Search Results (85,456)

This study proposes an innovative Thermodynamic Activity Controlled Homogeneous Charge Compression Ignition (TAC-HCCI) strategy for diesel–natural gas dual-fuel engines, aiming to achieve high thermal efficiency while maintaining low emissions. By employing numerical simulation methods, the effects of the intake pressure, intake temperature, EGR rate, intake valve closing timing, diesel injection timing, diesel injection pressure, and diesel injection quantity on engine combustion, energy distribution, and emission characteristics were systematically investigated. Through a comprehensive analysis of optimized operating conditions, a high-efficiency and low-emission TAC-HCCI combustion technology for dual-fuel engines was developed. The core mechanism of TAC-HCCI combustion control was elucidated through an analysis of the equivalence ratio and temperature distribution of the in-cylinder mixture. The results indicate that under the constraints of PCP ≤ 30 ± 1 MPa and RI ≤ 5 ± 0.5 MW/m², the TAC-HCCI technology achieves a gross indicated mean effective pressure (IMEPg) of 24.0 bar, a gross indicated thermal efficiency (ITEg) of up to 52.0%, and indicated specific NOx emissions (ISNOx) as low as 1.0 g/kW∙h. To achieve low combustion loss, reduced heat transfer loss, and high thermal efficiency, it is essential to ensure the complete combustion of the mixture while maintaining low combustion temperatures. Moreover, a reduced diesel injection quantity combined with a high injection pressure can effectively suppress NOx emissions. Full article

To tackle the challenges of detecting complex cracks on large stone slabs with noisy textures, this paper presents the first domain-optimized framework for stone slab cracks, an improved semantic segmentation model (YOLOv8-Seg) synergistically integrating U-NetV2, DSConv, and DySample. The network uses the lightweight U-NetV2 backbone combined with dynamic feature recalibration and multi-scale refinement to better capture fine crack details. The dynamic up-sampling module (DySample) helps to adaptively reconstruct curved boundaries. In addition, the dynamic snake convolution head (DSConv) improves the model’s ability to follow irregular crack shapes. Experiments on the custom-built ST stone crack dataset show that YOLOv8-Seg achieves an mAP@0.5 of 0.856 and an mAP@0.5–0.95 of 0.479. The model also reaches a mean intersection over union (MIoU) of 79.17%, outperforming both baseline and mainstream segmentation models. Ablation studies confirm the value of each module. Comparative tests and industrial validation demonstrate stable performance across different stone materials and textures and a 30% false-positive reduction in real production environments. Overall, YOLOv8-Seg greatly improves segmentation accuracy and robustness in industrial crack detection on natural stone slabs, offering a strong solution for intelligent visual inspection in real-world applications. Full article

Honeybees (Apis mellifera) are pollinators for most crops in nature and a core species for the production of bee products. Body size and body weight are crucial breeding traits, as colonies possessing individuals with large body weight tend to be healthier and exhibit high productivity. In this study, small interfering RNA (siRNA) targeting 15-Hydroxyprostaglandin dehydrogenase (15-PGDH) was incorporated into the feed for feeding worker bee larvae, thereby achieving the silencing of this gene’s expression. The research further analyzed the impact of the RNA expression level of the 15-PGDH gene on the juvenile hormone (JH) titer and its subsequent effects on the body weight and size of worker bees. The results show that inhibiting the expression of 15-PGDH in larvae could significantly increase JH titer, which in turn led to an increase in the body weight of worker bees (1.13-fold higher than that of the control group reared under normal conditions (CK group); p < 0.01; SE: 7.85) and a significant extension in femur (1.08-fold longer than that of the CK group; p < 0.01; SE: 0.18). This study confirms that 15-PGDH can serve as a molecular marker related to body weight and size in honey bees, providing an important basis for molecular marker-assisted selection in honey bee breeding. Full article

