Using event-related potentials (ERPs), this study examines how trait information inferred from behaviors is associated with person names. In linguistic discourses, person names were associated with descriptions of either positive or negative behaviors. In a subsequent explicit evaluation task, the previously described person names were presented in isolation, and the participants were asked to judge the emotional valence of these names. We found that the names associated with positive descriptions elicited a larger positivity in the ERP than the names associated with negative descriptions. The results indicate that the emotional valence of person names attached to person perception can be dynamically influenced by short descriptions of the target person, probably due to trait inference based on the provided behavioral descriptions.
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This study used a trait-state-occasion (TSO) model to isolate stable trait variance, occasion-specific state variance, and shared method related variance in a measure for leisure satisfaction in a Dutch nationally representative nine-year panel study. Findings indicate that satisfaction with leisure time is a consistently stronger indicator of overall leisure satisfaction than satisfaction with leisure activities. About half of the variance in leisure satisfaction is stable trait variance, with the remaining variance being mostly occasion-specific and to a lesser extent attributable to shared method variance and error. However, these findings depend on the age group we consider.Several socio-demographic variables relate directly to the trait aspect of leisure satisfaction. Our study underscores the importance of recognizing that over time leisure satisfaction measurements have considerable stable and more volatile elements and that one should control for shared method effects.
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This study presents an automated method for detecting and measuring the apex head thickness of tomato plants, a critical phenotypic trait associated with plant health, fruit development, and yield forecasting. Due to the apex's sensitivity to physical contact, non-invasive monitoring is essential. This paper addresses the demand for automated, contactless systems among Dutch growers. Our approach integrates deep learning models (YOLO and Faster RCNN) with RGB-D camera imaging to enable accurate, scalable, and non-invasive measurement in greenhouse environments. A dataset of 600 RGB-D images captured in a controlled greenhouse, was fully preprocessed, annotated, and augmented for optimal training. Experimental results show that YOLOv8n achieved superior performance with a precision of 91.2 %, recall of 86.7 %, and an Intersection over Union (IoU) score of 89.4 %. Other models, such as YOLOv9t, YOLOv10n, YOLOv11n, and Faster RCNN, demonstrated lower precision scores of 83.6 %, 74.6 %, 75.4 %, and 78 %, respectively. Their IoU scores were also lower, indicating less reliable detection. This research establishes a robust, real-time method for precision agriculture through automated apex head thickness measurement.
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When an adult claims he cannot sleep without his teddy bear, people tend to react surprised. Language interpretation is, thus, influenced by social context, such as who the speaker is. The present study reveals inter-individual differences in brain reactivity to social aspects of language. Whereas women showed brain reactivity when stereotype-based inferences about a speaker conflicted with the content of the message, men did not. This sex difference in social information processing can be explained by a specific cognitive trait, one's ability to empathize. Individuals who empathize to a greater degree revealed larger N400 effects (as well as a larger increase in γ-band power) to socially relevant information. These results indicate that individuals with high-empathizing skills are able to rapidly integrate information about the speaker with the content of the message, as they make use of voice-based inferences about the speaker to process language in a top-down manner. Alternatively, individuals with lower empathizing skills did not use information about social stereotypes in implicit sentence comprehension, but rather took a more bottom-up approach to the processing of these social pragmatic sentences.
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An extended professional identity theory is proposed to enhance interprofessional collaboration. The purpose of this study is to investigate whether comparative feedback on interprofessional interaction can decrease the degree of profession-based dominance and general dominance in mixed profession groups. This observational study comprised a randomized double-blind pretest-posttest control group design with 19 mixed profession groups (10 intervention and nine control groups, each with three dental and three dental hygiene students). All groups received reflective feedback during two consecutive two hour team development meetings. Intervention groups also received comparative feedback. Profession-based dominance concerned the sum of three observation items (conversational turntaking, dominance and contributing ideas) with a three-point scale: −1 = dental dominance, 0 = no dominance, +1 = dental hygiene dominance. Polychoric correlations confirmed positive associations with the latent trait and an unidimensional underlying structure. Observation items were internally consistent (α > .70). General dominance concerned the sum of absolute values of observation items with a minimum value of zero (no dominance) and the maximum value of three (strong dominance). A two-way factorial ANOVA was performed. The results revealed a significant interaction effect with regard to general dominance, F(1,17) = 6.630, p = 0.020 and large effect size (partial eta squared = 0.28). Comparative feedback on interprofessional interaction decreases general dominance in mixed profession groups.
