Search Results (60,206)

Deep learning is becoming the most widely used technology for multi-sensor data fusion. Semantic correspondence has recently emerged as a foundational task, enabling a range of downstream applications, such as style or appearance transfer, robot manipulation, and pose estimation, through its ability to provide robust correspondence in RGB images with semantic information. However, current representations generated by self-supervised learning and generative models are often limited in their ability to capture and understand the geometric structure of objects, which is significant for matching the correct details in applications of semantic correspondence. Furthermore, efficiently fusing these two types of features presents an interesting challenge. Achieving harmonious integration of these features is crucial for improving the expressive power of models in various tasks. To tackle these issues, our key idea is to integrate depth information from depth estimation or depth sensors into feature maps and leverage learnable weights for feature fusion. First, depth information is used to model pixel-wise depth distributions, assigning relative depth weights to feature maps for perceiving an object’s structural information. Then, based on a contrastive learning optimization objective, a series of weights are optimized to leverage feature maps from self-supervised learning and generative models. Depth features are naturally embedded into feature maps, guiding the network to learn geometric structure information about objects and alleviating depth ambiguity issues. Experiments on the SPair-71K and AP-10K datasets show that the proposed method achieves scores of 81.8 and 83.3 on the percentage of correct keypoints (PCK) at the 0.1 level, respectively. Our approach not only demonstrates significant advantages in experimental results but also introduces the depth awareness module and a learnable feature fusion module, which enhances the understanding of object structures through depth information and fully utilizes features from various pre-trained models, offering new possibilities for the application of deep learning in RGB and depth data fusion technologies. We will also continue to focus on accelerating model inference and optimizing model lightweighting, enabling our model to operate at a faster speed. Full article

Globally, the construction industry is facing a severe labor shortage, and attracting and retaining workers has become a pressing challenge. This study examined the effect of rehabilitation exercise on construction workers’ willingness to sustain their careers through a questionnaire survey of 479 construction workers using a quantitative research methodology. It aims to reveal how the self-efficacy, perceived usefulness, and self-regulation of rehabilitation exercise affect construction workers’ occupational sustainability through physical and psychological recovery. The results of the study show that (1) the rehabilitation exercise self-efficacy and perceived usefulness of recovery exercise positively affect construction workers’ career sustainability intentions and (2) psychological recovery and physical recovery play parallel mediating roles in the effects of rehabilitation exercise self-efficacy, the perceived usefulness of recovery exercise, and self-regulation of recovery exercise on construction workers’ career sustainability intentions. The findings suggest that improving the physical and psychological capital of construction workers through recovery exercise can effectively enhance their career commitment and willingness to be sustainable. This study provides a reference for the design of more comprehensive and systematic rehabilitation and health management programs in the future and offers suggestions from the perspective of recovery exercise for the development of sustainable construction workers. Full article

Classical viscoelastic models usually only consider the motion of chain segments and the motion of the entire molecular chain; therefore, they will cause inevitable errors when modeling self-healing vitrimer materials with many group movements. In this paper, a group-enriched viscoelastic model is proposed for self-healing vitrimers where the group effect cannot be neglected. We synthesize a specific damping vitrimer with many dangling chains, surpassing the limited loss modulus of conventional engineering materials. Due to the dangling chains, the damping capability can be improved and the group effect cannot be neglected in the synthesized damping vitrimer. The group-enriched viscoelastic model accurately captures the experimental damping behavior of the synthesized damping vitrimer. Our results indicate that the group-enriched viscoelastic model can improve the accuracy of classical viscoelastic models. It is shown that the group effect can be ignored at low frequencies since the chain segments have sufficient time for extensive realignment; however, the group effect can become significant in the case of high frequency or low temperature. Full article

Self-incompatibility (SI) is a complex mechanism that prevents plants from self-fertilizing to preserve and promote genetic variability. The angiosperm species have developed two different SI systems, the sporophytic (SSI) and the gametophytic (GSI) systems. SI is a significant impediment to steady fruit production in fruit tree species of the Rosaceae. In Rosaceae, GSI is genetically regulated via a single locus, named the ‘S-locus’, which includes a minimum of two polymorphic and relatively intercorrelated S genes: a pistil-expressed S-RNase gene and several pollen-expressed SFBB (S-locus F-Box Brothers) or SFB (S haplotype-specific F-box protein). This necessitates the interaction of S-RNases with the male determinants. Although genetic and molecular analyses of S genes have shown that mutations in both pistils and pollen-specific components induce self-compatibility in many species and cultivars, other genes or molecules outside the S-locus can co-participate in the male gamete rejection in GSI. However, we highlight and synthesize the most recent knowledge on different mechanisms of GSI in Rosaceae in this current review. Full article