Cold rolling is widely recognized as a key industrial process for enhancing the mechanical properties of materials, particularly hardness, through strain hardening. Despite its importance, accurately predicting the final hardness remains a challenge due to the inherently nonlinear nature of the deformation. While several studies have employed artificial neural networks to predict mechanical properties, architectural parameters still need to be investigated to understand their effects on network behavior and model performance, ultimately supporting the design of more effective architectures. This study investigates hyperparameter tuning in artificial neural networks trained using Resilient Backpropagation by evaluating the impact of varying number of hidden layers and neurons on the prediction accuracy of hardness in 70-30 brass specimens subjected to cold rolling. A dataset of 1000 input–output pairs, containing dimensional and hardness measurements from multiple rolling passes, was used to train and evaluate 819 artificial neural network architectures, each with a different configuration of 1 to 3 hidden layers and 4 to 12 neurons per layer. Each configuration was tested over 50 runs to reduce the influence of randomness and enhance result consistency. Enhancing the network depth from one to two hidden layers improved predictive performance. Architectures with two hidden layers achieved better performance metrics, faster convergence, and lower variation than single-layer networks. Introducing a third hidden layer did not yield meaningful improvements over two-hidden-layer architectures in terms of performance metrics. While the top three-layer model converged in fewer epochs, it required more computational time due to increased model complexity and weight elements. Full article

Aging, a progressive and time-dependent decline in physiological functions, is driven by interconnected hallmarks, among which mitochondrial dysfunction plays a central role. Mitochondria not only regulate energy production but also play key roles in other cellular processes, including ROS generation, apoptosis, and metabolic signaling—all of which decline with aging. Polyphenols are a diverse group of natural compounds found in fruits, vegetables, tea, and wine; they emerged as promising anti-aging agents due to their ability to modulate several hallmarks of aging, particularly mitochondrial dysfunction. This review explores how various polyphenolic classes influence mitochondrial function and mitigate aging-related decline. These natural compounds have been shown to reduce oxidative stress, increase energy production, and help maintain normal mitochondrial structure. Moreover, in vitro and in vivo studies suggest that polyphenols can delay signs of aging and improve physical and cognitive functions. Overall, polyphenols show great potential to promote healthy aging and even delay the decline in physiological functions by protecting and enhancing mitochondrial health. Full article

This study adopts a dynamic Expectancy–Disconfirmation framework to investigate the evolving nature of user satisfaction across three product categories: durable goods, fast-moving consumer goods (FMCG), and digital products. A 25-day longitudinal experiment involving 128 participants was conducted, during which users engaged with their most recently purchased products and provided repeated subjective evaluations over time. The findings reveal dynamic changes in the influence of expectations and perceived performance on satisfaction throughout the product usage cycle. For durable goods and FMCG, both expectations and perceived performance gradually declined, accompanied by a weakening effect of expectations on satisfaction. In contrast, digital products exhibited greater volatility, lacking a stable experiential baseline and resulting in greater fluctuations in satisfaction trajectories. Moreover, external contextual and emotional factors were found to play a more significant role in shaping satisfaction with physical products, beyond the scope of the traditional expectancy–performance model. These insights offer theoretical and managerial implications for sustainable product and experience design. In particular, they highlight the importance of implementing experience-stabilizing strategies in digital consumption contexts to support user well-being and enhance continuous product utilization, thereby maximizing product potential and reducing waste. Full article

Cultured meat is emerging as a sustainable alternative to conventional animal agriculture, with scaffolds playing a central role in supporting cellular attachment, growth, and tissue maturation. This review focuses on the development of gel-based hybrid biomaterials that meet the dual requirements of biocompatibility and food safety. We explore recent advances in the use of naturally derived gel-forming polymers such as gelatin, chitosan, cellulose, alginate, and plant-based proteins as the structural backbone for edible scaffolds. Particular attention is given to the integration of food-grade functional additives into hydrogel-based scaffolds. These include nanocellulose, dietary fibers, modified starches, polyphenols, and enzymatic crosslinkers such as transglutaminase, which enhance mechanical stability, rheological properties, and cell-guidance capabilities. Rather than focusing on fabrication methods or individual case studies, this review emphasizes the material-centric design strategies for building scalable, printable, and digestible gel scaffolds suitable for cultured meat production. By systemically evaluating the role of each component in structural reinforcement and biological interaction, this work provides a comprehensive frame work for designing next-generation edible scaffold systems. Nonetheless, the field continues to face challenges, including structural optimization, regulatory validation, and scale-up, which are critical for future implementation. Ultimately, hybrid gel-based scaffolds are positioned as a foundational technology for advancing the functionality, manufacturability, and consumer readiness of cultured meat products, distinguishing this work from previous reviews. Unlike previous reviews that have focused primarily on fabrication techniques or tissue engineering applications, this review provides a uniquely food-centric perspective by systematically evaluating the compositional design of hybrid hydrogel-based scaffolds with edibility, scalability, and consumer acceptance in mind. Through a comparative analysis of food-safe additives and naturally derived biopolymers, this review establishes a framework that bridges biomaterials science and food engineering to advance the practical realization of cultured meat products. Full article

