In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental stage or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. Additionally, four TCP genes exhibited in silico binding with cold stress-related miRNA319s. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics.

The cultivated passion fruit (Passiflora edulis) is a diploid plant (2n=2x=18) and is an important fruit tree in southern China. However, the occurrence and spread of stem rot in passion fruit severely impact its yield and quality. This study aims to construct a high-density genetic linkage map and identify the quantitative trait locus (QTL) and candidate genes associated with stem rot resistance in passion fruit. In this study, we used an HG and ZG7 hybrid to develop a BC1F1 population consisting of 158 individuals. Take a previously published passion fruit genome as reference, a high-density genetic linkage map was constructed with 1,180,406 single nucleotide polymorphisms (SNPs). The map contains 9 linkage groups, covering a total genetic distance of 1559.03 cM, with an average genetic distance of 311.81 cM. The average genetic distance between 4206 bins was 0.404 cM, and the average gap length was 10.565 cM. The collinearity correlation coefficient between the genetic map and the passion fruit genome was 0.9994. Fusarium solani was used to infect the BC1F1 population, and the resistance to stem rot showed a continuous distribution. A QTL, qPSR5, was identified in the 145.878-152.951 cM region on the 5th linkage group. We performed RNA-seq and RT-qPCR to analyze the expression levels of predicted genes in the candidate region and identified ZX.05G0020740 and ZX.05G0020810 as ideal candidate genes for stem rot resistance in passion fruit. The findings in this study not only lay the foundation for cloning the qPSR5 responsible for stem rot resistance but also provide genetic resources for the genetic improvement of passion fruit.

The Burnout syndrome is a negative experience for the athlete development and it has been demonstrated that it gets worse when a sport is practiced in an obsessive way. The interventions about a positive vision through the sport could be a protective factor to boost the athlete’s wellbeing. The aim of the present study was to analyze the mediator effect from social support, the relationship between the burnout, positivity and passion in young Mexican athletes. The sample was composed by 452 Mexican athletes, males and females from 12 to 18 years of age (M = 16.29, SD = 1.66). Participants answered the Athlete Burnout Questionnaire, The Scale of the Social Support Perceived by Athletes, the Passion Scale and the Positivity Scale. The results of structural equation modeling showed the model presented a good adjustment (χ2 = 813.507; df = 229; χ2 /df = 3.552; p < 0.01; CFI = 0.93; TLI = 0.91; IFI = 0.93; NFI = 0.91; RMSEA = 0.07). The positivity and harmonious passion presented direct and indirect effects over the burnout, being the perceived social support the mediator variable of the indirect effects. However, the effect of the obsessive passion mediated by the perceived social support did not resulted significant.

This paper provides a narrative review of previous research on effort-reward imbalance and passion exploitation, and provides a perspective for future research. Previous research has shown that ERI can cause work stress, negative economic behavior such as job turnover, and illnesses such as metabolic syndrome. Previous research also claims that loyal and generous people, as well as young people and women, are more likely to be targets of passion exploitation. However, there are unresolved issues in previous research, such as (i) the mechanism by which effort-reward imbalance leads to stress and illness, (ii) there is a lack of research on what types of jobs are more likely to experience imbalance, and (iii) there is a lack of research on what level of imbalance is acceptable, and therefore further research is required. To this end, this study recommends addressing these challenges through the integration of ERI and passion exploitation theory.

Manufacturing enterprises are increasingly compelled to pursue innovative solutions to environmental issues. Addressing such issues requires mindful leadership to support employees and organizations in maintaining awareness during complex situations, thereby promoting environmental sustainability. Drawing on social information processing theory, this study theorizes and tests the relationships mindfulness leadership, employee moral reflectiveness, environmental passion, and employee green creativity. To test the model, we utilize a two-wave multi-source dataset comprising 215 workers from manufacturing firms in China. The findings demonstrate that mindful leadership is positively related to employee green creativity. Additionally, our research reveals that both moral reflectiveness and environmental passion serve as mediators in linking mindful leadership to employee green creativity. Crucially, our empirical analysis suggests a serial mediation model, examining the sequential role of moral reflectiveness and environmental passion in the relationship between mindful leadership and employee green creativity. The findings provide a new viewpoint on employees' eco-friendly behaviors and have practical implications for improving environmental sustainability within organizations.