Search Results (397)

Glass fiber-reinforced polymer (GFRP) composites exhibit significant advantages over conventional structural webbing materials, including lightweight and corrosion resistance. This study investigates the localized compression performance of the proposed GFRP grid web–concrete composite beam through experimental and numerical analyses. Three specimen groups with variable shear-span ratios (λ = 1.43, 1.77) and local stiffener specimens were designed to assess their localized compressive behavior. Experimental results reveal that a 19.2% reduction in shear-span ratio enhances ultimate load capacity by 22.93% and improves stiffness by 66.85%, with additional performance gains of 77.53% in strength and 94.29% in stiffness achieved through local stiffener implementation. In addition, finite element (FE) analysis demonstrated a strong correlation with experimental results, showing less than 5% deviation in ultimate load predictions while accurately predicting stress distributions and failure modes. FE parametric analysis showed that increasing the grid thickness and decreasing the grid spacing within a reasonable range can considerably enhance the localized compression performance. The proposed analytical model, based on Winkler elastic foundation theory, predicts ultimate compression capacities within 10% of both the experimental and numerical results. However, the GFRP grid strength adjustment factor β_g should be further refined through additional experiments and numerical analyses to improve reliability. Full article

The characterization of Large Reasoning Models (LRMs) as exhibiting an “illusion of thinking” has recently emerged in the literature, sparking widespread public discourse. Some have suggested these manifestations represent bugs requiring fixes. I challenge this interpretation by reframing LRM behavior through dual-process theory from cognitive psychology. I draw on more than half a century of research on human cognitive effort and disengagement. The observed patterns include performance collapse at high complexity and counterintuitive reduction in reasoning effort. These appear to align with human cognitive phenomena, particularly System 2 engagement and disengagement under cognitive load. Rather than representing technical limitations, these behaviors likely manifest computational processes analogous to human cognitive constraints. In other words, they represent not a bug but a feature of bounded rational systems. I propose empirically testable hypotheses comparing LRM token patterns with human pupillometry data. I suggest that computational “rest” periods may restore reasoning performance, paralleling human cognitive recovery mechanisms. This reframing indicates that LRM limitations may reflect bounded rationality rather than fundamental reasoning failures. Accordingly, this article is presented as a hypothesis paper: it collates six decades of cognitive effort research and invites the scientific community to subject the dual-process predictions to empirical tests through coordinated human–AI experiments. Full article

The uptake of the COVID-19 and seasonal influenza (SI) vaccines have decreased in Europe and especially in Malta. The present study aimed to investigate the attitudes toward COVID-19 and SI vaccines and determine if individuals perceive that these vaccines are relevant to protect their health and identify reasons for their responses. A cross-sectional study using an anonymous questionnaire, informed by the Theory of Planned Behavior, addressing behavior beliefs and attitudes, and targeted at adult residents in Malta, was designed on Google Forms and disseminated using social media between January and March 2024. A total of 555 responses were received. The majority of respondents did not take/intend to take the COVID-19 (75%, n = 417) or SI (64.3%, n = 362) vaccines, with females being less likely to do so (p = 0.033). Perceived lack of safety (31.3%, n = 174) was the primary reason for rejecting the COVID-19 vaccine, and perceived lack of a threat from SI (26%, n = 144) was the reason for rejecting the SI vaccine. Those having chronic conditions were positively associated with uptake of both vaccines. In the post-pandemic era, these vaccines are not envisaged as having a major role in protecting one’s health. A high degree of skepticism especially toward the combined COVID-19 and SI vaccine in terms of safety, mostly in women, is still present. Full article

Coal miners’ unsafe behavior is the primary reason for accidents. This research aims to examine the effect of male coal miners’ shared work crew identity on their safety behavior. A 2-2-1 multilevel mediation model is established based on social identity theory and safety climate theory. To validate the model, a paper-and-pencil survey with male coal miners was carried out in Henan Province, China. A total of 212 valid responses from male coal miners nested in 53 work crews were secured, and Mplus was used to analyze the data. Results show that work crew safety climate fully mediates the effect of male coal miners’ shared work crew identity on their safety behavior. In theory, the findings support that social identity brings a safety climate. In practice, the findings highlight that making safety part of work crew norms improves male coal miners’ safety behavior. Limitations and future research are also discussed. Full article

