Search Results (13,764)

Previous research has shown individual differences in (a) time on task (ToT) and (b) the degree of structuredness in processing figural matrices. The goal of this article was to integrate these two lines of research by analyzing log files from a computer-based assessment (N = 198) to examine the role of three ToT sub-components: onset times (before engaging with the first matrix rule), interrule times (between the rules), and intrarule times (within a single rule). We tested three clues that support the assumptions that the interrule times reflect the cognitive construction of a rule-specific solution plan, while the onset times represent a global orientation reaction, and the intrarule times capture the behavioral execution of the plan: (1) based on the interrule times, we identified two clusters of participants, of which one processed the matrices in a more structured fashion; (2) only the accelerating effect of the interrule times across the test was associated with test performance, indicating higher reasoning saturation; (3) a mediated path analysis revealed that faster interrule times propagate in faster intrarule times and more structured processing of matrix rules, resulting in better performance. Confirming internal validity, the three log file times accounted for an incremental 24.30% of test performance variance beyond the traditional ToT. Confirming external validity, two clusters were also identified based on the interrule times from the first test and performance scores from a second matrix test. Full article

The diffusion of green energy technological innovation based on international green energy cooperation is a critical pathway to achieving global low-carbon emission reductions. However, few studies have considered the innovation diffusion pathways of green energy technologies under bilateral policy uncertainties. This paper constructs an evolutionary game model for the diffusion of green energy technological innovation in a complex network environment, with a focus on analyzing the impacts of key parameters such as policy spillover effects, technological heterogeneity, technical leakage risks, and free-riding risks on the equilibrium outcomes of evolutionary strategies. The results of the study are as follows: (1) Technological synergy and technological heterogeneity have a significant role in promoting the diffusion of green energy technological innovation, but when technological heterogeneity is too high, it is difficult for the two parties to find more common interests and areas of technological interaction, and the cooperative innovation will be turned into an empty shell that has a name but no reality. (2) Policy uncertainty has a significant impact on the diffusion of green energy technology innovation, and the specific impact depends on the type of policy, policy intensity, policy spillover effects, and other key parameters. (3) The risk of technological obsolescence has prompted countries to deeply participate in green energy international cooperation to realize the “curved road overtaking” of green energy technology based on technological locking and latecomer advantages; due to the existence of the phenomenon of “free-riding”, the logic of value creation based on win–win cooperation is replaced by the opportunism of “enjoying the benefits”, and cooperative innovation may be turned into a one-time “handshake agreement”. The existence of the risk of technology leakage can turn collaborative innovation into a “witch hunt” by the underdog against the overdog, and the diffusion process of green energy technology innovation is led in the wrong direction. Full article

With the increasing air traffic flow, the workload of air traffic controllers is also growing, and their proficiency directly impacts civil aviation safety and efficiency. To address the lack of clear training objectives and inconsistent evaluation methods in the initial controller training at the Southwest Air Traffic Management Bureau, this study aimed to develop and validate a core competency model for initial air traffic controllers. Referencing ICAO Document 10056, the study first defined core competencies. Subsequently, using job analysis, the behavioral event interview (BEI) method, and expert panels, a core competency model tailored to the training objectives of the Southwest ATMB was constructed. The key findings of this research include: first, the defined structure of the developed model, comprising seven competency dimensions, 21 elements, and 26 observable behaviors (OBs); second, the determination of combined weights for each dimension and indicator using questionnaire surveys, the Analytic Hierarchy Process (AHP), and the Entropy Weight Method; and third, the successful application and validation of the model. Specifically, in its application, the weighted TOPSIS method was employed to evaluate trainees in a specific group. This not only provided a ranking of trainee abilities but also facilitated in-depth analysis through radar charts of competency dimensions and box plots of OB items. These application results demonstrate the model’s effectiveness and practicality. Full article

In intelligent building, efficient surface defect detection is crucial for structural safety and maintenance quality. Traditional methods face three challenges in complex scenarios: locating defect features accurately due to multi-scale texture and background interference, missing fine cracks because of their tiny size and low contrast, and the insufficient generalization of irregular defects due to complex geometric deformation. To address these issues, an improved version of the You Only Look Once (YOLOv8) algorithm is proposed for building surface defect detection. The dataset used in this study contains six common building surface defects, and the images are captured in diverse scenarios with different lighting conditions, building structures, and ages of material. Methodologically, the first step involves a normalization-based attention module (NAM). This module minimizes irrelevant features and redundant information and enhances the salient feature expression of cracks, delamination, and other defects, improving feature utilization. Second, for bottlenecks in fine crack detection, an explicit vision center (EVC) feature fusion module is introduced. It focuses on integrating specific details and overall context, improving the model’s effectiveness. Finally, the backbone network integrates deformable convolution net v2 (DCNV2) to capture the contour deformation features of targets like mesh cracks and spalling. Our experimental results indicate that the improved model outperforms YOLOv8, achieving a 3.9% higher mAP50 and a 4.2% better mAP50-95. Its performance reaches 156 FPS, suitable for real-time inspection in smart construction scenarios. Our model significantly improves defect detection accuracy and robustness in complex scenarios. The study offers a reliable solution for accurate multi-type defect detection on building surfaces. Full article