Childhood nutrition is a cornerstone of long-term health, yet many children exhibit reluctance to consume healthy foods such as vegetables. This aversion can be influenced by various factors, including food neophobia and the sensory and visual appeal of the foods that are being presented. Hence, understanding how visual cues affect children’s willingness to eat can provide insights into effective strategies to enhance their dietary habits. This research explores the influence of visual cues on the dietary behaviors of children aged 9 to 12, their willingness to consume and request healthy foods such as vegetables, within the context of challenges such as food neophobia. This study examines how intrinsic cues (e.g., vegetable characteristics) and extrinsic cues (e.g., the plate’s color and shape) affect children’s liking and emotional responses, impacting their willingness to eat and request purchases from parents. Conducted using a sample of 420 children, this cross-sectional study reveals that attributes such as a plate’s color and shape significantly affect food-related behaviors and emotions. A validated and reliable self-administered questionnaire was employed. Independent t-tests and ANOVA were used to test the differences between gender and food neophobia, while Spearman correlations were used for correlation analysis. Visual cues served as the independent variables, liking and emotional responses as the mediating variables, and willingness behaviors as the dependent variable. Hierarchical regression analyses were conducted to explore the relationships among intrinsic cues, extrinsic cues, and the mediating effect of liking and emotional responses. Findings show that boys prefer blue and triangular plates, while girls prefer pink plates, generating more positive emotions. Children with food neophobia initially experience aversion, but this can be reduced by enhancing sensory appeal and emotional engagement. The findings underscore the importance of leveraging visual cues and fostering positive emotional experiences to encourage healthier eating habits and increase children’s acceptance and purchase of nutritious foods. Full article

Walking, a basic physical movement of the human body, is a resource for observers in forming interpersonal impressions. We have previously investigated the expression and perception of the attractiveness of female gaits. In this paper, drawing on our previous research, additional analysis, and reviewing previous studies, we seek to deepen our understanding of the function of gait attractiveness. First, we review previous research on gait as nonverbal information. Then, we show that fashion models’ gaits reflect sociocultural genderlessness, while nonmodels express reproductive-related biological attractiveness. Next, we discuss the functions of gait attractiveness based on statistical models that link gait parameters and attractiveness scores. Finally, we focus on observers’ perception of attractiveness, constructing a model of the visual information processing with respect to gait attractiveness. Overall, our results suggest that there are not only biological but also sociocultural criteria for gait attractiveness, and men and women place greater importance on the former and latter criteria, respectively, when assessing female gait attractiveness. This paper forms a major step forward in neuroaesthetics to understand the beauty of the human body and the generation of biological motions. Full article

The operational stability of the power transformer is essential for maintaining the symmetry, balance, and security of power systems. Once the power transformer fails, it will lead to heightened instability within grid operations. Accurate prediction of oil temperature is crucial for efficient transformer operation. To address challenges such as the difficulty in selecting model hyperparameters and incomplete consideration of temporal information in transformer oil temperature prediction, a novel model is constructed based on the improved whale optimization algorithm (IWOA) and long short-term memory (LSTM) neural network with self-attention (SA) mechanism. To incorporate holistic and local information, the SA is integrated with the LSTM model. Furthermore, the IWOA is employed in the optimization of the hyper-parameters for the LSTM-SA model. The standard IWOA is improved by incorporating adaptive parameters, thresholds, and a Latin hypercube sampling initialization strategy. The proposed method was applied and tested using real operational data from two transformers within a practical power grid. The results of the single-step prediction experiments demonstrate that the proposed method significantly improves the accuracy of oil temperature prediction for power transformers, with enhancements ranging from 1.06% to 18.85% compared to benchmark models. Additionally, the proposed model performs effectively across various prediction steps, consistently outperforming benchmark models. Full article

Women’s participation and leadership in technology and entrepreneurship are crucial for advancing innovation and ensuring inclusive economic development. Despite progress in gender equality, women in tech face challenges like under-representation and systemic biases. This research delves into the multifaceted experiences of women in tech innovation and entrepreneurship, highlighting the barriers they face and the strategies they use to overcome them. This study used a qualitative, observational design with semi-structured interviews and thematic analysis to explore the experiences and perceptions of entrepreneurial women in the Science, Technology, Engineering, and Mathematics (STEM) field. It was possible to conclude that entrepreneurial women exhibit a strong sense of autonomy, competence, and leadership, enabling them to manage their ventures independently and effectively. Also, the success of entrepreneurial women is multifaceted, combining personal fulfilment, professional achievements, and financial stability, with positive feedback and recognition playing a key role. Building strong social and supportive relationships is vital for entrepreneurial women, providing a sense of belonging, community, and emotional support. In this context, to empower women in STEM and entrepreneurship, Higher Education Institutions (HEIs) should promote entrepreneurship as a career path, provide practical and value-based education, and foster a work environment of trust, communication, and continuous learning. Full article

