In 1979 Reeder and Brewer reported that people make stronger attributions for negative behaviors than for positive ones, following Hastorf and Cantril's statement that people are motivated to maintain positive self-views. The present study tested whether 67 participants would make stronger self-attributions for negative behaviors than for positive ones by having them indicate the number of times that they had to engage in a specific behavior before it would become a trait they possess. Analysis confirmed that participants make stronger self-attributions for negative behaviors than for positive behaviors.
Background: The proliferation of generative artificial intelligence (AI), such as ChatGPT, has added complexity and richness to the virtual environment by increasing the presence of AI-generated content (AIGC). Although social media platforms such as TikTok have begun labeling AIGC to facilitate the ability for users to distinguish it from human-generated content, little research has been performed to examine the effect of these AIGC labels.
Objective: This study investigated the impact of AIGC labels on perceived accuracy, message credibility, and sharing intention for misinformation through a web-based experimental design, aiming to refine the strategic application of AIGC labels.
Science and Technology on Aerospace Chemical Power Laboratory, Laboratory of Emergency Safety and Rescue Technology, Hubei Institute of Aerospace Chemotechnology, Xiangyang 441003, China.
Doped semiconductors are often used to improve photocatalytic efficiency and address the challenges of easy recombination of electron-hole pairs and poor photoluminescence. However, the reproducibility and complexity of experimental studies result in time-consuming and less cost-effective studies, and it is difficult to gain insights into the intrinsic properties of doped photocatalysts to control their performance. Introducing a machine learning approach, we constructed a photocatalytic model of transition-metal- and rare earth metal-ion-doped γ-BiMoO.
The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China; Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China;; Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China. Electronic address:
In the circulatory system, the microenvironment surrounding cancer cells is complex and involves multiple coupled factors. We selected two core physical factors, shear stress and hydraulic resistance, and constructed a microfluidic device with dual negative inputs to study the trade-off movement behavior of cancer cells when facing coupled factors. We detected significant shear stress escape phenomena in the MDA-MB-231 cell line and qualitatively explained this behavior using a cellular force model.
The effects of guanidinium hydrochloride (GdmCl) on two intrinsically disordered proteins (IDPs) are investigated using simulations of the self-organized polymer-IDP (SOP-IDP) model. The impact of GdmCl is taken into account using the molecular transfer model (MTM). We show that due to the dramatic reduction in the stiffness of the highly charged Prothymosin-α (ProTα) with increasing concentration of GdmCl ([GdmCl]), the radius of gyration () decreases sharply until about 1.
Nowadays, with the widespread use of the Internet, cyberbullying has become a pervasive threat to people. This study aimed to create a structural model of cyberbullying based on dark personality traits, with empathy as a mediating factor among students. A total of 360 students of the Mohaghegh Ardabili University were included using the multistage random sampling method.