Generally, following an omnibus (overall equality) test, multiple pairwise comparison (MPC) tests are typically conducted as the second step in a sequential testing procedure to identify which specific pairs (e.g., proportions) exhibit significant differences. In this manuscript, we develop maximum likelihood estimation (MLE) methods to construct three different types of confidence intervals (CIs) for multiple pairwise differences in proportions, specifically in contexts where both types of misclassifications (i.e., over-reporting and under-reporting) exist in multiple-sample binomial data. Our closed-form algorithm is straightforward to implement. Consequently, when dealing with multiple sample proportions, we can readily apply MPC adjustment procedures—such as Bonferroni, Šidák, and Dunn—to address the issue of multiplicity. This manuscript advances the existing literature by extending from scenarios with only one type of misclassification to those involving both. Furthermore, we demonstrate our methods using a real-world data example. Full article

Constrained pseudorandom functions (CPRFs) are fundamental cryptographic primitives used in broadcast encryption and attributed-based encryption. Constrained verifiable random functions (CVRFs) extend CPRFs by incorporating verifiability. A constrained key $s{k}_S$, derived from the master secret key $sk$, restricts computation to a set Sf with correct evaluation. This allows holders of $s{k}_S$ to compute function values only for inputs in S. Prior constructions of CVRFs rely on strong assumptions like multilinear maps or indistinguishability obfuscation, which often suffer from theoretical or practical limitations. In this work, we introduce a simple, generic approach for building CVRFs from basic cryptographic primitives. Specifically, we give a general transformation from any CPRF to a CVRF, achieving provability, uniqueness, and pseudorandomness. We demonstrate that CVRFs can be generically constructed from the following cryptographic primitives: CPRFs, perfectly binding commitment schemes, and non-interactive proof systems. Compared to previous schemes, our approach features a fixed-length public key independent of the circuit depth, improving efficiency and scalability. Full article

This study investigates the determinants of eco-buying behavior by drawing from the Theory of Planned Behavior (TPB) and considering green consumption values and prosocial attitudes. Using a cross-sectional survey of 436 adults in the UK and employing a two-step analysis with Partial Least Squares Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA), this research examines both sufficient and necessary conditions for sustainable purchasing behavior. The findings reveal that green consumption values and social influence are positively associated with green buying behavior, with green consumption values exerting the strongest influence. Conversely, prosocial attitudes and perceived behavioral control show no significant direct effects, yet age moderates the relationship between prosocial attitudes and green buying behavior. Moreover, NCA identifies green consumption values and perceived behavioral control as necessary conditions at specific thresholds, underscoring their importance in fostering high levels of green buying behavior. Additionally, a logarithmic relationship is observed between green consumption values and green buying behavior, suggesting diminishing returns at higher levels of green consumption values. Notably, the influence of green consumption values on green buying behavior is stronger among older individuals (35+), highlighting age-based differences in sustainable consumption. By integrating both sufficient and necessary conditions, this research addresses the attitude-behavior gap in sustainable consumption, offering novel insights into the roles of intrinsic values and social influences. These findings challenge established constructs like perceived behavioral control and highlight the relevance of advanced analytical methods in sustainable consumer research. The study contributes theoretical insights and practical implications for sustainable marketing strategies targeting value-driven consumers. Full article

Objectives: Differentiation of adrenal incidentalomas (AIs) remains a challenge in the oncological setting. The aim of the study was to explore the diagnostic efficacy of [18F]Fluorodeoxyglucose (FDG) positron emission tomography combined with computed tomography (PET/CT)-based radiomics in identifying adrenal metastases and to compare it with that of conventional PET/CT parameters. Materials: Retrospective analysis was performed on 195 AIs for model construction, nomogram drawing, and internal validation. An additional 30 AIs were collected for external validation of the radiomics model and nomogram. Logistic regression analysis was employed to build models based on clinical and PET/CT routine parameters. The open-source software Python (version 3.7.11) was utilized to process the regions of interest (ROI) delineated by ITK-SNAP, extracting radiomic features. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied for feature selection. Based on the selected features, the optimal model was chosen from ten machine learning algorithms, and the nomogram was constructed. Results: The area under the curve (AUC), sensitivity, specificity, and accuracy of conventional parameters of PET/CT were 0.919, 0.849, 0.892, and 0.844, respectively. XGBoost demonstrated superior diagnostic efficiency among the radiomics models, outperforming those constructed using independent predictors. The AUC, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of XGBoost’s internal and external validation were 0.945, 0.932, 0.930, 0.960, 0.970, 0.890 and 0.910, 0.900, 0.860, 1, 1, 0.750. The accuracy, sensitivity, specificity, PPV, and NPV of the nomogram in external validation were 0.870, 0.952, 0.667, 0.870, and 0.857. Conclusions: The radiomics model and conventional PET/CT parameters both showed high diagnostic performance (AUC p > 0.05) in discriminating adrenal metastases from benign lesions, offering a practical, non-invasive approach for clinical assessment. Full article

