Search Results (691)

When periodic and other piecewise linear functions are introduced in a chaotic system with two-dimensional offset boosting for extra feedback, more patterns of diagonal distribution from coexisting attractors can be organized. In this study, the periodic function is implanted for attractor self-reproducing, while the signum function and absolute value function are integrated for the attractor symmetrization. For the offset interlocking across dimensions, the coexisting attractors can be reproduced in phase space with the shapes of “V” and “X”. Based on the FPGA platform, all the patterns are validated in a digital hardware environment confirming the consistency with simulation. Full article

Workplace toxicity in the tourism sector remains a widespread issue, particularly for hotel staff who are constantly suffering from verbal, emotional, or physical abuse. While previous research has primarily highlighted the negative consequences of abusive behavior, this study examines a different perspective—how abusive supervision may be associated with reduced helping behavior among hotel employees, with emotional contagion and self-esteem serving as key moderating and mediating variables. Based on the Conservation of Resources (COR) theory, the current paper suggests that abusive supervision causes people’s psychological resources to be depleted, which decreases their self-esteem and, in turn, their helpful behavior. Furthermore, it is revealed that emotional contagion can act as a moderator to amplify the detrimental association between abusive supervision and self-esteem. Data were gathered from frontline hotels employees. Employing structural equation modeling with SmartPLS 3, the findings reveal that abusive supervision was negatively related to both self-esteem and helping behaviors. Additionally, the correlation between helpful behavior and abusive supervision was strongly mediated by self-esteem. It is also shown that emotional contagion mitigated the detrimental relationship between abusive supervision and self-esteem, such that people with high emotional contagion experienced a stronger negative relationship. This paper advances our theoretical knowledge of workplace dynamics by expanding COR theory to justify how and why abusive supervision impairs pro-social behavior. From a practical standpoint, the findings underscore the significance of management behavior and emotional intelligence in service-oriented sectors. Employee self-esteem and cooperative workplace behavior may be preserved by interventions that deplete supervisory abuse and boost emotional resilience. Full article

Background: Interoception, the multifaceted perception of internal bodily signals, is crucial for homeostasis, emotional regulation, and overall well-being. Physical exercise significantly influences interoceptive mechanisms through its varied physiological, neurobiological, and psychological impacts. Despite its potential to enhance this internal sensing across its dimensions and foster adaptive behaviors like self-regulation, exercise remains an underutilized therapeutic approach. Objective: This narrative review explores the current understanding of the interplay between exercise and interoception, examining its resulting impact on both mental and physical health. Method: A comprehensive literature search was conducted on PubMed using keywords such as “interoception,” “exercise,” and “well-being.” Article selection prioritized empirical studies, reviews, and influential theoretical papers. The synthesis of the literature was performed through a thematic analysis, structured around three primary mechanisms: physiological changes, neurobiological adaptations, and psychological benefits. Key Findings: Engaging in exercise improves interoceptive function by inducing physiological changes, fostering neurobiological adaptations, and yielding psychological advantages such as reduced stress. This enhancement in internal bodily sensing, encompassing its various dimensions, and promotion of adaptive behaviors has notable consequences for well-being. Conclusions and Future Directions: Exercise presents a valuable and readily available means to enhance interoceptive processing and encourage adaptive behaviors, with substantial positive implications for well-being throughout life. Future studies should focus on identifying the most effective exercise approaches tailored to individual requirements and exploring their specific impact on different interoceptive dimensions. Integrating exercise into clinical treatment plans and public health strategies offers a promising path to substantially boost well-being. Full article

