Search Results (1,754)

Studying the impact of digital economy development on marine environmental quality has important theoretical and practical significance for achieving a win–win situation between high-quality economic development and high-level ecological environment protection. This article selects the marine environment of coastal provinces and cities in China from 2011 to 2022 as the research object and uses the entropy method to comprehensively evaluate the quality of marine environment and the level of digital economy. Also, we construct intermediary and threshold effect models to deeply explore the impact mechanism of digital economy development on marine environmental quality. We find that digital economy and marine environmental quality both show a wave-like rising trend, but the comprehensive level is relatively low. The development of the digital economy can effectively improve the level of marine environmental quality, and the digital economy promotes the improvement of marine environmental quality by improving the level of marine economy. The level of economic development and industrial scale has created a threshold effect in the process of promoting the development of marine environmental quality through the digital economy. Therefore, strengthening the digital governance of the marine environment and promoting the industrialization of marine ecology and the ecologicalization of marine industries will help promote the integrated development of the digital economy and marine environment. Full article

The sharing economy is considered to be a potentially efficacious approach for promoting sustainable production and consumption (SPC). This study utilizes dockless bike sharing (DBS) in Beijing as a case study to examine how sharing economy policies and business practices advance SPC. It also dynamically quantifies the environmental and economic performance of DBS practices from a life cycle perspective. The findings indicate that effective SPC practices can be achieved through the collaborative efforts of multiple stakeholders, including the government, operators, manufacturers, consumers, recycling agencies, and other business partners, supported by regulatory systems and advanced technologies. The SPC practices markedly improved the sustainability of DBS promotion in Beijing. This is evidenced by the increase in greenhouse gas (GHG) emission reduction benefits, which have risen from approximately 35.81 g CO₂-eq to 124.40 g CO₂-eq per kilometer of DBS travel. Considering changes in private bicycle ownership, this value could reach approximately 150.60 g CO₂-eq. Although the economic performance of DBS operators has also improved, it remains challenging to achieve profitability, even when considering the economic value of the emission reduction benefits. In certain scenarios, DBS can maximize profits by optimizing fleet size and efficiency, without compromising the benefits of emission reductions. The framework of stakeholder interaction proposed in this study and the results of empirical analysis not only assist regulators, businesses, and the public in better understanding and promoting sustainable production and consumption practices in the sharing economy but also provide valuable insights for achieving a win-win situation of platform profitability and environmental benefits in the SPC practice process. Full article

This study proposes a novel metaheuristic algorithm, Cosmic Evolution Optimization (CEO), for numerical optimization and engineering design. Inspired by the cosmic evolution process, CEO simulates physical phenomena including cosmic expansion, universal gravitation, stellar system interactions, and celestial orbital resonance.The algorithm introduces a multi-stellar framework system, which incorporates search agents into distinct subsystems to perform simultaneous exploration or exploitation behaviors, thereby enhancing diversity and parallel exploration capabilities. Specifically, the CEO algorithm was compared against ten state-of-the-art metaheuristic algorithms on 29 typical unconstrained benchmark problems from CEC2017 across different dimensions and 13 constrained real-world optimization problems from CEC2020. Statistical validations through the Friedman test, the Wilcoxon rank-sum test, and other statistical methods have confirmed the competitiveness and effectiveness of the CEO algorithm. Notably, it achieved a comprehensive Friedman rank of 1.28/11, and the winning rate in the Wilcoxon rank-sum tests exceeded 80% in CEC2017. Furthermore, CEO demonstrated outstanding performance in practical engineering applications such as robot path planning and photovoltaic system parameter extraction, further verifying its efficiency and broad application potential in solving real-world engineering challenges. Full article

The commercial propagation of strawberries is increasingly constrained by the incidence of both established and emerging soilborne pathogens, particularly under soil cultivation systems. Micropropagation represents an effective strategy to ensure the production of virus-free, true-to-type mother plants suitable for high-efficiency propagation. In this study, micropropagated mother plants of four short-day cultivars (‘Francesca’, ‘Silvia’, ‘Lauretta’, and ‘Dina’) and one ever-bearing advanced selection (‘AN12,13,58’) were cultivated under a controlled soilless system. Quantitative parameters including number of runners per plant, runner length, and number of tips per runner and per plant were assessed to evaluate propagation performance. Micropropagated mother plants exhibited a significantly higher stoloniferous potential compared to in vivo-derived mother plants (frigo plants type A), with the latter producing approximately 50% fewer propagules. Rooted tips of ‘Dina’ were further assessed under different fertigation regimes. The NPK 20–20–20 nutrient solution enhanced photosynthetic activity and shoot and root biomass (length, diameter, and volume via WinRHIZO analysis). These results confirm the suitability of micropropagated mother plants grown in soilless conditions for efficient, high-quality clonal propagation and support the integration of such systems into certified nursery production schemes. Full article

