Search Results (41,488)

The transition towards climate-neutral metallurgical production requires a broader transformation than the simple substitution of fossil-fuel combustion with electrical heating. While process electrification is a fundamental step towards reducing greenhouse gas emissions, achieving truly sustainable high-temperature processing also depends on the ability to maintain tightly controlled reaction environments, minimise thermal losses, and maximise the efficient use of process gases. These factors become increasingly important as the industry moves towards hydrogen-assisted processing routes and greater integration of renewable energy sources. By controlling heat transfer and gas composition, a stable processing environment can be maintained in which temperature, and gases’ partial pressure, can be accurately regulated throughout the treatment cycle. This study introduces the engineering concept of an airtight electrified indirect-fired rotary furnace, developed as a new process for efficient calcination, and also, hydrogen-based reduction processes. To assess the applicability of the proposed reactor concept, a bench-scale experimental campaign was carried out using two representative metallurgical processes: magnesite calcination and hydrogen-assisted reduction of lateritic ores. Throughout the testing campaign, the reactor maintained stable thermal conditions and a well-controlled process atmosphere, while the integrated monitoring system enabled continuous observation of temperature evolution and gas composition. The calcination trials achieved conversion efficiencies above 98%, whereas the hydrogen-reduction experiments successfully promoted the transformation of iron and nickel oxide phases into their metallic state. The results demonstrate that the integration of indirect electrical heating with airtight reactor operation provides a robust platform for hydrogen-assisted thermal processing. The proposed architecture improves atmosphere control and process efficiency while offering a scalable solution for the future implementation of electrified, low-carbon metallurgical technologies. Full article

The transition from electrical to optical interconnects, enabled by the adoption of co-packaged optics (CPO) in advanced processors, is accelerating the scale-up to high volumes and redefining wafer-level test requirements. As optical interfaces migrate closer to the compute die, an increasing share of functional characterization must occur at the probe, where stringent sub-micron alignment, the mechanical stability necessary to preserve optical coupling against dynamic disturbances, and opto-electrical co-validation introduce new technical challenges. Ensuring repeatable and precise fiber-array-unit (FAU) engagement at the wafer level is therefore essential to enable scalable manufacturing of photonic-enabled processors. This paper introduces the EclipsePhotonic probe card, which embeds the Eclipse Dynamic piezoelectric positioning mechanism into a standard vertical-needle probe head as a route toward six-degree-of-freedom FAU manipulation with nanometric positioning accuracy. This architecture is designed to support repeatable coupling to on-wafer photonic structures without requiring specialized probe-head designs, thereby reducing integration complexity and addressing alignment-related yield risks. The platform is also intended to support multi-site electrical and optical probing, providing a path toward parallel test execution once the corresponding layout, optical-routing, and validation constraints are satisfied. A core innovation of the platform is its embedded sensor network, which integrates low- and higher-frequency displacement sensors, relative displacement sensors, and temperature sensors around a microcontroller-based supervisor. The vibration sensor fulfills a dual operational role: it detects environmental and test-cell disturbances that may have influenced optical coupling, providing essential context for binning decisions or targeted retest, and it contributes to probe card lifecycle monitoring by ensuring that the mechanical signature of the probe card remains within a validated operational “swim lane” throughout its service life. Recently published characterization of the underlying Eclipse Dynamic alignment engine shows that, in the production-optimized high-speed regime with effective hysteresis compensation, the Fixed Gradient routine provides the best normalized trade-off among the evaluated routines, with a normalized alignment cost of 1.44 a.u., 95.8% convergence reliability, and 99.4% of the global maximum optical coupling. These values should be interpreted as inherited algorithmic benchmarking results rather than as absolute wall-clock performance of the fully integrated sensor-augmented platform. Full article

Globally, school meals have formed a social safety net for improving children’s nutrition, health, and educational attainment. In Aotearoa New Zealand, government funded lunches for children attending schools in low-income neighbourhoods were introduced in 2020, amidst rising poverty levels and consequent household food insecurity. The aspirations encapsulated within the scheme’s indigenous Māori name, ‘Ka Ora, Ka Ako’ (‘to be well, healthy and safe; to be ready to learn’) have lost focus since reforms to the lunches in 2024 prioritised cost savings, resulting in widely publicised quality issues. This present study draws from a critical multi-level investigation into the issue of hungry children in New Zealand schools, prior to the introduction of ‘Ka Ora, Ka Ako’. Narrative analysis identified how food in schools has been conceptualised within the context of a settler colonial charity model and neoliberal austerity. Applying a critical community psychology lens highlights how burnt and meagre lunches offered to children from food insecure households are a concrete product of historically grounded, unequal relations between groups. A community psychology approach reimagines state-funded food in schools as a public good, arguing for equitable rights to nutrition, including recognition of Māori rights to food sovereignty. Full article

