Symmetry Shape Prior for Object Segmentation

Symmetry is a useful segmentation cue. We develop an algorithm for segmenting a single symmetric object from the background. Our algorithm is formulated in the principled global optimization framework. Thus we can incorporate all the useful segmentation cues in the global energy function, in addition to the symmetry shape prior. We use the standard cues of regular boundary and coherent object (background) appearance. Our algorithm consists of two stages. The first stage, based on seam carving, detects a set of symmetry axis candidates. Symmetry axis is detected by first finding image “seams” that are aligned with intensity gradients and then matching them based on pairwise symmetry. The second stage formulates symmetric object segmentation in discrete optimization framework. We choose the longest symmetry axis as the object axis. Object symmetry is encouraged through submodular long-range pairwise terms. These pairwise terms are submodular, so optimization with a graph cut is applicable. We demonstrate the effectiveness of symmetry cue on a new symmetric object dataset

Unlock Multi-Modal Capability of Dense Retrieval via Visual Module Plugin

This paper proposes Multi-modAl Retrieval model via Visual modulE pLugin (MARVEL) to learn an embedding space for queries and multi-modal documents to conduct retrieval. MARVEL encodes queries and multi-modal documents with a unified encoder model, which helps to alleviate the modality gap between images and texts. Specifically, we enable the image understanding ability of a well-trained dense retriever, T5-ANCE, by incorporating the image features encoded by the visual module as its inputs. To facilitate the multi-modal retrieval tasks, we build the ClueWeb22-MM dataset based on the ClueWeb22 dataset, which regards anchor texts as queries, and exact the related texts and image documents from anchor linked web pages. Our experiments show that MARVEL significantly outperforms the state-of-the-art methods on the multi-modal retrieval dataset WebQA and ClueWeb22-MM. Our further analyses show that the visual module plugin method is tailored to enable the image understanding ability for an existing dense retrieval model. Besides, we also show that the language model has the ability to extract image semantics from image encoders and adapt the image features in the input space of language models. All codes are available at https://github.com/OpenMatch/MARVEL

Generator condition monitoring method based on SAE and multi-source data fusion

With the increasing number of units involved in power system regulation and the increasing proportion of industrial load, a single data source has been unable to meet the accuracy requirements of online monitoring of unit conditions in the new power system. Based on the stacked autoencoder (SAE) network, combined with multi-source data fusion technology and adaptive threshold, a generator condition monitoring method is proposed. First, a SCADA–PMU data fusion method based on the weighted D–S evidence theory is proposed. Second, the auto-coding technology is introduced to build a stacked self-coding deep learning network model, extract the deep features of the training dataset, and build a generator fault detection model. Finally, by smoothing the reconstruction error and combining it with the trend change in the state monitoring quantity detected by the adaptive threshold, the fault judgment is realized. The simulation results show that, compared with the traditional method based on a single data source, the proposed method has higher robustness and accuracy, thus effectively improving the refinement level of generator condition monitoring

Association of psychological symptoms with job burnout and occupational stress among coal miners in Xinjiang, China: A cross-sectional study

ObjectiveThe study aimed to investigate the influencing factors of psychological symptoms in relation to job burnout and occupational stress among coal miners in Xinjiang, so as to provide data support for enterprises in an effort to help them identify internal psychological risk factors and improve the mental health of coal miners.MethodsA cross-sectional study was carried out. A total of 12 coal mines were selected using the stratified cluster random sampling method and 4,109 coal miners were investigated by means of online electronic questionnaires. The Symptoms Check List-90 (SCL-90), Chinese Maslach Burnout Inventory (CMBI), and Job Demand-Control (JDC) model were respectively used to measure the status of psychological symptoms, job burnout, and occupational stress among coal miners. The mediation analysis was performed through structural equation modeling (SEM) by using Analysis of Moment Structure (AMOS).ResultsThe prevalence of psychological symptoms was higher in the occupational stress group than in the non-occupational stress group, and increased with job burnout (P < 0.05). The multivariate logistic regression analysis results showed that mild (OR = 1.401, 95% CL: 1.165, 1.685), moderate (OR = 2.190, 95% CL: 1.795, 2.672), or severe levels of burnout (OR = 6.102, 95% CL: 3.481, 10.694) and occupational stress (OR = 1.462, 95% CL: 1.272, 1.679) were risk factors for psychological symptoms in coal miners. The results of structural equation modeling indicated that occupational stress (β = 0.11, P = 0.002) and job burnout (β = 0.46, P = 0.002) had significant positive direct effects on psychological symptoms, and job burnout was an intermediate variable between occupational stress and psychological symptoms.ConclusionHigh levels of job burnout and occupational stress were risk factors for psychological symptoms. Both occupational stress and job burnout had direct effects on psychological symptoms, and occupational stress could also have an indirect effect on coal miners' psychological symptoms through the intermediate variable of job burnout