The effective design of logistics platform business models is an important means for platform-type logistics enterprises to gain a competitive advantage. This study employs RRS Logistics as a case study to clarify the dynamic environmental mechanisms of logistics platform business models from the perspective of value co-creation and build a novel structural framework for logistics platform business models with community at their core. The research findings are as follows: First, guided by the idea of “value positioning–value co–creation–value support–value maintenance–value capture”, the conceptual framework of business models is redefined. The key steps in designing logistics platform business models, which can provide guidance and assistance for different logistics platforms, are proposed. Second, the design process for logistics platform business models should be dynamically adjusted in real time according to changes and environmental uncertainty. Third, in the process of transitioning to an ecological platform, logistics platforms’ ecosystem service clusters and ecosystem envelope are key factors in achieving a win–win scenario for all the stakeholders in the community. The case studies show that in logistics platform business model design, methods and key steps based on value co-creation could enhance the core competitiveness of logistics platforms. Full article

With consumers increasing in environmental awareness, manufacturers have integrated green R&D into their strategies, aiming to grasp the green market. However, manufacturers may be too bullish on the market potential of green products and maintain an optimistic attitude toward green R&D. Despite having an optimistic attitude, manufacturers often have no demand information advantage over downstream retailers due to their position in the supply chain, away from the market. It is worth exploring what impact optimistic green R&D in a sustainable supply chain with demand information asymmetry will have. Previous studies have not managed to reveal this. In this study, a stylized model is introduced to explore this question. The main findings are as follows: (1) optimistic green R&D increases the feasibility of the retailer sharing demand information, which facilitates information communication in the sustainable supply chain; (2) in most cases, optimistic green R&D does not bring higher profits for the manufacturer, yet is likely to allow the retailer to earn more, thereby resulting in a loss–win outcome; and (3) depending on the green R&D efficiency of the manufacturer and the consumer’s environmental awareness, optimistic green R&D may not generate higher environmental benefits. Full article

This study presents a comprehensive evaluation of miscible gas injection (MGI) strategies for enhanced oil recovery (EOR) in high-salinity reservoirs, with a focus on the Raleigh Oil Field. Using a calibrated Equation of State (EOS) model in CMG WinProp™, eight gas injection scenarios were simulated to assess phase behavior, miscibility, and swelling factors. The results indicate that carbon dioxide (CO₂) and enriched separator gas offer the most technically and economically viable options, with CO₂ demonstrating superior swelling performance and lower miscibility pressure requirements. The findings underscore the potential of CO₂-EOR as a sustainable and effective recovery method in pressure-depleted, high-salinity environments. Full article

The evaluation of large language models (LLMs) increasingly relies on other LLMs acting as automated judges. While this approach offers scalability and efficiency, it raises serious concerns regarding evaluator reliability, positional bias, and ranking stability. This paper presents a scalable framework for diagnosing positional bias and instability in LLM-based evaluation by using controlled pairwise comparisons judged by multiple independent language models. The system supports mirrored comparisons with reversed response order, prompt injection, and surface-level perturbations (e.g., paraphrasing, lexical noise), enabling fine-grained analysis of evaluator consistency and verdict robustness. Over 3600 pairwise comparisons were conducted across five instruction-tuned open-weight models using ten open-ended prompts. The top-performing model (gemma:7b-instruct) achieved a 66.5% win rate. Evaluator agreement was uniformly high, with 100% consistency across judges, yet 48.4% of verdicts reversed under mirrored response order, indicating strong positional bias. Kendall’s Tau analysis further showed that local model rankings varied substantially across prompts, suggesting that semantic context influences evaluator judgment. All evaluation traces were stored in a graph database (Neo4j), enabling structured querying and longitudinal analysis. The proposed framework provides not only a diagnostic lens for benchmarking models but also a blueprint for fairer and more interpretable LLM-based evaluation. These findings underscore the need for structure-aware, perturbation-resilient evaluation pipelines when benchmarking LLMs. The proposed framework offers a reproducible path for diagnosing evaluator bias and ranking instability in open-ended language tasks. Future work will apply this methodology to educational assessment tasks, using rubric-based scoring and graph-based traceability to evaluate student responses in technical domains. Full article