Background/Objectives: Ultrasound imaging is widely employed to assess kidney health and diagnose renal diseases. Accurate segmentation of renal structures in ultrasound images plays a critical role in the diagnosis and treatment of related kidney diseases. However, challenges such as speckle noise and low contrast still hinder precise segmentation. Methods: In this work, we propose an encoder–decoder architecture, named MAT-UNet, which incorporates two distinct attention mechanisms to enhance segmentation accuracy. Specifically, the multi-convolution pixel-wise attention module utilizes the pixel-wise attention to enable the network to focus more effectively on important features at each stage. Furthermore, the triple-branch multi-head self-attention mechanism leverages the different convolution layers to obtain diverse receptive fields, capture global contextual information, compensate for the local receptive field limitations of convolution operations, and boost the segmentation performance. We evaluate the segmentation performance of the proposed MAT-UNet using the Open Kidney US Data Set (OKUD). Results: For renal capsule segmentation, MAT-UNet achieves a Dice Similarity Coefficient (DSC) of 93.83%, a 95% Hausdorff Distance (HD95) of 32.02 mm, an Average Surface Distance (ASD) of 9.80 mm, and an Intersection over Union (IOU) of 88.74%. Additionally, MAT-UNet achieves a DSC of 84.34%, HD95 of 35.79 mm, ASD of 11.17 mm, and IOU of 74.26% for central echo complex segmentation; a DSC of 66.34%, HD95 of 82.54 mm, ASD of 19.52 mm, and IOU of 51.78% for renal medulla segmentation; and a DSC of 58.93%, HD95 of 107.02 mm, ASD of 21.69 mm, and IOU of 43.61% for renal cortex segmentation. Conclusions: The experimental results demonstrate that our proposed MAT-UNet achieves superior performance in multiple renal structure segmentation in ultrasound images. Full article

Central Environmental Protection Inspection (CEPI) is a major step in China’s environmental vertical supervision reform. With the multi-period Difference-in-Differences method, we assess the impact of CEPI on enterprise green transformation. In addition, we further explore the impact of enterprise environmental self-discipline. The results show that CEPI significantly promotes enterprise green transformation, and this effect on governance is further strengthened by environmental self-discipline. The synergistic governance effect of compound environmental regulation is pronounced, particularly in enterprises lacking government–enterprise relationships and in areas covered by CEPI “look back” initiatives and where local governments rigorously enforce environmental laws. The mechanism analysis reveals that CEPI mainly promotes enterprise green transformation by improving executive green cognition, boosting investment in environmental protection, and enhancing green innovation efficiency. This study provides a fresh perspective on analyzing the governance impact of CEPI and provides valuable insights for improving multi-collaborative environmental governance systems. Full article

This paper presents the multi-triangular ring and self-routing protocol (MTRSRP), which is a new decentralized strategy designed to boost throughput and network efficiency in multiring scatternets. MTRSRP comprises two primary phases: leader election and scatternet formation, which collaborate to establish an effective multi-triangular ring topology. In the leader election phase, nodes exchange broadcast messages to gather neighbor information and elect coordinators through a competitive process. The scatternet formation phase determines the optimal number of rings based on the coordinator’s collected node information and predefined rules. The master nodes then send unicast connection requests to establish piconets within the scatternet, following a predefined role table. Intra- and inter-bridge nodes were activated to interconnect the piconets, creating a cohesive multi-triangular ring scatternet. Additionally, MTRSRP incorporates a self-routing addressing scheme within the triangular ring architecture, optimizing packet transmission paths and reducing overhead by utilizing master/slave relationships established during scatternet formation. Simulation results indicate that MTRSRP with dual-bridge connectivity outperforms the cluster-based on-demand routing protocol and Bluetooth low-energy mesh schemes in key network transmission performance metrics such as the transmission rate, packet delay, and delivery ratio. In summary, MTRSRP significantly enhances throughput, optimizes routing paths, and improves network efficiency in multi-ring scatternets through its multi-triangular ring topology and self-routing capabilities. Full article