The relationships between emerging adults self-efficacy and motivation levels and physical activity: a cross-sectional study based on the self-determination theory

ObjectivesThe study aims to examine the associations between exercise self-efficacy, motivation, physical activity, and body composition among emerging adults.DesignCross-sectional.MethodsA convenience sample of 147 emerging adults participated in the Releasing Weight (RELEW) project. The InBody720 analyzer was used to measure body composition, and the International Physical Activity Questionnaire-Short, the Shortened Physical Activity Self-Efficacy Scale, and the Treatment Self-Regulation Questionnaire were used to measure self-reported physical activity, self-efficacy, and motivation. Structural Equation Modeling was used to exam the complex relationships among multiple variables. in this study. The Partial least squares structural equation modeling analysis with bootstrapping in Smart PLS 3 was employed to explore the path coefficients and t-values for the relationships that were thought to exist. Significance was determined using a threshold of p < 0.05.ResultsThe mean age of 147 participants was 18.5 ± 1.87, of whom 51.7% were female, recruited for this study. Exercise self-efficacy has a significant positive correlation with exercise motivation (r = 0.220, p = 0.008) and physical activity (r = 0.279, p < 0.001). Exercise motivation does not demonstrate significant associations with physical activity (r = 0.094, p = 0.298). Utilizing SEM, the model explained 9.2% of exercise self-efficacy, 11.8% of physical activity, and 68.3% of body composition variance. Mediation analysis revealed that exercise self-efficacy partially mediated the relationship between exercise motivation and physical activity (β = 0.106, t = 2.538, p < 0.05), and physical activity partially mediated the relationship between exercise self-efficacy and body composition (β = −0.296, t = 4.280, p < 0.001).ConclusionThis study sheds light on the complex relationships among motivation, self-efficacy, physical activity and body composition during emerging adulthood. Our results highlight the mediating role of self-efficacy and its impact on physical activity behaviors, offering valuable insights for targeted interventions and policy development to improve health outcomes in this demographic

Development of a Novel Restrictive Medium for Monascus Enrichment From Hongqu Based on the Synergistic Stress of Lactic Acid and Ethanol

Hongqu is a famous fermented food produced by Monascus and has been used as food coloring, wine starters and food additives for thousands of years in China. Excellent Monascus strain is an important prerequisite for producing high-quality Hongqu. However, the isolation of Monascus pure culture from Hongqu samples is time-consuming and laborious because it is easily interfered by other microorganisms (especially filamentous fungi). Therefore, the development of restrictive medium for Monascus enrichment from Hongqu is of great significance for the preparation and screening of excellent Monascus strains. Results of this study showed that Monascus has good tolerance to lactic acid and ethanol. Under the conditions of tolerance limits [7.5% lactic acid (v/v) and 12.0% ethanol (v/v)], Monascus could not grow but it still retained the vitality of spore germination, and the spore activity gradually decreased with the increasing concentrations of lactic acid and ethanol. More interestingly, the addition of lactic acid and ethanol significantly changed the microbial community structure in rice milk inoculated with Hongqu. After response surface optimization, Monascus could be successfully enriched without the interference of other microorganisms when 3.98% (v/v) lactic acid and 6.24% (v/v) ethanol were added to rice milk simultaneously. The optimal enrichment duration of Monascus by the restrictive medium based on the synergistic stress of lactic acid and ethanol is 8∼24 h. The synergistic stress of lactic acid and ethanol had no obvious effects on the accumulation of major metabolites in the progeny of Monascus, and was suitable for the enrichment of Monascus from different types of Hongqu. Finally, the possible mechanisms on the tolerance of Monascus to the synergistic stress of lactic acid and ethanol were preliminarily studied. Under the synergistic stress of lactic acid and ethanol, the cell membrane of Monascus defends against lactic acid and ethanol into cells to some extent, and the superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GSH-Px) activities of Monascus were higher than those of other fungi, which significantly reduced the degree of lipid peroxidation of cell membrane, while secreting more amylase to make reducing sugars to provide the cells with enough energy to resist environmental stress. This work has great application value for the construction of Monascus strain library and the better development of its germplasm resources