EU legislation provides the implementation of most building energy performance measures at a subnational level. This obligation is causing a lot of completely new dilemmas that are challenging for local governments (LGs), requiring a radical re-evaluation of the prioritization of LGs’ traditional tasks and the ranking of new responsibilities. The attitude of local population and businesses towards the solutions to dilemmas, which are set by LGs decisions, vary widely. Separate groups actively lobby for their mutually contradictory interests, questioning decisions and fighting against them during the decision-drafting and -making process, significantly hindering the work of LGs and prolonging decision-making. The authors’ suggested solution to the problem is to make municipal decisions based on verifiable data and facts, thus preventing the manifestations of populism and demagogy, and reducing the possibilities for interest group advocacy. To obtain objective information for balanced decision-making about the benefits and costs of heating system retrofitting projects without carrying out the labor-intensive, time-consuming, and costly design of various options, an express methodology and an easy-to-use tool for project feasibility studies have been developed. The methodology utilizes a limited number of open indicators to streamline the evaluation process, and does not require specific knowledge in thermal physics, economics, or construction. Full article

B Cell Maturation Antigen (BCMA) has gained considerable attention as a target in directed therapies for multiple myeloma (MM) treatment, via immunoglobulin-based bispecific T cell engagers or CAR T cell strategies. We describe the development of alternative, non-immunoglobulin BCMA-recognising affinity proteins, based on the small (58 aa) three-helix bundle affibody scaffold. A first selection campaign using a naïve affibody phage library resulted in the isolation of several BCMA-binding clones with different kinetic profiles. One clone showing the slowest dissociation kinetics was chosen as the template for the construction of two second-generation libraries. Characterization of output clones from selections using these libraries led to the identification of clone 1-E6, which demonstrated low nM affinity to BCMA and high thermal stability. Biosensor experiments showed that 1-E6 interfered with the binding of BCMA to both its natural ligand APRIL and to the clinically evaluated anti-BCMA monoclonal antibody belantamab, suggesting overlapping epitopes. A fluorescently labelled head-to-tail homodimer construct of 1-E6 showed specific binding to the BCMA⁺ MM.1s cell line in both flow cytometry and fluorescence microscopy. Taken together, the results suggest that the small anti-BCMA affibody 1-E6 could be an interesting alternative to antibody-based affinity units in the development of BCMA-targeted therapies and diagnostics. Full article

In public–private partnership (PPP) projects, the private sector’s performance is influenced by administrative efficiency, and the impact varies across different contractual dimensions. Existing research mainly focuses on the influence of project governance on project performance, with few scholars delving into the impact of administrative efficiency on the contractual dimensions of PPP projects. To address this gap, this study employs literature analysis to examine the contractual relationships among PPP project stakeholders, identifying four sub-dimensions: responsibility and authority allocation, profit allocation, risk allocation, and accountability. It then investigates the moderating role of administrative efficiency in the relationships between contractual dimensions and project performance, proposing hypotheses and constructing a research model. The findings reveal that all four sub-dimensions of contractual relationships exert significant positive effects on project performance. Specifically, administrative efficiency significantly enhances the positive relationship between responsibility/authority allocation and project performance, as well as between risk allocation and project performance. These results highlight the critical role of administrative efficiency in optimizing contractual mechanisms to improve PPP project outcomes, providing theoretical and practical insights for enhancing contractual governance in PPP projects. Full article