Background and Objectives: Depression is a leading cause of disability globally, with treatment challenges including limited access, stigma, and poor adherence. Gamification, which applies game elements such as points, levels, and storytelling into non-game contexts, offers a promising strategy to enhance engagement and augment traditional treatments. Our research is the first study designed to explore the implementation of gamification within the Malaysian context. The objective was to explore the feasibility of implementation of gamification as an adjunctive treatment for adults with depression. Materials and Methods: Focus group discussions were held with five mental health professionals and ten patients diagnosed with moderate depression. The qualitative component assessed perceptions of gamified interventions, while quantitative measures evaluated participants’ depressive and anxiety symptomatology. Results: Three key themes were identified: (1) understanding of gamification as a treatment option, (2) factors influencing its acceptance, and (3) characteristics of a practical and feasible intervention. Clinicians saw potential in gamification to boost motivation, support psychoeducation, and encourage self-paced learning, but they expressed concerns about possible addiction, stigma, and the complexity of gameplay for some patients. Patients spoke of gaming as a source of comfort, escapism, and social connection. Acceptance was shaped by engaging storylines, intuitive design, balanced difficulty, therapist guidance, and clear safety measures. Both groups agreed that gamification should be used in conjunction with standard treatments, be culturally sensitive, and be presented as a meaningful therapeutic approach rather than merely as entertainment. Conclusions: Gamification emerges as an acceptable and feasible supplementary approach for managing depression in Malaysia. Its success depends on culturally sensitive design, robust clinical oversight, and seamless integration with existing care pathways. Future studies should investigate long-term outcomes and establish guidelines for the safe and effective implementation of this approach. We recommend targeted investment into culturally adapted gamified tools, including training, policy development, and collaboration with key stakeholders to realistically implement gamification as a mental health intervention in Malaysia. Full article

Direct electrification and hydrogen utilization represent two key pathways for decarbonizing the glass industry, with their effectiveness subject to adequate furnace design and renewable energy availability. This study presents a techno-economic assessment for optimal solar energy integration in a representative 300 t/d oxyfuel container glass furnace with a specific energy consumption of 4.35 GJ/t. A mixed-integer linear programming formulation is developed to evaluate specific melting costs, carbon emissions, and renewable energy self-consumption and self-production rates across three scenarios: direct solar coupling, battery storage, and a hydrogen-based infrastructure. Battery storage achieves the greatest reductions in specific melting costs and emissions, whereas hydrogen integration minimizes electricity export to the grid. By incorporating capital investment considerations, the study quantifies the cost premiums and capacity requirements under varying decarbonization targets. A combination of 30 MW of solar plant and 9 MW of electric boosting enables the realization of around 30% carbon reduction while increasing total costs by 25%. Deeper decarbonization targets require more advanced systems, with batteries emerging as a cost-effective solution. These findings offer critical insights into the economic and environmental trade-offs, as well as the technical constraints associated with renewable energy adoption in the glass industry, providing a foundation for strategic energy and decarbonization planning. Full article

Parental school involvement (PSI) is an important contributor to children’s academic and overall positive development. Such activities as discussing schoolwork and tracking progress can boost children’s motivation and achievements. Although the multifaceted nature of PSI is widely recognized, there are limited reliable measures that comprehensively capture all its dimensions, particularly for children and adolescents. This study aims to develop a measure for assessing children and adolescents’ perceptions of parental involvement based on parent- and teacher-validated self-report measures—the Parental School Involvement Questionnaire—Children’s version (PSIQ-CV). A total of 537 children and adolescents (M_Age = 9.64, SD_Age = 2.43), mainly female (52.8%), from the south of Portugal participated in this study. An exploratory factor analysis (EFA, n = 150) and a confirmatory factor analysis (CFA, n = 387) were carried out. The EFA indicated a three-factor solution (i.e., support in learning activities, parent–school communication, and supervision), supported by the CFA, with good quality-of-fit indices (χ² = 225; df = 101; χ²/df = 2.23; CFI = 0.91; TLI = 0.89; RMSEA = 0.060 [CI: 0.049–0.070]). Our data confirmed that the PSIQ-CV has robust psychometric properties, with acceptable reliability and validity. The PSIQ-CV can be considered a relevant and valid tool for measuring the perception of parental school involvement among children and adolescents, in line with Epstein’s theoretical model, and useful for both researchers and practitioners. Full article