The nudging effect of social norms on drivers’ yielding behaviour when turning corners

Drivers who do not give way to pedestrians are among&nbsp;the&nbsp;main causes&nbsp;of&nbsp;traffic crashes&nbsp;of&nbsp;motor vehicles and pedestrians in China. There is an urgent need to explore&nbsp;effective&nbsp;methods for improving drivers&#39;&nbsp;yielding&nbsp;behaviour. This study used eight kinds&nbsp;of&nbsp;social&nbsp;norm&nbsp;slogans to&nbsp;nudge&nbsp;drivers&rsquo;&nbsp;yielding&nbsp;behaviour&nbsp;and explored&nbsp;the&nbsp;influence&nbsp;of&nbsp;pedestrian characteristics and situational factors&nbsp;on&nbsp;drivers&rsquo; decision-making regarding giving way&nbsp;when&nbsp;turning&nbsp;right. By analysing 254 valid questionnaires, it was found that compared with static&nbsp;norms, injunctive&nbsp;norms&nbsp;and dynamic + static&nbsp;norms, positively worded dynamic&nbsp;norms&nbsp;have a better&nbsp;nudging&nbsp;effect&nbsp;on&nbsp;drivers&#39;&nbsp;yielding&nbsp;behaviour.&nbsp;The&nbsp;results&nbsp;of&nbsp;the&nbsp;conjoint analysis showed that&nbsp;social&nbsp;norms&nbsp;have&nbsp;the&nbsp;greatest impact&nbsp;on&nbsp;drivers&#39; decisions to&nbsp;yield&nbsp;(32.28%), followed by whether pedestrians comply with traffic rules (23.33%) and&nbsp;the&nbsp;age&nbsp;of&nbsp;pedestrians (18.40%). This study expands&nbsp;the&nbsp;application&nbsp;of&nbsp;social&nbsp;norms&nbsp;and provides a new perspective to promote positive&nbsp;behaviour&nbsp;among drivers.</p

Which Position is Better? A Survey on User Preference for Ambient Light Positions

With the development of intelligent automotive products, in-vehicle ambient lighting has received increasing attention, as shown by the growing number of models on the market with in-vehicle ambient lighting installed and the growing range of ambient lighting installation positions. Currently, there is no industry guideline for the appropriate position of ambient lights. Therefore, this study investigated user preference for 15 ambient light positions and explored whether driving experience, demographic variables, and ambient light usage experience influence user preference for ambient light positions. This study used two indicators to measure users&#39; preference for ambient light positions, aesthetic evaluation and favourite ranking. The results of 479 valid questionnaires showed that users&rsquo; preference for 15 ambient light positions can be divided into three categories. The ambient light positions with high preference were those surrounding the centre screen, armrest and centre screen bottom. Users had a low preference for the upper front windshield, steering wheel, bottom of left and right windows, A-pillar and rear view mirror. It was also found that users&#39; aesthetic evaluation of each position was influenced by gender and experience with ambient lighting. Male drivers, users with ambient lights currently installed in their vehicles and users with more frequent use of ambient lights showed a higher aesthetic evaluation for each position, indicating a more open attitude toward ambient lighting. The results of this study can provide a reference for the layout of in-vehicle ambient lighting, help relevant practitioners determine in-vehicle ambient light positions that better meet user needs, and suggest that ambient light layouts should be designed to better match the characteristics of consumer groups.</p