Against the backdrop of the “Rural Revitalization” strategy, contract farming has emerged as a new mechanism and a growing research focus. This study employs differential game theory to systematically analyze the dynamic decision-making and operational performance differences among supply chain members by comparing scenarios with and without research institution participation, as well as different government subsidy policies. The innovative contribution lies in introducing a dual-effect index to capture consumers’ quality utility from agricultural products and psychological utility derived from supporting farmers. Furthermore, we explore the synergistic effects of research institutions’ technological empowerment and government subsidy strategies on supply chain efficiency. Through the above research and analysis, the study draws the following conclusions: (1) The collaborative agricultural supporting model significantly enhances both farmer yields and overall supply chain profits through technology diffusion and brand premium effects. However, revenue distribution conflicts may lead enterprises to limit their cooperation depth. (2) Government subsidies can alleviate benefit allocation conflicts. Subsidizing a research institution proves more effective at stimulating long-term technological dividends, while subsidizing an enterprise primarily ensures short-term market stability. (3) Brand advantage, technological leadership, and consumer preferences exhibit nonlinear driving effects on supply chain efficiency. Specifically, the positive impact progressively strengthens with wider brand advantages, greater technological leadership, and more intense consumer preferences. The study provides a theoretical foundation for tripartite collaboration, revealing the pivotal role of policy precision and dynamic benefit allocation equilibrium in agricultural supply chain upgrading. Full article

This paper asks whether the digital economy is becoming the new economy: not because traditional economic functions disappear, but because they are increasingly reorganised through digital infrastructure, digital finance and algorithmic capability. We introduce an open-data Digital Architecture framework and build a fully reproducible panel of 38 OECD economies for 2010 to 2024 from World Bank sources. The framework constructs transparent composite indices for digital infrastructure, FinTech, AI/ML capability, the traditional economy, and a clean new economy. Using two-way fixed-effects panels, we provide a descriptive answer: in OECD economies, the digital economy coincides with the new economy mainly through digital infrastructure. First, digital infrastructure is the load-bearing pillar of the digital economy’s association with the new economy: it accounts for about 24 per cent of within-country variation in new-economy outcomes, although its coefficient is imprecise under country-clustered errors. Second, the Digital Architecture Index is useful as a benchmarking construct, but it does not improve the within-country fit because the digital pillars are collinear and infrastructure carries most of the signal. Third, the evidence does not support a robust three-way configuration effect among digital infrastructure, FinTech and AI/ML capability; the association is sensitive to error structure, dynamics, outcome definition and true survey-year estimation. A future-dated placebo loads for the infrastructure block as well, so even the descriptive associations cannot be cleanly separated from slow-moving common trends. The paper therefore contributes a reusable open-data measurement framework and a clear empirical benchmark: in OECD economies, the digital economy aligns with the new economy primarily through digital infrastructure, the pillar that carries the strongest within-country association with productivity and entrepreneurship. The AI/ML capability proxy is externally validated against Eurostat enterprise-AI adoption data, with a cross-country correlation of 0.80. Full article

Digital capitalism is often described either as a clean break with the past or as a continuation of older markets. This article takes a third position: digital capitalism is a reorganisation of capitalist accumulation around platforms, data, attention and digital labour, not a departure from capitalism’s basic logic. The study uses a critical narrative review approach, drawing on Marxian value theory and recent work on platforms, datafication and surveillance. It is anchored by a curated set of publicly reported indicators from institutional and market sources, used as context rather than as a causal test. These show a platform environment that reaches most of humanity, highly concentrated advertising and cloud markets, platform labour as a global phenomenon, and a supposedly weightless economy resting on dense physical infrastructure. The article traces four contradictions: the commodification of unpaid user activity, the material basis of immaterial production, the concentration of market power, and the gap between participation and algorithmic control. The contribution is conceptual. It shows that media business models usually treated as separate, including advertising, subscriptions, creator monetisation, in-game spending and platform commissions, share one logic: user activity is captured as attention, measured as data and converted into revenue. New media therefore function as economic infrastructures for value extraction. Full article

