To Be or Not To Be Humorous? Cross Cultural Perspectives on Humor

open access articleHumor seems to manifest differently in Western and Eastern cultures, although little is known about how culture shapes humor perceptions. The authors suggest that Westerners regard humor as a common and positive disposition; the Chinese regard humor as a special disposition particular to humorists, with controversial aspects. In Study 1, Hong Kong participants primed with Western culture evaluate humor more positively than they do when primed with Chinese culture. In Study 2a, Canadians evaluate humor as being more important in comparison with Chinese participants. In Study 2b, Canadians expect ordinary people to possess humor, while Chinese expect specialized comedians to be humorous. The implications and limitations are discussed

Can you forgive? It depends on how happy you are

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper examined how individual group status and happiness influence forgiveness. In Study 1, happiness was treated as a trait difference: highly happy people, compared with very unhappy people, were found to be more willing to forgive murderers. More important, an interaction effect between happiness and group status on forgiveness was found, that is, highly happy people tended to be more forgiving when either ingroup or outgroup mem- bers were killed; unhappy people, however, tended to be less forgiving about murder when ingroup rather than outgroup members were killed. In Study 2, happiness was treated as an emotional state difference: happiness, rather than sadness, was found to bring greater forgiveness. Moreover, consistent with the interaction effect displayed in Study 1, happy participants tended to forgive more when ingroup or outgroup members were hurt; sad partici- pants tended to forgive less when ingroup members rather than outgroup members were hurt. Implications for connections between happiness, group membership, and forgiveness are discussed

How Belief in a Just World Benefits Mental Health: The Effects of Optimism and Gratitude

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Past research suggests that individuals’ belief in a just world (BJW) is closely connected with their mental health. To clarify the underlying mechanism, the current study proposes that BJW encourages optimism and gratitude which then mediates the relation- ship between BJW and mental health as indicated by subjective well-being (SWB) and depression. A sample of 1,200 undergraduates yields results indicating that (a) BJW influences optimism, gratitude, SWB, and depression after controlling for gender, age, income, and personality; (b) optimism and gratitude mediate BJW effects by increasing SWB and decreasing depression. The issues of BJW’s adaptive functions are discussed

ProphNet: Efficient Agent-Centric Motion Forecasting with Anchor-Informed Proposals

Motion forecasting is a key module in an autonomous driving system. Due to the heterogeneous nature of multi-sourced input, multimodality in agent behavior, and low latency required by onboard deployment, this task is notoriously challenging. To cope with these difficulties, this paper proposes a novel agent-centric model with anchor-informed proposals for efficient multimodal motion prediction. We design a modality-agnostic strategy to concisely encode the complex input in a unified manner. We generate diverse proposals, fused with anchors bearing goal-oriented scene context, to induce multimodal prediction that covers a wide range of future trajectories. Our network architecture is highly uniform and succinct, leading to an efficient model amenable for real-world driving deployment. Experiments reveal that our agent-centric network compares favorably with the state-of-the-art methods in prediction accuracy, while achieving scene-centric level inference latency.Comment: CVPR 2023 (Highlight

Green technology innovation and carbon emissions nexus in China: Does industrial structure upgrading matter?

Compared with traditional technological innovation modes, green technology innovation is more targeted for low carbon development and critical support for countries worldwide to combat climate change. The impact of green technology innovation on carbon emissions is considered in terms of fixed effect and mediating effect models through industrial structure upgrading. For this purpose, the sample dataset of 30 provincial administrative areas in China from 2008 to 2020 is employed. The results demonstrate that green technology innovation exerts significantly inhibitory effects on carbon emissions, whose conclusion still holds after removing municipalities and replacing the dependent variable. Industrial structure upgrading is vital for green technology innovation to diminish carbon emissions. There is significant regional heterogeneity in the effects of green technology innovation on carbon emissions, i.e., the direct and indirect impact of green technology innovation on carbon emission reduction is significant in the eastern-central area, but its effect is insignificant in the western region. Therefore, it is essential to realize carbon emission reduction by further bolstering green technology innovation and accelerating industrial structure upgrading to fulfill the synergy of technology and structure

Enhanced Heavy Oil Recovery in Mild Conditions by S

The important key of heavy oil efficient exploring is to decrease the viscosity and increase the flowability. Solid acid catalyst is one of the commonly used catalysts to reducing the viscosity of heavy oil, but good dispersion in oil phase and better catalytic activity are difficult to achieve. Herein, ZrO2-TiO2 was selected as the fundamental catalyst because of its superior solid superacid properties, and CTAB was selected as the surfactant package coat to help enhance catalytic activity. The as-prepared catalysts were characterized systematically by TEM, XRD, FTIR, and N2 adsorption-desorption isotherms measurement. The reduction efficiency of the heavy oil viscosity achieved as high as 66.3% at 180°C. At the same time, the portion of asphaltenes and resins slipped down by 4.93% and 3.78%, respectively, while saturated and aromatic hydrocarbon component increased by 5.37% and 3.26%, respectively, indicating that our catalyst showed a good activity for reducing the viscosity and improving the quality of heavy crude oil

Practical Deep Dispersed Watermarking with Synchronization and Fusion

Deep learning based blind watermarking works have gradually emerged and achieved impressive performance. However, previous deep watermarking studies mainly focus on fixed low-resolution images while paying less attention to arbitrary resolution images, especially widespread high-resolution images nowadays. Moreover, most works usually demonstrate robustness against typical non-geometric attacks (\textit{e.g.}, JPEG compression) but ignore common geometric attacks (\textit{e.g.}, Rotate) and more challenging combined attacks. To overcome the above limitations, we propose a practical deep \textbf{D}ispersed \textbf{W}atermarking with \textbf{S}ynchronization and \textbf{F}usion, called \textbf{\proposed}. Specifically, given an arbitrary-resolution cover image, we adopt a dispersed embedding scheme which sparsely and randomly selects several fixed small-size cover blocks to embed a consistent watermark message by a well-trained encoder. In the extraction stage, we first design a watermark synchronization module to locate and rectify the encoded blocks in the noised watermarked image. We then utilize a decoder to obtain messages embedded in these blocks, and propose a message fusion strategy based on similarity to make full use of the consistency among messages, thus determining a reliable message. Extensive experiments conducted on different datasets convincingly demonstrate the effectiveness of our proposed {\proposed}. Compared with state-of-the-art approaches, our blind watermarking can achieve better performance: averagely improve the bit accuracy by 5.28\% and 5.93\% against single and combined attacks, respectively, and show less file size increment and better visual quality. Our code is available at https://github.com/bytedance/DWSF.Comment: Accpeted by ACM MM 202