Expatriates and missionaries in China played a significant role in the development and transformation of Chinese architecture in the Late Qing period. However, a systematic comparison of their discourses and proposals on Chinese architecture has been hindered by a lack of historical literature and the complexities of fragmented data and methodologies. This article examines and compares the two most influential non-native newspapers: The North-China Daily News in English, edited by expatriates, and The Review of the Times in Chinese, founded by missionaries. By analyzing these two groups’ discourses and narratives on Chinese architecture, the study explores their similarities and distinctions, revealing the characteristics, strategies, attitudes, interests, and opinions of expatriates, missionaries, and non-missionaries in China on the transmission and transformation of architecture knowledge. The research highlights differences in their preferences for specific text types, subjects, and themes on Chinese architecture, as well as their attitudes toward native and foreign architecture, professional education, and architecture regulations in individual and official spheres. Despite these differences, overlapping characteristics and proposals existed among the three groups. The study further investigates the underlying reasons and mechanisms for their similar or divergent mindsets and behavioral patterns, drawing on human responsive psychology rather than relying on postcolonial or cultural theories. Full article

In composites, fiber–matrix thermal mismatch induces stress heterogeneity that is beyond the resolution of macroscopic approaches. The asymptotic expansion homogenization method is used to create a multi-scale thermo-mechanical coupling model that predicts the elastic modulus, thermal expansion coefficients, and thermal conductivity of ceramic matrix composites at both the macro- and micro-scales. These predictions are verified to be accurate with a maximum relative error of 9.7% between the measured and predicted values. The multi-scale analysis method is then used to guide the vane’s thermal stress analysis, and a macro–meso–micro multi-scale model is created. The thermal stress distribution and stress magnitudes of the guide vane under a transient high-temperature load are investigated. The results indicate that the temperature and thermal stress distributions of the guide vane under the homogenization and lamination theory models are rather comparable, and the locations of the maximum thermal stress are predicted to be reasonably close to one another. The homogenization model allows for the rapid and accurate prediction of the guide vane’s thermal stress distribution. When compared to the macro-scale stress values, the meso-scale predicted stress levels exhibit excellent accuracy, with an inaccuracy of 11.7%. Micro-scale studies reveal significant stress concentrations at the fiber–matrix interface, which is essential for the macro-scale fatigue and fracture behavior of the guide vane. Full article

The COVID-19 pandemic has significantly altered consumer habits, particularly in relation to food choices. In this context, plant-based diets have gained prominence, driven by health, environmental, and ethical considerations. This study investigates the primary motivational and inhibitory factors influencing the consumption of plant-based foods among residents of the Galicia–Northern Portugal Euroregion. Utilizing the Theory of Reasoned Action, an extended model was proposed and tested through a quantitative survey. A total of 214 valid responses were collected via an online questionnaire distributed in Portuguese and Spanish. Linear regression analysis revealed that health awareness, animal welfare, and environmental concern significantly shape positive attitudes, which subsequently affect the intention to consume plant-based foods. Additionally, perceived barriers—such as lack of taste and insufficient information—were found to negatively influence intention. These findings contribute to the consumer behavior literature and provide strategic insights for stakeholders aiming to promote more sustainable dietary patterns in culturally connected cross-border regions. Full article

This study explores strategic deception and counter-deception in multi-agent reinforcement learning environments for a police officer–robber game. The research is motivated by real-world scenarios where agents must operate with partial observability and adversarial intent. We develop a suite of progressively complex grid-based environments featuring dynamic goals, fake targets, and navigational obstacles. Agents are trained using deep Q-networks (DQNs) with game-theoretic reward shaping to encourage deceptive behavior in the robber and intent inference in the police officer. The robber learns to reach the true goal while misleading the police officer, and the police officer adapts to infer the robber’s intent and allocate resources effectively. The environments include fixed and dynamic layouts with varying numbers of goals and obstacles, allowing us to evaluate scalability and generalization. Experimental results demonstrate that the agents converge to equilibrium-like behaviors across all settings. The inclusion of obstacles increases complexity but also strengthens learned policies when guided by reward shaping. We conclude that integrating game theory with deep reinforcement learning enables the emergence of robust, deceptive strategies and effective counter-strategies, even in dynamic, high-dimensional environments. This work advances the design of intelligent agents capable of strategic reasoning under uncertainty and adversarial conditions. Full article