In the present study, 96 teams’ performances across 48 matches in the group stage of the FIFA Club World Cup 2025 were analyzed. Teams scoring first won 62.5% of matches (p < 0.05), while goals were evenly distributed between halves (p > 0.05) and showed marginal variation across six 15 min intervals, peaking near the 30–45 and 75–90 min marks. Parametric analyses revealed a significant effect of match outcome on possession, with winning teams exhibiting higher average possession (53.3%) compared to losing and drawing teams. Non-parametric analyses identified significant differences between match outcomes for goals scored, attempts at goal, total and completed passes, pass completion rate, defensive line breaks, receptions in the final third, ball progressions, defensive pressures, and total distance covered. Winning teams scored more goals and registered more attempts on target than losing teams, although some metrics showed no significant difference between wins and draws. Logistic regression analysis identified attempts at goal on target, defensive pressures, total completed passes, total distance covered, and receptions in the final third as significant predictors of match success (AUC = 0.85), correctly classifying 80.2% of match outcomes. These results emphasized the crucial role of offensive accuracy and possession dominance in achieving success in elite football. Full article

Small news media organizations are increasingly reshaping the news media system in Latin America. They are stepping into the role of watchdogs by investigating issues such as corruption scandals that larger outlets sometimes overlook. However, this journalistic work exposes both journalists and their organizations to a range of security threats, including physical violence, legal pressure, and digital attacks. In response, these outlets have developed coping strategies to manage and mitigate such risks. This article presents an exploratory study of the approaches adopted to protect information and data, ensure the safety and well-being of journalists, and maintain organizational continuity. Based on a series of in-depth interviews with leaders of award-winning news organizations for their investigative reporting, the study examines a shift from a competitive newsroom model to a collaborative approach in which information is shared—sometimes across borders—to support investigative reporting and strengthen security practices. We identify strategies implemented by small news organizations to safeguard their journalistic work and propose an integrative model of news safety encompassing the following three areas of security: physical, legal, and digital. This study contributes to the development of the newsafety framework and sheds light on safety practices that support media freedom. Full article

This paper proposes an incentive scheme based on a public–private partnership (PPP) to encourage low-carbon travel behavior by inducing the mode choice shift from private cars to public transit. The scheme involves three key entities: travelers, the government, and the private sector. Travelers can choose between private cars and public transit, producing different emissions. As the leader, the government aims to reduce total emission to a certain level with limited budgets. The private sector, as an intermediary, invests subsidies in low-carbon rewards to attract green travelers and benefits from a larger user pool. A two-layer multi-objective optimization model is proposed, which includes travel time, monetary cost, and emission. The objective of the upper level is to maximize the utilities of the private sector and minimize social costs to the government. The lower layer is the user equilibrium of the travelers. The numerical results obtained through heuristic algorithms demonstrate that the proposed scheme can achieve a triple-win situation, where all stakeholders benefit. Moreover, sensitivity analysis finds that prioritizing pollution control strategies will be beneficial to the government only if the unit pollution control cost coefficient is below a low threshold. Contrary to intuition, larger government subsidies do not necessarily lead to better promotion of low-carbon travel. Full article

During the long-term preservation of murals, the degradation of mural image information poses significant challenges to the restoration and conservation of world cultural heritage. Currently, mural conservation scholars focus on image segmentation techniques for mural restoration and protection. However, existing image segmentation methods suffer from suboptimal segmentation quality. To improve mural image segmentation, this study proposes an efficient mural image segmentation method termed Adaptive Nonlinear Bernstein-guided Parrot Optimizer (ANBPO) by integrating an adaptive learning strategy, a nonlinear factor, and a third-order Bernstein-guided strategy into the Parrot Optimizer (PO). In ANBPO, First, to address PO’s limited global exploration capability, the adaptive learning strategy is introduced. By considering individual information disparities and learning behaviors, this strategy effectively enhances the algorithm’s global exploration, enabling a thorough search of the solution space. Second, to mitigate the imbalance between PO’s global exploration and local exploitation phases, the nonlinear factor is proposed. Leveraging its adaptability and nonlinear curve characteristics, this factor improves the algorithm’s ability to escape local optimal segmentation thresholds. Finally, to overcome PO’s inadequate local exploitation capability, the third-order Bernstein-guided strategy is introduced. By incorporating the weighted properties of third-order Bernstein polynomials, this strategy comprehensively evaluates individuals with diverse characteristics, thereby enhancing the precision of mural image segmentation. ANBPO was applied to segment twelve mural images. The results demonstrate that, compared to competing algorithms, ANBPO achieves a 91.6% win rate in fitness function values while outperforming them by 67.6%, 69.4%, and 69.7% in PSNR, SSIM, and FSIM metrics, respectively. These results confirm that the ANBPO algorithm can effectively segment mural images while preserving the original feature information. Thus, it can be regarded as an efficient mural image segmentation algorithm. Full article