Wound healing is a multifaceted biological process comprising the phases of hemostasis, inflammation, proliferation, and remodeling, all of which require supportive microenvironment for optimal tissue regeneration. Biopolymer-based hydrogels, derived from materials such as cellulose and its derivatives, chitosan, alginate, and hyaluronic acid, have emerged as promising wound dressing materials due to their excellent biocompatibility, biodegradability, moisture-retention capacity, and potential to mimic the native extracellular matrix. The structural characteristics, wound healing functions, and underlying mechanisms of these biopolymers are critically examined and summarized in tabular form. The review further highlights the incorporation of natural and synthetic therapeutic agents, growth factors, stem-cell-derived products, and peptides into biopolymer matrices to enhance therapeutic efficacy. The examined research findings indicate significant increases in fluid intake, moisture retention, antibacterial activity, angiogenesis, collagen deposition, tissue regeneration, and wound healing rates. Translational difficulties, regulatory issues, clinical research, and new patent activity pertaining to advanced wound healing biomaterials are also covered in the review. Despite tremendous improvements, issues still exist in bulk manufacturing, long-term safety, reproducibility, mechanical stability, and clinical validation. Future innovations are anticipated to concentrate on smart, multipurpose, and customized hydrogel systems that can integrate drug delivery, biosensing, and regenerative capabilities while reacting dynamically to wound microenvironments. Overall, biopolymer-based hydrogels are a flexible, rapidly developing platform with significant promise to improve next-generation skin tissue engineering and change the treatment of both acute and chronic wounds. Full article

Background: CAV (cardiac allograft vasculopathy) is considered the leading cause of late post-transplant mortality and affects approximately 50% of transplant patients at 10 years post-transplant. Its etiopathogenetic mechanism is considered to be immune-mediated, but the identification of other non-immunological risk factors could represent new therapeutic targets for this pathology. Lipofuscin is due to reactive oxygen species (ROS) and appears to have a determining role in CAV. The aim of this study is to investigate the association between the amount of lipofuscin identified on EMB (endomyocardial biopsy) from patients followed up after heart transplantation, and the presence of CAV detected by coronary angiography. Methods: This retrospective study includes 99 EMBs from 47 transplanted patients, who also had coronary angiography. The amount of lipofuscin, damage to intramyocardial small vessels, vasculitis, Quilty effect, and acute cellular and humoral rejection was evaluated microscopically. Results: 19 CAV cases (19.2%) were identified, of which 15 (68.18% of total CAV cases) were insignificant. Grade 3 lipofuscin affected equally the cases with insignificant and significant CAV, 3 cases (37.5%) from each group. Grade 2 lipofuscin was reported in 10 cases (58.8%) of insignificant CAV, respectively 1 case of significant CAV (5.9%), (p-value of 0.0001). Quantitative evaluation of lipofuscin on microscopic sections revealed 8 EMBs (8.1%) with grade 3 lipofuscin. Two cases (25.0%) with lipofuscin score 3 were associated with moderate ACR (acute cellular rejection), ISHLT 2R and 3 cases (37.5%) with lipofuscin score 3 were associated with mild ACR ISHLT 1R, the differences being statistically significant, (p = 0.0001). Lipofuscin grades 2 and 3 were associated with severe fibrosis in 6 cases (35.3%) and 2 cases (25.0%), respectively (p = 0.042). A statistically significant association between the degree of damage to the intramyocardial small vessels and the amount of intracytoplasmic lipofuscin was observed (p = 0.00014). Discussion: Our study revealed that lipofuscin was more frequently associated with CAV, fibrosis, and damaged small vessels. Oxidative stress influences lipofuscinogenesis and CAV, which leads to endothelial dysfunction and neointimal hyperplasia, which over time will produce progressive narrowing of the vascular lumen and dysfunction of the cardiac allograft. Of the total number of 19 cases with CAV, 17 (89.47%) presented a lipofuscin score of 2 or 3 concomitantly with CAV, (p = 0.0001). This could mean that lipofuscin is not a harmless degradation product. At the same time, the association of a large number of cases with lipofuscin score 2, 10 cases (58.8%) with insignificant CAV could lead to the idea of using lipofuscin as a potential biomarker in the early diagnosis of CAV. Conclusions: We evidenced a significant association between the amount of intracytoplasmic lipofuscin and CAV. Accordingly, lipofuscin might be involved in the pathogenesis of CAV. Further research is needed to clarify the exact mechanisms of this association. Full article