In complex dynamic environments, robotic arms face multiple challenges such as real-time environmental changes, high-dimensional state spaces, and strong uncertainties. Trajectory planning tasks based on deep reinforcement learning (DRL) suffer from difficulties in acquiring human expert strategies, low experience utilization (leading to slow convergence), and unreasonable reward function design. To address these issues, this paper designs a neural network-based expert-guided triple experience replay mechanism (NETM) and proposes an improved reward function adapted to dynamic environments. This replay mechanism integrates imitation learning’s fast data fitting with DRL’s self-optimization to expand limited expert demonstrations and algorithm-generated successes into optimized expert experiences. Experimental results show the expanded expert experience accelerates convergence: in dynamic scenarios, NETM boosts accuracy by over 30% and safe rate by 2.28% compared to baseline algorithms. Full article

Precisely recognizing diseases in tomato leaves plays a crucial role in enhancing the health, productivity, and quality of tomato crops. However, disease identification methods that rely on single-mode information often face the problems of insufficient accuracy and weak generalization ability. Therefore, this paper proposes a tomato leaf disease recognition framework FCMNet based on multimodal fusion, which combines tomato leaf disease image and text description to enhance the ability to capture disease characteristics. In this paper, the Fourier-guided Attention Mechanism (FGAM) is designed, which systematically embeds the Fourier frequency-domain information into the spatial-channel attention structure for the first time, enhances the stability and noise resistance of feature expression through spectral transform, and realizes more accurate lesion location by means of multi-scale fusion of local and global features. In order to realize the deep semantic interaction between image and text modality, a Cross Vision–Language Alignment module (CVLA) is further proposed. This module generates visual representations compatible with Bert embeddings by utilizing block segmentation and feature mapping techniques. Additionally, it incorporates a probability-based weighting mechanism to achieve enhanced multimodal fusion, significantly strengthening the model’s comprehension of semantic relationships across different modalities. Furthermore, to enhance both training efficiency and parameter optimization capabilities of the model, we introduce a Multi-strategy Improved Coati Optimization Algorithm (MSCOA). This algorithm integrates Good Point Set initialization with a Golden Sine search strategy, thereby boosting global exploration, accelerating convergence, and effectively preventing entrapment in local optima. Consequently, it exhibits robust adaptability and stable performance within high-dimensional search spaces. The experimental results show that the FCMNet model has increased the accuracy and precision by 2.61% and 2.85%, respectively, compared with the baseline model on the self-built dataset of tomato leaf diseases, and the recall and F1 score have increased by 3.03% and 3.06%, respectively, which is significantly superior to the existing methods. This research provides a new solution for the identification of tomato leaf diseases and has broad potential for agricultural applications. Full article

Background. Healthcare workers’ health can be influenced by physical, psychological, social, emotional, and work-related stress. MountainTherapy Activities (MTAs) are an integrated therapeutic approach that uses nature to enhance their well-being through group activities like hiking. This cross-sectional study examines well-being levels among Italian Departments of Mental Health workers who do or do not participate in MTAs. It hypothesizes that MTAs may reduce burnout, boost psychological resilience, and increase job satisfaction. Methods. The study involved 167 healthcare workers from 11 Italian Local Health Authorities, divided into MTA (who take part in MTA; n = 83) and non-MTA (who have never participated in MTA; n = 84) groups. They completed five validated questionnaires on psychological distress, burnout, resilience, job engagement, and psychological safety. Data were compared between groups, considering MTA frequency and well-being differences during MTAs versus workplace activities. Results. MTA participants scored higher in psychological well-being (t(117.282) = −1.721, p = 0.044) and general dysphoria (t(116.955) = −1.721, p = 0.042). Additionally, during MTAs, they showed greater job engagement (vigor: t(66) = −8.322, p < 0.001; devotion: t(66) = −4.500, p < 0.001; emotional involvement: t(66) = −8.322, p = 0.002) and psychological safety (general: t(66) = −5.819, p < 0.001; self-expression: t(66) = −5.609, p < 0.001) compared to other activities. Conclusions. MTAs can be considered a valid intervention for the promotion of the mental health of healthcare workers. Full article

