republic, Centrum výzkumu Řez (CVŘ) is developing Energy Well (EW), a molten salt-cooled micro modular reactor concept employing FLiBe (Fluoride Lithium Beryllium) as primary and secondary coolant and a supercritical CO₂ (sCO₂) tertiary loop. A dedicated experimental facility was built to reproduce EW operating conditions and provide critical data on thermohydraulic behavior, fuel properties and heat-transfer mechanisms. This paper presents the development and assessment of a TRACE (TRAC/RELAP Advanced Computational Engine) model of the experimental facility, including specific methodologies for the main heater and the heat exchanger. Model accuracy was assessed through comparison with experimental commissioning data. The simulations demonstrated overall model consistency, especially regarding the heat exchanger and the main heater general performances, while some discrepancies were observed inside the main heater graphitic core. Other discrepancies were observed along the loop, mainly resulting from modeling simplifications and lack of information regarding certain experimental loop phenomena. In particular, the pressure calculation showed large inconsistencies mainly connected to the complexity of pressure measurements in molten salt circuits and the lack of specific head loss correlations. This study also helped identify broader issues in both the code (persistent error in generating CO₂ property tables and instabilities resulting from FLiBe interactions with non-condensable gases) and the experimental loop (defect in the heat exchanger filling and uncertainties on sensors location), also contributing to resolving sensor-related inconsistencies in the facility. Results confirm TRACE as a reliable tool for modeling molten salt systems, regarding the temperature distribution and the heat transfer. However, depending on the specific experimental case, this paper introduces specific limitations, such as some inconsistencies in the pressure drops distribution, in order to support the future development of TRACE code. Beyond technical advances, this work provides unique experimental data and fosters international collaboration in advancing SMR and molten salt reactor technologies. Full article

In remote sensing object detection, current models typically employ feature extraction modules and attention mechanisms to tackle issues such as significant scale variations among targets, cluttered backgrounds, and the subtle characteristics of small objects. Nevertheless, existing feature extraction approaches often depend on convolution kernels with fixed sizes, which can blur the contours of large objects and provide inadequate feature representation for small objects. Moreover, many attention mechanisms simply combine spatial and channel attention, without fully considering the deep integration between spatial and channel features, consequently leading to high-dimensional features and considerable computational overhead. To overcome these shortcomings, this paper introduces a multi-scale object detection network with integrated spatial-channel collaborative attention for remote sensing images. This approach enhances feature perception and representation for multi-scale targets, particularly small targets, through the design of the cross-channel multi-scale feature extraction module (CC-MSFE). Furthermore, a new channel-spatial cross-attention mechanism (CSCA) is introduced, comprising the channel attention mechanism (CA), the spatial attention mechanism (SA), and the cross-attention fusion module (CAFM). This design fosters dynamic interaction and joint optimization across channel and spatial dimensions, thereby improving detection accuracy while effectively reducing computational cost. The efficacy of the proposed model is evaluated on three publicly available remote sensing datasets. Experimental results show that the model achieves a mAP of 78.1% on the DIOR dataset and of 90.6% on the HRRSD dataset, outperforming YOLOv11 by 0.7% and 1.4%, respectively. On the RSOD dataset, it attains a mAP of 96.5%, surpassing YOLOv8 by 2.1%. In addition, the proposed method maintains a notably lower parameter count and computational complexity compared to existing approaches, achieving an effective balance between detection accuracy and computational efficiency. Full article

Learning environments are increasingly expected to enable students to develop competencies necessary for addressing complex social, environmental, and technological challenges in sustainable societies. Within this context, instructional approaches that are inclusive, flexible, and learner-centered have gained increasing importance. This study investigates the effects of project-based learning (PBL) informed by Universal Design for Learning (UDL) principles on secondary school students’ 21st-century skills. Employing a mixed-methods embedded design, the quantitative component utilized a quasi-experimental pretest–posttest control group model. The study was conducted with 60 eleventh-grade students enrolled in a public high school, with one group receiving UDL-informed PBL instruction and the other following the standard curriculum. Data were collected using the 21st Century Learner Skills Usage Scale and analyzed through paired-samples t-tests, independent-samples t-tests, and ANCOVA. The findings revealed statistically significant improvements in the experimental group’s overall 21st-century skills, particularly in cognitive skills and collaboration and flexibility, with medium to large effect sizes. In contrast, the control group showed no meaningful gains, and a decline was observed in innovation skills. The results indicate that project-based learning informed by UDL principles constitutes an effective pedagogical approach for fostering inclusive and sustainable learning environments that support the development of future-oriented learner competencies. These findings further suggest that integrating UDL principles into project-based instructional models may contribute to competency-oriented and inclusive secondary education systems aligned with sustainability frameworks. Full article

Adaptability and flexibility in teaching with digital technologies are essential for instructors to navigate dynamic and ever-evolving educational contexts. However, little has been done to investigate the underlying competencies required of instructors to fluently integrate technologies into their instructional practices. This study employed the Delphi method to address this gap and identify the competencies of a digitally fluent educator in higher education. Through three rounds of data analysis, 36 experts across multiple higher education institutions reached consensus on 14 competencies, including 8 knowledge, 3 skills, and 3 dispositions as indicators of an educator fluent in applying digital tools. The final list of competencies highlights the importance of metacognitive skills, conditional knowledge, and a disposition to be adaptable when defining fluency in digital instruction. The findings indicate a differentiation between digital fluency and previous paradigms such as digital literacy and digital competency. Implications for competency-based professional development opportunities and future research are discussed. Full article