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While Amazonian forests are extraordinarily diverse, the abundance of trees is skewed strongly towards relatively few ‘hyperdominant’species. In addition to their diversity, Amazonian trees are a key component of the global carbon cycle, assimilating and storing morecarbon than any other ecosystem on Earth. Here we ask, using a unique data set of 530 forest plots, if the functions of storing andproducing woody carbon are concentrated in a small number of tree species, whether the most abundant species also dominate carboncycling, and whether dominant species are characterized by specific functional traits.
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The carbon sink capacity of tropical forests is substantially affected by tree mortality. However, the main drivers of tropical tree death remain largely unknown. Here we present a pan-Amazonian assessment of how and why trees die, analysing over 120,000 trees representing > 3800 species from 189 long-term RAINFOR forest plots. While tree mortality rates vary greatly Amazon-wide, on average trees are as likely to die standing as they are broken or uprooted—modes of death with different ecological consequences. Species-level growth rate is the single most important predictor of tree death in Amazonia, with faster growing species being at higher risk. Within species, however, the slowest-growing trees are at greatest risk while the effect of tree size varies across the basin. In the driest Amazonian region species-level bioclimatic distributional patterns also predict the risk of death, suggesting that these forests are experiencing climatic conditions beyond their adaptative limits.These results provide not only a holistic pan-Amazonian picture of tree death but largescale evidence for the overarching importance of the growth–survival trade-off in driving tropical tree mortality.
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Camera trap technology has galvanized the study of predator-prey ecology in wild animal communities by expanding the scale and diversity of predator-prey interactions that can be analyzed. While observational data from systematic camera arrays have informed inferences on the spatiotemporal outcomes of predator-prey interactions, the capacity for observational studies to identify mechanistic drivers of species interactions is limited. Experimental study designs that utilize camera traps uniquely allow for testing hypothesized mechanisms that drive predator and prey behavior, incorporating environmental realism not possible in the lab while benefiting from the distinct capacity of camera traps to generate large data sets from multiple species with minimal observer interference. However, such pairings of camera traps with experimental methods remain underutilized. We review recent advances in the experimental application of camera traps to investigate fundamental mechanisms underlying predator-prey ecology and present a conceptual guide for designing experimental camera trap studies. Only 9% of camera trap studies on predator-prey ecology in our review mention experimental methods, but the application of experimental approaches is increasing. To illustrate the utility of camera trap-based experiments using a case study, we propose a study design that integrates observational and experimental techniques to test a perennial question in predator-prey ecology: how prey balance foraging and safety, as formalized by the risk allocation hypothesis. We discuss applications of camera trap-based experiments to evaluate the diversity of anthropogenic influences on wildlife communities globally. Finally, we review challenges to conducting experimental camera trap studies. Experimental camera trap studies have already begun to play an important role in understanding the predator-prey ecology of free-living animals, and such methods will become increasingly critical to quantifying drivers of community interactions in a rapidly changing world. We recommend increased application of experimental methods in the study of predator and prey responses to humans, synanthropic and invasive species, and other anthropogenic disturbances.
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This paper proposes and showcases a methodology to develop an observational behavior assessment instrument to assess psychological competencies of police officers. We outline a step-by-step methodology for police organizations to measure and evaluate behavior in a meaningful way to assess these competencies. We illustrate the proposed methodology with a practical example. We posit that direct behavioral observation can be key in measuring the expression of psychological competence in practice, and that psychological competence in practice is what police organizations should care about. We hope this paper offers police organizations a methodology to perform scientifically informed observational behavior assessment of their police officers’ psychological competencies and inspires additional research efforts into this important area.
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Player behavior during game play can be used to construct player models that help adapt the game and make it more fun for the player involved. Similarly in-game behavior could help model personality traits that describe people's attitudes in a fashion that can be stable over time and over different domains, e.g., to support health coaching, or other behavior change approaches. This paper demonstrates the feasibility of this approach by relating Need for Cognition (NfC) a personality trait that can predict the effectiveness of different persuasion strategies upon users to a commonly used game mechanic - hints. An experiment with N=188 participants confirmed our hypothesis that NfC has a negative correlation with the number of hints players follow during the game. Future work should confirm if adherence to hints can be used as a predictor of behavior in different games, and to find other game mechanics than hints, that help predict user traits.
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