Background: It is estimated that in Italy, there were 364,000 new diagnoses of neoplasms each year and that the overall incidence of blood cancers was 10% of these. Leukemia and lymphomas represented the ninth and eighth places, respectively, among the causes of death from neoplasia. Hematopoietic stem cell transplantation represented an effective treatment option for many of these malignancies, and not only that: benign and congenital diseases could also be treated. Objective: To assess knowledge among the Apulian population regarding stem cell donation and factors that could influence this choice, focusing especially on the knowledge of the residents of Puglia, Italy on how stem cells were harvested and their functions, their reasons for joining the National Registry, and the reasons that hold them back from making such a choice. Study Design: An observational and cross-sectional study was conducted, through snowball sampling methodology, until data saturation. An online survey was conducted, which included several Italian associations. The questionnaire administered contained five main sections, such as sociodemographic data, knowledge of the existence of National Registries and their adherence, the nationwide presence of various associations that promote donation, knowledge with respect to the structure, use and functions of stem cells, sources of procurement, such as bone marrow, peripheral blood and umbilical cord, and related procedures, beliefs, attitudes, values, and opinions of the Italian population regarding the topic, and degree of information and education regarding bone marrow donation. Results: A total of 567 Apulian citizens were enrolled. Of these, 75.3% were female and 96.8% were aged between 18 and 65 years. Most of participants were single (46.9%) and married (47.3%) and had a diploma (44.4%), and less had a degree (35.8%). Significant differences were recorded between gender, singles, and married participants, and participants with a diploma or a degree and the items proposed. Conclusions: A true culture of donation in our region was not clearly spread. Although something has been accomplished in recent years in terms of deceased donor donation, still a great deal needs to be achieved for living donation, which encountered a great deal of resistance. It has been deemed necessary to seek winning solutions to this issue in terms of communication and information campaigns, raising awareness and empowering citizens to express consciously their concerns about organs and tissues and to stand in solidarity with those who suffered. Full article

Reward processing is a vital function for health and survival and is impaired in various psychiatric and neurological disorders. Using a monetary gambling task, the current study aims to elucidate neural substrates in the reward network underlying the evaluation of win versus loss outcomes and their association with behavioral characteristics, such as impulsivity and task performance, and neuropsychological functioning. Functional MRI was recorded in thirty healthy, male community volunteers (mean age = 27.4 years) while they performed a monetary gambling task in which they bet with either 10 or 50 tokens and received feedback on whether they won or lost the bet amount. Results showed that a set of key brain structures in the reward network, including the putamen, caudate nucleus, superior and inferior parietal lobule, angular gyrus, and Rolandic operculum, had greater blood oxygenation level-dependent (BOLD) signals during win relative to loss trials, and the BOLD signals in most of these regions were highly correlated with one another. Furthermore, exploratory bivariate analyses between these reward-related regions and behavioral and neuropsychological domains showed significant correlations with moderate effect sizes, including (i) negative correlations between non-planning impulsivity and activations in the putamen and caudate regions, (ii) positive correlations between risky bets and right putamen activation, (iii) negative correlations between safer bets and right putamen activation, (iv) a negative correlation between short-term memory capacity and right putamen activity, and (v) a negative correlation between poor planning skills and left inferior occipital cortex activation. These findings contribute to our understanding of the neural underpinnings of monetary reward processing and their relationships to aspects of behavior and cognitive function. Future studies may confirm these findings with larger samples of healthy controls and extend these findings by investigating various clinical groups with impaired reward processing. Full article

The mosaic tesserae that are the topic of this study were found during an archeological excavation in a Roman villa at Aiano, in the municipality of San Gimignano, Tuscany (Italy). Many thousands of tesserae were found in the site in many different stratigraphic units (US). For this study, 392 tesserae mainly from three US (US 1095, US 5010 and US 5015 being the most consistent ones) were selected for non-invasive analyses. They might be tesserae coming from different places, collected to be reused or melted down to create new glass objects. The characterization of the tesserae, divided in various groups depending on their color, is an important tool in evaluating their compositional homogeneity/inhomogeneity. The presence of certain markers, such as the opacifiers based on Sb or Sn, could be helpful also in approximately dating the tesserae, since, as reported in the literature, various opacifiers were used in different periods. A well-established diagnostic protocol, based only on non-invasive techniques, allowed us to study a large number of tesserae, which certainly did not derive from a single mosaic and could have been of very different ages, compositions and origins. This procedure has proven to be a winning tool for this aim. Full article