The pro-environmental behavior of tourists is an important guarantee for the sustainable development of ecotourism scenic spots. This article is based on 806 tourist survey data from two ecotourism scenic spots, making use of exploratory factor analysis (EFA) and the structural equation model (SEM) to explore the impact of tourist experience quality on tourists’ pro-environmental behavior. The research findings indicate that (1) the quality of the tourist experience is an important factor affecting the formation of place attachment; (2) the quality of tourism experience directly and positively affects place dependence, and indirectly affects place identity through the mediating factor of place dependence; and (3) the direct impact of tourist experience quality on tourists’ pro-environmental behavior is significant, with place attachment playing a mediating role. This article provides inspiration for scenic spots to encourage tourists to engage in pro-environmental behavior. In the process of stimulating tourists to engage in pro-environmental behaviors, ecotourism scenic spots should pay more attention to the tourist experiences and emotional experiences. Scenic spots should make more efforts to improve the quality of the tourist experience, so that tourists can develop a sense of dependence on ecotourism scenic spots, gradually form self-identification with the scenic spots, and engage in environmentally friendly behavior, helping to achieve the sustainable development of ecotourism scenic spots. Full article

Bacterial resistance and persistence in food environments are major concerns for the industry, which constantly seeks new strategies to reduce microbial contamination. Rhamnolipids (RL) biosurfactants are considered sustainable and green alternatives to synthetics; furthermore, they have demonstrated potential for controlling various foodborne pathogens. Food environments are typically exposed to diverse pH, solutes, temperatures, and water activity (a_w) levels that may favor the survival of pathogens. Therefore, it is crucial to consider these factors in evaluating the performance of novel antimicrobials. Our study examined the influence of pH and sucrose on the antimicrobial activity of RL against both planktonic and biofilm of Listeria monocytogenes. We found that the presence of sucrose can enhance the antimicrobial effectiveness of RL against both planktonic and sessile bacteria. The addition of sugar particularly improved RL action at pH 6 and 7. Moreover, we observed that the type and size of RL self-assembly structures depend on the pH and sucrose concentration. These findings suggest potential for developing RL-based innovative methods to control L. monocytogenes in sugar-rich or -low a_w foods and environments. Full article

The current study is focused on devising treated diatomite interfaces with the robustness and boiling water resistance necessary for high-temperature purposes. This work describes the synthesis methodology of the diatomite-based coatings, which followed the production of a composite formulation composed by treated diatomite powder dispersed in an epoxy resin matrix. After its preparation, the suspension was applied via the dip-coating technique over AISI-304 stainless-steel foils, which, after being air dried, underwent a post-curing treatment. Also, the interfaces were characterized by diverse techniques such as scanning electron microscopy and optical tensiometry. Apart from this, their thermophysical properties like thermal conductivity were also determined. Further, the physical and chemical durability of the interfaces was also evaluated via the elaboration of robustness tests including abrasion resistance, adhesion strength, solid impact resistance, and solvent resistance. The results showed satisfactory resistant interfaces, and with a wettability characterized by contact angles superior to 150°. Also, the interfaces confirmed improved durability when immersed in boiling water at 1 atm, since their wetting characteristics and durability remained nearly unaltered after 762 h of testing. Additionally, the synthesized interfaces possessed self-cleaning ability and chemical and thermal shock aging resistance. Generally, the fundamental outcomes of this work point out the suitability of the produced diatomite-based interfaces to be explored in high-temperature applications like flow boiling, pool boiling, and condensation. In terms of practicality, the method of preparation of the interfaces was a relatively easy and rapid approach to obtaining enhanced wettability and resilient interfaces, and with the required adaptations like the ratios between the raw materials, its suitability for large-scale applications makes this an appealing option. Full article