Consciousness remains one of the most critical yet least understood functions of the brain, not only in humans but also in certain highly organized animal species. In this review, we propose treating consciousness as an emergent, goal-directed informational system organized by the subjective “self” as an active system-forming factor. We present an integrative theoretical–systems framework in which subjectivity functions as system-forming factor of consciousness (SFF) throughout biological evolution. Beginning with proto-conscious invertebrates, we trace progressive elaborations of working and long-term memory, the refinement of behavioral programs, and the emergence of an internal arbiter capable of resolving competing drives. In endothermic vertebrates, subjectivity acquires distinct functional features—sensory filtering, causal reasoning, and adaptive arbitration—underpinned by increasingly complex neural architectures. This evolutionary trajectory culminates in humans, where subjectivity attains its highest level of organization through culturally mediated networks. Although the framework does not assume any specific neural substrate, it provides a testable roadmap linking evolutionary biology, information theory, and quantitative modeling. By clarifying why consciousness arose and how subjectivity shapes complex networks, this perspective also lays the groundwork for exploring possible nonbiological extensions of subjectivity. Full article

Flexible strain sensors, fabricated from high-elongation polymers and conductive filler particles, are proving an essential tool in the study of biomechanics using wearable technology. It has been previously shown that the resistive response of such composites, relative to the amount of conductive filler material, can be reasonably modeled using a standard percolation-type model. Once a certain critical fraction of filler material is reached, a conductive network across the sample is established and resistance rapidly decreases. However, modeling the more subtle resistance changes that occur while deforming the sensors during operation is more nuanced. Conductivity across the network of particles is dominated by tunneling mechanisms at the interfaces between the filler materials. Small changes in strain at these interfaces lead to relatively large, but nevertheless continuous, changes in local resistance. By assigning some arbitrary value of resistance as a dividing line between ‘low’ and ‘high’ resistance, one might model the piezoresistive behavior using a standard percolation model. But such an assumption is likely to lead to low accuracy. Our alternative approach is to divide the range of potential resistance values into several bins (rather than the usual two bins) and apply a relatively novel multi-state percolation theory. The performance of the multi-state percolation model is assessed using a random resistor model that is assumed to provide the ground truth. The model is applied to predict resistance response with both changes in relative amount of conductive filler (i.e., to help design the initial unstrained sensor) and with applied strain (for an operating sensor). We find that a multi-state percolation model captures the behavior of the simulated composite sensor in both cases. The multicomponent percolation theory becomes more accurate with more divisions/bins of the resistance distribution, and we found good agreement with the simulation using between 10 and 20 divisions. Full article

As aging urban expressways become more pronounced, maintenance and construction work on these roadways is increasingly necessary. Some lanes may need to be closed during maintenance and construction, decreasing driving safety and comfort in the work zone. This situation often leads to traffic congestion and a higher risk of traffic accidents. Notably, 80% of work zone traffic accidents occur in the warning and upstream transition areas (or simply warning and transition areas). Therefore, it is crucial to appropriately determine the lengths of these areas to enhance both safety and comfort for drivers. In this study, we examined three different warning lengths (1800 m, 2000 m, and 2200 m) and three transition lengths (120 m, 140 m, and 160 m) using the entropy weighting method to create nine simulation scenarios on a two-way, six-lane urban expressway. We selected various metrics for driving safety and comfort, including drivers’ eye movement, electroencephalogram, and driving behavior indicators. A total of 45 participants (mean age = 23.9 years, standard deviation = 1.8) were recruited for the driving simulation experiment, and each participant completed all 9 simulation scenarios. After eliminating 5 invalid datasets, we obtained valid data from 40 participants. We employed a combination of the analytic network process and entropy weighting method to calculate the comprehensive weights of the eight evaluation indicators. Additionally, we introduced the fuzzy theory, utilizing a trapezoidal membership function to evaluate the membership matrix values of the indicators and the comprehensive evaluation grade eigenvalues. The ranking of the experimental scenarios was determined using these eigenvalues. The results indicated that more extended warning lengths correlated with increased safety and comfort. Specifically, the best driver safety and comfort levels were observed in Scenario I, which featured a 2200 m warning length × 160 m transition length. However, the difference in safety and comfort across different transition lengths diminished as the warning length increased. Therefore, when road space is limited, a thoughtful combination of reasonable lengths can still provide high driving safety and comfort. Full article

