Trait rumination in post-stress growth among Chinese college students: the chain mediating effect of distress disclosure and perceived social support

BackgroundRumination has emerged as a significant factor contributing to personal growth following periods of stress or trauma. The present study aimed to investigate the relationship between trait rumination and post-stress growth (PSG) within the context of Chinese college students who encounter mild stressors in their daily lives. Moreover, we aim to evaluate the potential mediating roles played by both distress disclosure and perceived social support in this dynamic relationship.MethodAll participants completed assessments using the Adolescent Self-Rating Life Events Checklist, Rumination Response Scale, Post-Stress Growth Inventory, Distress Disclosure Index, and Perceived Social Support Scale. Correlation and mediation analyses were conducted using SPSS PROCESS 4 MACRO.ResultsAll students reported experiencing mild psychological impacts as a result of negative life events in the past year and displayed moderate levels of PSG. There was no significant correlation observed between the effects of negative life events and PSG. Significant negative correlations were found between trait rumination and distress disclosure, perceived social support, and PSG. Distress disclosure and perceived social support jointly operated as sequential mediators in the relationship between trait rumination and PSG among all the participants. Qualitative analyses revealed different correlation patterns of high- versus low-ruminator.ConclusionTrait rumination affects PSG both directly and indirectly, through its influence on distress disclosure and perceived social support. Our results emphasize the significance of actively participating in distress disclosure and nurturing a robust sense of social support to counteract the detrimental effects of rumination on post-stress growth among Chinese college students

A Survey on Datasets for Decision-making of Autonomous Vehicle

Autonomous vehicles (AV) are expected to reshape future transportation systems, and decision-making is one of the critical modules toward high-level automated driving. To overcome those complicated scenarios that rule-based methods could not cope with well, data-driven decision-making approaches have aroused more and more focus. The datasets to be used in developing data-driven methods dramatically influences the performance of decision-making, hence it is necessary to have a comprehensive insight into the existing datasets. From the aspects of collection sources, driving data can be divided into vehicle, environment, and driver related data. This study compares the state-of-the-art datasets of these three categories and summarizes their features including sensors used, annotation, and driving scenarios. Based on the characteristics of the datasets, this survey also concludes the potential applications of datasets on various aspects of AV decision-making, assisting researchers to find appropriate ones to support their own research. The future trends of AV dataset development are summarized

Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation

The author wishes to extend sincere appreciation to Professor Lin Shi for the generous provision of equipment support, which significantly aided in the successful completion of this research. Furthermore, the author expresses gratitude to Associate Professor Ning Li and Teacher Wei Guan for their invaluable academic guidance and unwavering support. Their expertise and advice played a crucial role in shaping the direction and quality of this research.Peer reviewe

A Hint-Based Random Access Protocol for mMTC in 5G Mobile Network

With the increasing popularity of machine-type communication (MTC) devices, several new challenges are encountered by the legacy long term evolution (LTE) system. One critical issue is that a massive number of MTC devices trying to conduct random access procedures may cause significant collisions and long delays. In this work, we present a new random access mechanism by splitting the contention-based preambles in LTE into two logically disjoint parts, one for the user equipment (UE) being paged and the other for the UEs not being paged. Since the IDs of paged UEs are known by the base station, a novel hash-based random access, which we call hint, is possible. The main idea is to pre-allocate preambles to paged UEs in a contention-free manner and confines non-paged UEs to contend in a separate region. We further build a mathematical model to find the optimal ratio of pre-allocated preambles. Extensive simulations are conducted to validate our results

Effect of physical exercise under different intensity and antioxidative supplementation for plasma superoxide dismutase in healthy adults:systematic review and network meta-analysis

BACKGROUND: The dynamic balance between oxidation and anti-oxidation in the body’s internal environment has a significant meaning for human health. Physical exercise and antioxidative supplementation could affect the balance of oxidation and anti-oxidation systems. The evidence on the effects of physical exercise and antioxidative supplementation is mixed. AIMS: To identify the effects of physical exercise, antioxidative supplementation, and their combination on the dynamic balance between oxidation and anti-oxidation in different subgroups of healthy adults. METHODS: All studies which reported randomized controlled trials with healthy participants were screened and included from the databases of PubMed, Medline, Embase, and Ovid. All participants were reclassified according to their different daily life activities. All physical exercise interventions were reclassified according to the intensity. The effect size would be calculated in percent or factor units from the mean level change with its associated random-effect variance. RESULT: There were 27 studies included in this review. The agreement between authors by using The Cochrane Collaboration Risk of Bias Assessment Tool reached a kappa-value of 0.72. Maintaining a regular physical exercise routine in an appropriate intensity would be beneficial to the body’s anti-oxidative potential. Anti-oxidative supplementation could have some positive but limited effects on the body’s anti-oxidative status and complex interaction with physical exercise. CONCLUSION: Keeping a regular physical exercise routine and gradually increasing its intensity according to the individual’s daily life activity might be a better choice to maintain and enhancing the body’s antioxidation potential, only using anti-oxidative supplementation is not recommended. More research is needed to explore the best combination protocol. REGISTRATION NUMBER: CRD42021241995

An Open and Comprehensive Pipeline for Unified Object Grounding and Detection

Grounding-DINO is a state-of-the-art open-set detection model that tackles multiple vision tasks including Open-Vocabulary Detection (OVD), Phrase Grounding (PG), and Referring Expression Comprehension (REC). Its effectiveness has led to its widespread adoption as a mainstream architecture for various downstream applications. However, despite its significance, the original Grounding-DINO model lacks comprehensive public technical details due to the unavailability of its training code. To bridge this gap, we present MM-Grounding-DINO, an open-source, comprehensive, and user-friendly baseline, which is built with the MMDetection toolbox. It adopts abundant vision datasets for pre-training and various detection and grounding datasets for fine-tuning. We give a comprehensive analysis of each reported result and detailed settings for reproduction. The extensive experiments on the benchmarks mentioned demonstrate that our MM-Grounding-DINO-Tiny outperforms the Grounding-DINO-Tiny baseline. We release all our models to the research community. Codes and trained models are released at https://github.com/open-mmlab/mmdetection/tree/main/configs/mm_grounding_dino.Comment: 10 pages, 6 figure