Product–Service Systems (PSS) require feedback loops that connect stakeholder experience with design decisions, but distributed feedback is often difficult to transform into actionable design knowledge. This paper synthesises previously distributed results from the DIVERSITY project into an integrated decision-support framework for feedback-driven PSS design. The framework combines social-sentiment representation, reach/influence weighting, opinion modelling, monitoring, extraction and prediction modules, and a hierarchical similarity mechanism for exploring likely sentiment toward new PSS configurations. It was implemented in the DIVERSITY engineering environment and assessed through a preliminary polarity plausibility check, controlled testing with synthetic data generated by OpinionSim, and three industrial business cases. The results indicate that the framework can support segmentation-aware interpretation of stakeholder feedback, shorten the path from market signals to design action, and provide exploratory evidence for early PSS concept generation and redesign. The predictive component is presented as an exploratory design-support mechanism, with forecasting accuracy remaining a topic for future empirical validation. The paper contributes an integrated feedback-to-design framework for PSS and clarifies the conditions under which sentiment-based indicators are most useful in B2C and B2B settings. Full article

Higher education is undergoing a rapid transformation driven by advancements in artificial intelligence (AI), creating new opportunities to support the development of higher-order cognitive skills through carefully designed learning environments. This study aimed to examine the effectiveness of an educational program that integrates AI-powered intelligent assistants into a structured e-learning environment to support the development of digital entrepreneurship and future-oriented problem-solving skills among graduate students. A quasi-experimental design was used with 82 graduate students, randomly assigned to two groups: an experimental group (n = 41) and a control group (n = 41). Both groups studied the same educational content and completed identical learning activities; however, the experimental group participated in a structured learning framework that included AI-powered intelligent assistants, guided learning activities, and instructor facilitation, while the control group completed the same activities without AI support. The educational program comprised five modules focusing on chatbot design, intelligent platform development, digital content production, educational data analysis, and future-oriented problem-solving. Learning outcomes were assessed using a Digital Entrepreneurship Product Rating Scale and a Future-Oriented Problem-Solving Scale, which measures skills in visualization, prediction, foresight, and planning. The results revealed statistically significant differences favoring the experimental group on both outcome scales, with large effect sizes. These findings suggest that integrating AI-powered intelligent assistants within a structured learning framework may support the development of digital entrepreneurship and future-oriented problem-solving skills among graduate students. This study contributes empirical evidence to the potential educational value of integrating AI-powered intelligent assistants with pedagogically designed learning activities to foster higher-level cognitive development in higher education. Full article

Cannabidiol (CBD) is a bioactive phytocannabinoid with considerable pharmacological potential. However, its limited aqueous solubility and high lipophilicity remain significant barriers to its broader pharmaceutical application. In this study, the enzymatic potential of selected filamentous fungi was investigated as a whole-cell biocatalytic platform for the regioselective functionalization of CBD. Sixteen fungal strains were screened, and thirteen microorganisms successfully transformed CBD into more polar derivatives. Four strains showing distinct and promising chromatographic profiles were selected for scale-up biotransformation and product isolation: Mucor hiemalis KCh W2, M. hiemalis AM 450, Isaria fumosorosea KCh J2, and Metarhizium robertsii MU4. Eight CBD derivatives were isolated and identified by UHPLC-DAD, NMR spectroscopy, and HRESI-MS, including hydroxylated, glycosylated, and methylglycosylated products. Among them, two metabolites, 2′-O-(4‴-O-methyl-β-D-glucopyranosyl)-cannabidiol and 2′-O-(4‴-O-methyl-β-D-glucopyranosyl)-5″-hydroxycannabidiol, are reported here as previously undescribed CBD derivatives. I. fumosorosea KCh J2 and M. robertsii MU4 demonstrated the ability to catalyse 4-O-methylglycosylation. An additional experiment using 2′-O-(β-D-glucopyranosyl)-cannabidiol as an intermediate supported a sequential pathway involving initial phenolic O-glycosylation followed by methylation of the sugar moiety. In silico analysis predicted reduced lipophilicity for the newly obtained derivatives compared with CBD; however, these computational results require experimental verification and should not be interpreted as evidence of improved aqueous solubility, bioavailability, or biological activity. These findings demonstrate that filamentous fungi are useful whole-cell biocatalysts for generating structurally diverse CBD derivatives with increased polarity and provide new compounds for future physicochemical and biological evaluation. Full article