Land use/land cover (LULC) change constitutes a critical driver influencing regional carbon cycling processes. Optimizing LULC structures represents a significant pathway toward the realization of carbon neutrality. This study takes Liaoning Province as a case area to analyze LULC changes from 2000 to 2020 and to assess their impacts on land use carbon emissions (LUCE) and ecosystem carbon storage (ECS). To accelerate the achievement of carbon neutrality, four development scenarios are established: natural development (ND), low-carbon emission (LCE), high-carbon storage (HCS), and carbon neutrality (CN). For each scenario, corresponding optimization objectives and constraint conditions are defined, and a multi-objective LULC optimization coupling model is formulated to optimize both the quantity structure and spatial pattern of LULC. On this basis, the model quantifies ECS and LUCE under the four scenarios and evaluates the economic value of each scenario and its contribution to the carbon neutrality target. Results indicate the following: (1) From 2000 to 2020, the extensive expansion of construction land resulted in a reduction in ECS by 12.72 × 10⁶ t and an increase in LUCE by 150.44 × 10⁶ t; (2) Compared to the ND scenario, the LCE scenario exhibited the most significant performance in controlling carbon emissions, while the HCS scenario achieved the highest increase in carbon sequestration. The CN scenario showed significant advantages in reducing LUCE, enhancing ECS, and promoting economic growth, achieving a reduction of 0.18 × 10⁶ t in LUCE, an increase of 118.84 × 10⁶ t in ECS, and an economic value gain of 3386.21 × 10⁶ yuan. This study optimizes the LULC structure from the perspective of balancing economic development, LUCE reduction, and ECS enhancement. It addresses the inherent conflict between regional economic growth and ecological conservation, providing scientific evidence and policy insights for promoting LULC optimization and advancing carbon neutrality in similar regions. Full article

Coronary artery disease (CAD) is the main cause of morbidity and death worldwide, and atherosclerosis represents the leading pathophysiological pathway responsible for CAD. Atherosclerotic process is a complex interplay of mechanisms and mediators resulting in plaque formation, progression and destabilization, the latter being the most frequent cause of acute cardiovascular events. Considering the systemic nature of atherosclerosis, polyvascular disease involvement is possible and has been described since 1960s. Accordingly, epidemiologic studies reported that concomitant CAD and atherosclerosis in other arterial beds like carotid arteries, lower limb arteries, mesenteric and renal circulation, and aorta, is frequent and related to increased chance of future cardiovascular events. Although risk factors, atherosclerotic plaque features and mechanisms of plaque destabilization are largely shared across different sites, many studies have reported some disparities among districts. Moreover, simultaneous polyvascular disease has been associated with increased likelihood of having particular plaque characteristics depending on the affected arterial level. In this comprehensive narrative review, we aim to discuss about epidemiology of concomitant CAD and atherosclerosis in other arterial beds, and to examine differences in risk factors, plaque features and mechanisms of plaque instability between CAD and other atherosclerotic locations. Finally, we review the studies observing differences on plaque features according to involved atherosclerotic sites, focusing on CAD. Full article

A global poly-crisis of climate change, biodiversity loss, dwindling natural resources, geopolitical instability, among other complex challenges, is on the rise. Societal transformations are therefore imminent, whether intended or unintended. The key question is how to steward and facilitate such changes where fragmentation and siloed ways of working persist. The concept of synergies and the notion of synergic action could help overcome fragmented efforts to steer transformative changes. However, there exists a critical research gap in understanding the conditions needed to enable synergic action. This paper thus explores how synergic action is currently undertaken and the key essentials needed to deliver synergic action. The study uses a case study of the Yorkshire food system transformation to learn from its exemplar practitioners. The study used semi-structured interviews and a thematic analysis process to reach our two key findings. First, we highlight the three types of synergic action: (1) Non-systemic synergic action, (2) Non-systemic synergic action with multiple outcomes, and (3) Systemic synergic action. Differentiating types of synergic action can help identify where synergic action is already underway and guide more explicit efforts towards transformative change. The second key finding is the five essentials for synergic action, which are (1) leadership for synergic action; (2) networking, partnerships, and collaborations; (3) care and understanding; (4) a systems approach; and (5) intentionality for synergic action. This study brings to the fore the importance of intentionality, without which the first four essentials are less likely to coalesce. This is important to inform the reflection and learning of practitioners of systemic change about how they are currently and could be working more synergistically in the future, driven by clear intentionality. Full article