This study explores the factors driving employees’ sustainability-switching behaviors (SSBs) by integrating the Push, Pull, and Mooring (PPM) model with the Theory of Reasoned Action (TRA). A quantitative, cross-sectional survey was conducted with a convenience sample of 132 professionals actively involved in organizational sustainability initiatives across diverse industries and global regions. The findings reveal that leadership commitment significantly fosters both affective and normative employee commitments, with normative commitment positively influencing SSB. Surprisingly, organizational trust showed a negative impact on SSB, suggesting that employees may delegate responsibility for sustainability to the organization when trust is high. Inertia emerged as a strong barrier to behavioral change, independently inhibiting sustainability efforts. The study highlights the complex dynamics among leadership, trust, and inertia, offering practical insights for organizations aiming to foster sustainability. Addressing inertia directly and promoting shared responsibility for sustainability are critical for successful organizational transitions. Future research should explore the psychological mechanisms behind inertia and further investigate the paradoxical role of trust in sustainability initiatives. Full article

As smart voice assistants (SVAs) become increasingly integrated into digital commerce, understanding the psychological factors driving their adoption or resistance is essential. While prior research has addressed the impact of privacy concerns, few studies have explored the competing forces that shape user decisions. This study investigates the dual role of privacy cynicism as a context-specific belief influencing both trust (reason-for) and perceived creepiness (reason-against)—which in turn affect attitudes, behavioral intentions, and resistance toward SVA usage, based on the Behavioral Reasoning Theory (BRT). The study used a convenience sampling method, gathering data from 250 Turkish consumers aged 18–35 through an online survey technique. The research model was analyzed using PLS-SEM. The findings revealed that perceived creepiness increases resistance intention but does not significantly affect attitudes toward using SVAs. Perceived cynicism was found to positively influence perceived trust, and perceived trust, in turn, increased both behavioral intentions and attitudes toward using SVAs. Furthermore, attitudes toward SVA usage decreased resistance intention but increased behavioral intention. The results emphasize consumer trust and skepticism in AI-driven marketing. The study offers both theoretical contributions by extending BRT with a novel dual-path conceptualization of privacy cynicism, and practical implications for developers aiming to boost SVA adoption through trust-building and privacy assurance strategies. Full article

Numerous studies have shown a positive relationship between intelligence and health, with higher intelligence quotient (IQ) linked to better health outcomes, longer life expectancy, and lower rates of non-communicable diseases. Better health behaviour in the more intelligent (either due to better health knowledge or more advantageous social-financial opportunities) and system integrity theory (overlaps in the background causes of intelligence and health, such as genetic factors) are competing explanations for this link. This study aimed to examine the dietary habits of high-IQ individuals compared to a control group. An online questionnaire was completed by Mensa members (IQ ≥ 130) and control group participants from three countries, assessing various lifestyle factors, especially dietary habits. Key findings include lower smoking rates among Mensa members, special diets primarily for personal rather than medical reasons, and more frequent consumption of some national staples. There was no clear trend for healthier nutritional habits among Mensa members, suggesting that this aspect of health behavior does not account for better health in the more intelligent and supporting system integrity theory instead. Full article

Large Language Models (LLMs) have demonstrated strong performance on English-language medical exams, but their effectiveness in non-English, high-stakes environments is less understood. This study benchmarks nine LLMs against human examinees on the Chilean Anesthesiology Certification Exam (CONACEM), a Spanish-language board examination. A curated set of 63 multiple-choice questions was used, categorized by Bloom’s taxonomy into four cognitive levels. Model responses were assessed using Item Response Theory and Classical Test Theory, complemented by additional error analysis, categorizing errors as reasoning-based, knowledge-based, or comprehension-related. Closed-source models surpassed open-source models, with GPT-o1 achieving the highest accuracy (88.7%). Deepseek-R1 is a strong performer among open-source options. Item difficulty significantly predicted the model accuracy, while discrimination did not. Most errors occurred in application and understanding tasks and were linked to flawed reasoning or knowledge misapplication. These results underscore LLMs’ potential for factual recall in Spanish medical exams but also their limitations in complex reasoning. Incorporating cognitive classification and error taxonomy provides deeper insights into model behavior and supports their cautious use as educational aids in clinical settings. Full article