Background: Dementia is a global condition affecting over 55 million people. Since there is no treatment, non-pharmacological interventions aim to delay its progression in a safe and cost-effective way. The extant literature suggests that Positive Psychology Interventions (PPIs) can probably be effective for this purpose. The systematic review aims to assess the effectiveness of PPIs as non-pharmacological interventions for mild cognitive decline related to dementia by evaluating their effectiveness in cognitive functions and brain functioning in people with Subjective Cognitive Decline (SCD), Mild Cognitive Impairment (MCI), and mild Alzheimer’s disease dementia (AD). Methods: A comprehensive search conducted in the databases Scopus, PubMed, ScienceDirect and PsychINFO (December 2024–March 2025) published between 2015 and 2025 to identify records that met inclusion criteria: studies included patients with SCD, MCI and mild AD dementia, implemented PPIs, Randomized controlled trials (RCTs) and pre–post intervention studies with measurable outcomes, assess at least one of the following: cognitive functions and brain functioning. Results: The systematic review included 12 studies (N = 669 participants) that can answer the research question. Only mindfulness interventions were identified. Findings suggest that different types of mindfulness interventions, such as the Mindfulness Awareness Program (MAP) and Mindfulness Training (MT), may be efficient for improving specific cognitive functions (e.g., working memory and attention) and influencing biological pathways related to cognitive decline. However, long-term efficacy has not been demonstrated, and results are mixed and unclear. Conclusions: Μindfulness interventions seem promising for enhancing cognition and brain functioning in older adults with cognitive decline, although the data is limited. However, limitations such as the heterogeneity of the studies and the diversity of the interventions make it necessary for more systematic and organized research to be conducted on the implementation of such interventions. At the same time, it is proposed to examine the effectiveness of other constructs of positive psychology, such as character strengths (CS). Full article

The combustion chamber is a critical component of turbojet engines, and airflow distribution plays an essential role in ensuring flame stability and optimizing combustion efficiency. This study investigates a miniature annular combustion chamber by employing SolidWorks 2022 software to model an evaporative tube combustion chamber. A dedicated combustion test platform was constructed for the proposed miniature combustion chamber. By adjusting the air and fuel flow ratios entering the evaporative tube, the temperature at the flame tube outlet was measured, and the combustion efficiency was subsequently calculated. In addition, numerical analysis was conducted using ANSYS/CFX software to simulate the flow field in the combustion chamber. The following conclusions were drawn from an analysis of the variations in the flow field and temperature field during the simulation process: When the flow rates in the ignition and dilution zones of the miniature annular combustion chamber remained constant, modifying the air-fuel flow ratio within the evaporative tube significantly enhanced the combustion characteristics within the chamber. Specifically, the combustion efficiency is closely related to the ratio of the air mass flow rate to the fuel mass flow rate within the evaporation tube. The highest combustion efficiency was achieved when the ratio fell within the range of 4.20 to 4.96. Furthermore, the area-averaged velocity at the combustion chamber outlet was independent of the air-fuel flow ratio but exhibited a positive correlation with the fuel flow entering the combustion chamber. Full article

Molybdenum nitrides are known to have a series of excellent physical properties owing to their unique bonding nature and electronic structure. However, the synthesized samples often exist in nonstoichiometric phases with structural defects (metal or non-metal vacancies), which may influence their performance. Based on the density functional theory, we theoretically studied the vacancy formation in δ-MoN. Various configurations that contained one single vacancy, divacancies, or trivacancies were constructed and systematically studied. It was found that Mo vacancy leads to significant electron loss at the vacant site while N vacancy results in excess electrons being trapped, forming a uniform electron gas region. Detailed analysis revealed that four types of binding clusters are encouraged to form in δ-MoN. The V_Mo–V_N or V_N–V_Mo–V_N (with a sandwich structure) binding is owing to the positive and negative interaction between Mo and N vacancies. The V_N–V_N or V_N–V_N–V_N binding is attributed to the overlap of electron density, but requires N vacancies to be distributed in a specific arrangement. Both Mo and N vacancies induce the anisotropic degradation of electronic conductivity in δ-MoN, with the extent of degradation governed by the vacancy type and concentration. Full article

CO₂ emissions, a significant contributor to climate change, have spurred the exploration of sustainable solutions. One putative solution involves using recycled aggregates (RAs) from construction and demolition waste (CDW) to substitute natural sand in construction materials. This not only extends the life cycle of the waste but also reduces the use of natural resources. The potential to capture CO₂ in RAs presents a promising route to mitigate the environmental impact of the construction industry and contribute to its much anticipated decarbonization. This research takes a unique approach by investigating the incorporation of an amine-based additive—specifically 2-amino-2-methyl-1,3-propanediol (AMPD)—to enhance CO₂ capture into a real-case RA from recycling plants, transforming CDW with low carbon-capture potential into a highly reactive CO₂ capture material. Through TG analysis, FTIR-ATR and the combination of both (TG-FTIR), we were able to validate the use of RA materials as a support medium and quantify the CO₂ capture potential (12%) of the AMPD amine; a dual valorization was achieved: new value was added to low-quality CDW and we enhanced CO₂ sequestration, offering hope for a more sustainable future. Full article