Powdery mildew, caused by Erysiphe quercicola, is one of the primary diseases responsible for the reduction in natural rubber production in China. This disease is a typical airborne pathogen, characterized by its ability to spread via air currents and rapidly escalate into an epidemic under favorable environmental conditions. Accurate prediction and determination of the prevention and control period represent both a critical challenge and key focus area in managing rubber-tree powdery mildew. This study investigates the effects of spore concentration, environmental factors, and infection time on the progression of powdery mildew in rubber trees. By employing six distinct machine learning model construction methods, with the disease index of powdery mildew in rubber trees as the response variable and spore concentration, temperature, humidity, and infection time as predictive variables, a preliminary predictive model for the disease index of rubber-tree powdery mildew was developed. Results from indoor inoculation experiments indicate that spore concentration directly influences disease progression and severity. Higher spore concentrations lead to faster disease development and increased severity. The optimal relative humidity for powdery mildew development in rubber trees is 80% RH. At varying temperatures, the influence of humidity on the disease index differs across spore concentration, exhibiting distinct trends. Each model effectively simulates the progression of powdery mildew in rubber trees, with predicted values closely aligning with observed data. Among the models, the Kernel Ridge Regression (KRR) model demonstrates the highest accuracy, the R² values for the training set and test set were 0.978 and 0.964, respectively, while the RMSE values were 4.037 and 4.926, respectively. This research provides a robust technical foundation for reducing the labor intensity of traditional prediction methods and offers valuable insights for forecasting airborne forest diseases. Full article

Forests are considered one of the most valuable natural areas in metropolitan region landscapes. Considering the sensitivity and ecosystem services provided by trees, the definition of urban forest ecosystems is nowadays based on a comprehensive understanding of the entire urban ecosystem. The effective capturing of particulate matter is one of the ecosystem services provided by urban forests. These ecosystems function as efficient biological filters. Plants accumulate pollutants passively via their leaves. Therefore, another ecosystem service provided by city forests could be the use of tree organs as bioindicators of pollution. This paper aims to estimate differences in trace metal pollution between the wooded urban areas of Vienna and Krakow using leaves of evergreen and deciduous trees as biomonitors. An additional objective of the research was to assess the ability of the applied tree species to act as biomonitors. Plant samples of five species—Norway spruce, Scots pine, European larch, common white birch, and common beech—were collected within both areas, in seven locations: four in the “Wienerwald” Vienna forest (Austria) and three in the “Las Wolski” forest in Krakow (Poland). Concentrations of Cr, Cu, Cd, Pb, and Zn in plant material were determined. Biomonitoring studies with deciduous and coniferous tree leaves showed statistically higher heavy metal contamination in the “Las Wolski” forest compared to the “Wienerwald” forest. Based on the conducted analyses and the literature study, it can be concluded that among the analyzed tree species, only two: European beech and common white birch can be considered potential indicators in environmental studies. These species appear to be suitable bioindicators, as both are widespread in urban woodlands of Central Europe and have shown the highest accumulation levels of trace metals. Full article