Accurate heat load forecasting is essential for the efficiency of District Heating Systems (DHS). Still, it is challenged by the need to model long-term temporal dependencies and nonlinear relationships with weather and other factors. This study proposes a hybrid deep learning framework combining an attention-enhanced Neural Basis Expansion Analysis for Time Series (N-BEATS) model and eXtreme Gradient Boosting (XGBoost). The N-BEATS component, with a multi-head self-attention mechanism, captures temporal dynamics, while XGBoost models non-linear impacts of external variables. Predictions are integrated using an optimized weighted averaging strategy. Evaluated on a dataset from 103 heating units, the model outperformed 13 baselines, achieving an MSE of 0.4131, MAE of 0.3732, RMSE of 0.6427, and R² of 0.9664. This corresponds to a reduction of 32.6% in MSE, 32.0% in MAE, and 17.9% in RMSE, and an improvement of 5.1% in R² over the best baseline. Ablation studies and statistical tests confirmed the effectiveness of the attention mechanism and ensemble strategy. This model provides an efficient solution for DHS load forecasting, facilitating optimized energy dispatch and enhancing system performance. Full article

Background and Objectives: Orthodontic treatment aims to enhance dental aesthetics and function, yet many patients report dissatisfaction. This study was designed with the following objectives: To assess overall patient satisfaction during active orthodontic treatment; to identify key psychosocial and clinical predictors of satisfaction, including self-confidence, social experiences, and cost perception; to evaluate the impact of orthodontist–patient communication on satisfaction and perceived treatment outcomes; to explore the relationship between aesthetic improvement and willingness to undergo treatment again. Materials and Methods: A cross-sectional survey was conducted using structured questionnaires to assess satisfaction, pain perception, treatment expectations, and communication quality. Statistical analyses, including correlations and regression models, were used to identify predictors of satisfaction. The study included 450 orthodontic patients from the north-eastern region of Romania, undergoing active treatment at the time of data collection. Results: The strongest predictor of satisfaction was improved self-confidence and smile aesthetics (r = 0.62). Effective communication with orthodontists significantly increased satisfaction (r = 0.58, p = 0.002), while perceived high costs had a negative impact (r = −0.41). Pain and discomfort were common, with 90% of patients experiencing treatment-related pain, leading to reduced compliance. Social embarrassment due to braces also contributed to dissatisfaction (r = −0.47). Conclusions: Patient satisfaction with orthodontic treatment is primarily influenced by aesthetic improvements and effective communication. While enhanced smile perception boosts confidence, financial concerns and social discomfort may negatively affect the overall experience. Improving accessibility to treatment and providing comprehensive patient support are essential for optimizing patient satisfaction. Full article

Background: Vaccines that stimulate systemic and mucosal immunity to a level required to prevent SARS-CoV-2 infection and transmission are an unmet need. Highly protective hepatitis B and human papillomavirus nanoparticle vaccines highlight the potential of multivalent nanoparticle vaccine platforms to provide enhanced immunity. Here, we report the construction and characterization of self-assembling 60-subunit icosahedral nanoparticle SARS-CoV-2 vaccines using the bacterial enzyme lumazine synthase (LuS). Methods and Results: Nanoparticles displaying prefusion-stabilized SARS-CoV-2 spike ectodomains fused to the surface-exposed amino terminus of LuS were designed using structure-guided approaches. Negative stain-electron microscopy studies of purified nanoparticles were consistent with self assembly into 60-mer nanoparticles displaying 20 spike trimers. After two intramuscular doses, these purified spike-LuS nanoparticles elicited significantly higher SARS-CoV-2 neutralizing activity than spike trimers in vaccinated mice. Furthermore, intramuscular DNA priming and intranasal boosting with a SARS-CoV-2 LuS nanoparticle vaccine stimulated mucosal IgA responses. Conclusion: These data identify LuS nanoparticles as highly immunogenic SARS-CoV-2 vaccine candidates and support the further development of this platform against SARS-CoV-2 and its emerging variants. Full article