Livelihood space serves as a fundamental medium for the livelihood practices of rural households. Understanding its optimization and reconstruction is essential for promoting the sustainable development of resettled households. This study adopts a spatial perspective to develop a multidimensional measurement framework for livelihood space. Focusing on resettled households in the karst regions of Guizhou, China, we integrate the Optimal Parameter-based Geographical Detector (OPGD) with fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically analyze the driving mechanisms and equifinal configuration pathways involved in the reconstruction of livelihood space. The key results are as follows: (1) The overall livelihood space is characterized as moderate. Among the various dimensions, institutional and cultural spaces receive the highest scores, followed by social and production spaces, while residential space is rated the lowest. (2) Excluding residential space, there are significant dimensional disparities across different resettlement and livelihood typologies. Households resettled in county towns outperform those in non-county areas. In terms of livelihood types, integrated and off-farm households rank the highest, whereas farming-dependent and subsidy-dependent households rank the lowest. (3) The OPGD analysis indicates that household income and accessibility to public services are primary drivers, exhibiting a bivariate nonlinear synergistic enhancement. (4) The fsQCA findings confirm that the reconstruction of livelihood space is not driven by a single factor; rather, it is influenced by four equifinal pathways formed through nonlinear interactions of multiple conditions, collectively contributing to the enhancement of high-livelihood space. The integration of OPGD and fsQCA moves beyond conventional linear approaches, yielding fresh empirical evidence and new perspectives on livelihood space reconstruction and the sustainability of fragile regions. Full article

In a highly homogeneous market environment, consumers’ cognitive inertia towards standardized products continues to strengthen, and traditional functional attributes significantly weaken the driving force of impulse buying. This study is based on the elaboration likelihood model (ELM). It constructs a dual-path theoretical framework of “cognitive inertia cue arousal”, aiming to reveal a new triggering mechanism for impulse buying behavior (IBB) in homogeneous competition. This study proposes a hybrid structural equation model (SEM) and artificial neural network (ANN) approach to evaluate the driving factors behind consumers’ maintenance of IBB in the context of homogeneous competition. Specifically, the first stage involves identifying key variables that significantly affect IBB using SEM. The second stage consists of predicting the accuracy of the outcome variables and ranking their importance using an ANN. This study confirms two pathways: product cognitive inertia (customized information and promotional discounts) and peripheral cue arousal (anchor novelty display strategy and observation learning). Research has found that observational learning has a positive impact on perceived attention. Interestingly, perceived attention does not have a significant mediating effect between promotional discounts and IBB. This discovery provides a theoretical basis and practical paradigm for cracking the involution competition. Full article

This study examines the impact of green innovation investment on ESG rating divergence and the mediating role of product market competition, based on 11,768 firm-year observations of Chinese A-share listed manufacturing enterprises from 2011 to 2023. We measure green innovation by lagged green patent applications (distinguishing invention and utility model patents), ESG rating divergence by the standard deviation and range of scores from six mainstream international and domestic agencies, and product market competition using the Herfindahl–Hirschman Index. Using mediating effect models with multi-dimensional fixed effects and heterogeneity analysis, we find that green innovation significantly widens ESG rating divergence, with green invention innovation exerting a stronger impact. Product market competition plays a partial mediating role, as green innovation intensifies industry competition and further amplifies rating divergence. Heterogeneity analysis shows no significant effect for heavily polluting firms, while green invention innovation of high-attention firms is more likely to cause rating disputes. This study reveals the reverse spillover effect of green innovation on ESG evaluation, providing new perspectives for understanding rating divergence and references for corporate green strategies and rating system optimization. Full article

The rapid emergence and dissemination of antimicrobial resistance (AMR) among bacterial pathogens, particularly the ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.), represents one of the most pressing global public health challenges, contributing to increased morbidity, mortality, and healthcare costs. The limited development of new antibiotic classes over the past two decades has intensified the search for structurally novel antimicrobial agents and adjuvants capable of overcoming multidrug resistance. Natural products continue to serve as an invaluable source of anti-infective drug leads owing to their remarkable structural diversity and broad spectrum of biological activities. Mangrove ecosystems, located at the interface of terrestrial and marine environments, harbor highly diverse microbial communities, including fungi that have evolved under extreme environmental conditions and produce a wide range of unique secondary metabolites. Beyond their ecological significance, mangrove-associated fungi have emerged as prolific producers of bioactive compounds with promising antibacterial activity against multidrug-resistant pathogens. This review comprehensively summarizes recent advances (2018–2026) in the discovery of antibacterial metabolites from mangrove-associated fungi active against ESKAPE pathogens, which discusses their structural diversity, reported antimicrobial activities, and emerging strategies for accelerating natural product discovery, including genome mining, metabolomics, OSMAC, adaptive laboratory evolution, and artificial intelligence-assisted approaches. A total of 139 chemically distinct metabolites (Compounds 1–139) isolated from mangrove-associated fungi are critically reviewed, highlighting their potential as promising leads for the development of next-generation antimicrobial agents against ESKAPE pathogens. Full article