This study sought to quantify and characterize diverse rootstock scion interactions in cacao around graft compatibility, disease resistance, nutrient use efficiency, vigor traits, and translocation of nonstructural carbohydrates. In total, 106 grafts were performed with three scion cultivars (Matina 1/6, Criollo 22, Pound 7) and nine diverse open-pollinated seedling populations (BYNC, EQX 3348, GNV 360, IMC 14, PA 107, SCA 6, T 294, T 384, T 484). We found evidence for both local and translocated graft incompatibility. Cross sections and Micro-XCT imaging revealed anatomical anomalies, including necrosis and cavitation at the junction and accumulation of starch in the rootstock directly below the graft junction. Scion genetics were a significant factor in explaining differences in graft take, and graft take varied from 47% (Criollo 22) to 72% (Pound 7). Rootstock and scion identity both accounted for differences in survival over the course of the 30-month greenhouse study, with a low of 28.5% survival of Criollo 22 scions and a high of 72% for Pound 7 scions. Survival by rootstocks varied from 14.3% on GNV 360 to 100% survival on T 294 rootstock. A positive correlation of 0.34 (p = 0.098) was found between the graft success of different rootstock–scion combinations and their kinship coefficient, suggesting that relatedness of stock and scion could be a driver of incompatibility. Significant rootstock–scion effects were also observed for nutrient use efficiency, plant vigor, and resistance to Phytophthora palmivora. These findings, while preliminary in nature, highlight the potential of rootstock breeding to improve plant nutrition, resilience, and disease resistance in cacao. Full article

Carbon (C) sequestration and nitrogen (N) and phosphorus (P) accumulation in urban forest green spaces are significant for global climate regulation and alleviating nutrient pollution. However, the effects of management and conservation practices across different urban forest vegetation types on soil C, N, and P contents and stoichiometric ratios remain largely unexplored. We selected forest soils from Guangzhou, a major Metropolis in China, as our study area. Soil samples were collected from two urban secondary forests that naturally regenerated after disturbance (108 samples) and six urban forest parks primarily composed of artificially planted woody plant communities (72 samples). We employed mixed linear models and variance partitioning to analyze and compare soil C, N, and P contents and their stoichiometry and its main driving factors beneath suburban forests and urban park vegetation. These results exhibited that soil pH and bulk density in urban parks were higher than those in suburban forests, whereas soil water content, maximum storage capacity, and capillary porosity were higher in urban forests than in urban parks. Soil C, N, and P contents and their stoichiometry (except for N:P ratio) were significantly higher in suburban forests than in urban parks. Multiple analyzes showed that soil pH had the most pronounced negative influence on soil C, N, C:N, C:P, and N:P, but the strongest positive influence on soil P in urban parks. Soil water content had the strongest positive effect on soil C, N, P, C:N, and C:P, while soil N:P was primarily influenced by the positive effect of soil non-capillary porosity in suburban forests. Overall, our study emphasizes that suburban forests outperform urban parks in terms of carbon and nutrient accumulation, and urban green space management should focus particularly on the impact of soil pH and moisture content on soil C, N, and P contents and their stoichiometry. Full article

Art therapy serves as a crucial intervention modality for children with autism spectrum disorder (ASD), demonstrating unique value in emotional expression, sensory integration, and social communication. However, current practice presents critical challenges, including the disconnect between design expertise and clinical needs, unclear mechanisms of environmental factors’ impact on therapeutic outcomes, and insufficient evidence-based support for technology integration. Purpose: This study aimed to construct an evidence-based theoretical framework for art therapy environment design for children with autism, clarifying the relationship between environmental design elements and therapeutic effectiveness. Methodology: Based on the Web of Science database, this study employed a dual-track approach comprising bibliometric analysis and micro-qualitative content analysis to systematically examine the knowledge structure and developmental trends. Research hotspots were identified through keyword co-occurrence network analysis using CiteSpace, while 24 representative design cases were analyzed to gain insights into design concepts, emerging technologies, and implementation principles. Key Findings: Through keyword network visualization analysis, this study identified ten primary research clusters that were systematically categorized into four core design elements: sensory feedback design, behavioral guidance design, emotional resonance design, and therapeutic support design. A responsive therapeutic environment conceptual framework was proposed, encompassing four interconnected components based on the ABC model from positive psychology: emotional, sensory, environmental, and behavioral dimensions. Evidence-based design principles were established emphasizing child-centeredness, the promotion of multisensory expression, the achievement of dynamic feedback, and appropriate technology integration. Research Contribution: This research establishes theoretical connections between environmental design elements and art therapy effectiveness, providing a systematic design guidance framework for interdisciplinary teams, including environmental designers, clinical practitioners, technology developers, and healthcare administrators. The framework positions technology as a therapeutic mediator rather than a driver, ensuring technological integration supports rather than interferes with children’s natural creative impulses. This contributes to creating more effective environmental spaces for art therapy activities for children with autism while aligning with SDG3 goals for promoting mental health and reducing inequalities in therapeutic access. Full article