To solve the problem of large residual deformation and high repair cost of traditional frame structures after an earthquake, a new type of assembled shuttle-shaped self-centering mild steel energy dissipation brace (ASSSEDB) with stable stiffness, material saving, and easy replacement was proposed. The plastic deformation of mild steel is used to dissipate energy, and the disc spring system provides a reset function. Based on the working mechanism of energy dissipation brace, a restoring force model for the ASSSEDB was established, and then the numerical analysis was carried out by ANSYS to verify the accuracy of the proposed model. The results confirm that the ASSSEDB has stable energy dissipation ability and a resetting function, with a full hysteresis curve. The finite element analysis results align well with the developed restoring force model, and the maximum deviations of initial stiffness and ultimate capacity are, respectively, 1.4% and 2.3%, which indicates that the established restoring force model can provide a theoretical basis for design of the ASSSEDB. Furthermore, the time history analysis was carried out to assess the seismic performance of a six-story steel frame structure using the proposed ASSSEDB. The results show that compared with the steel frame structure with BRBs, the proposed ASSSEDB can decrease the residual deformation of structures by up to 93.41%. The self-centering ratio of the ASSSEDB is crucial in controlling residual deformation of structures, and it is recommended to be greater than 1.0. Full article

In the context of high academic pressure and inadequate physical activity (PA) among adolescents, it is important to study how the physical environment and students’ perceptions affect their physical activity during school recess. An empirical study was conducted in four secondary schools in Xi’an to gather data on students’ physical activity using DJI Mini Drone recordings and self-reported questionnaires. Three physical activity indices—concentration, type richness and intensity—were visualized and quantified for intercomparison. This study found that physical environmental factors such as the building shape complexity and green space proportion significantly affected the PA concentration and intensity indices, whereas the campus area per student, the average distance to PA facilities and the number of PA facilities indicated a strong correlation with the PA richness index at the school level. Additionally, perceived environmental factors like space safety, facilities enjoyment and visual accessibility exerted influence on the PA intensity and frequency at the individual level. The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. By incorporating spatial, perceptual and behavioral aspects, this approach provides an efficient and integrated analytical methodology to promote adolescents’ health in school. Full article

Background/Objectives: Ethnic identity development is associated with positive mental health in young adults from ethnic minority groups. How a sense of belonging and attachment to one’s ethnic culture is related to personal mental health recovery remains unexplained. This study examines the experiences of ethnic minority young adults in the U.S. to understand the aspects of culture and identity development that are relevant to their recovery processes. Methods: Young adults who were living with chronic mental disorders were recruited from four rehabilitation programs. Interviews produced quantitative and qualitative data. An explanatory sequential mixed methods design was used to integrate the qualitative findings from a sub-group of young adults (n = 44) with the results from the quantitative study. Directed content analysis was used to analyze the qualitative data, and the integrated data were analyzed in joint displays. Results: The prominent themes characterizing ethnic identity development in personal recovery were (a) cultural history, traditions, and values; (b) mental illness stigma within the ethnic community; and (c) bias and discrimination in mental health services. Young adults with high ethnic identity development reported having more support from family, but they also described experiences with stigma and racism. Conclusions: The integrated results suggest that ethnic identity development promotes mental health recovery in minoritized young adults through social support and improved well-being and resilience. Experiences of intersectional stigma and structural racism associated with ethnic identity can interfere with self-determination and access to care among minoritized Hispanic/Latine, Black, and multiracial young adults in the U.S. Full article

Ginseng has anti-hyperglycemic effects. Gintonin, a glycolipoprotein derived from ginseng, also stimulates insulin release from pancreatic beta cells. However, the role of gintonin in glucose metabolism within skeletal muscle is unknown. Here, we showed the effect of gintonin on glucose uptake, glycogen content, glucose transporter (GLUT) 4 expression, and adenosine triphosphate (ATP) content in C2C12 myotubes. Gintonin (3–30 μg/mL) dose-dependently stimulated glucose uptake in myotubes. The expression of GLUT4 on the cell membrane was increased by gintonin treatment. Treatment with 1–3 μg/mL of gintonin increased glycogen content in myotubes, but the content was decreased at 30 μg/mL of gintonin. The ATP content in myotubes increased following treatment with 10–100 μg/mL gintonin. Gintonin transiently elevated intracellular calcium concentrations and increased the phosphorylation of extracellular signal-regulated kinase (ERK). Gintonin-induced transient calcium increases were inhibited by treatment with the lysophosphatidic acid receptor inhibitor Ki16425, the phospholipase C inhibitor U73122, and the inositol 1,4,5-trisphosphate receptor antagonist 2-aminoethoxydiphenyl borate. Gintonin-stimulated glucose uptake was decreased by treatment with U73122, the intracellular calcium chelator 1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid tetra(acetoxymethyl) ester, and the ERK inhibitor PD98059. These results show that gintonin plays a role in glucose metabolism by increasing glucose uptake through transient calcium increases and ERK signaling pathways. Thus, gintonin may be beneficial for glucose metabolism control. Full article