Search Results (172,865)

Environmental innovation represents a pivotal pathway toward achieving energy efficiency improvements, carbon footprint reduction, and ecological sustainability enhancement. The research investigates Chinese manufacturing enterprises listed on domestic stock exchanges throughout 2011–2023. The analytical framework utilizes count-based regression methodologies to explore how R&D investment intensity influences eco-innovation capabilities. Results demonstrate curvilinear associations linking R&D expenditure levels with both substantive and strategic environmental innovation achievements across industrial firms. This outcome successfully passed the turning-point test. Environmental oversight and financial incentives produce divergent moderating influences on innovation trajectories. Regulatory frameworks generate restrictive impacts through narrowing optimal investment ranges and dampening peak innovation outputs, whereas fiscal support mechanisms foster expansive effects via broadening resource availability and amplifying achievement levels. Cross-sectional examination uncovers substantial variations among ownership categories and geographical locations. State-owned enterprises demonstrate significantly lower optimal R&D intensity thresholds. Private firms require substantially elevated thresholds for optimal performance. Inland territories manifest unbalanced innovation dynamics. Coastal areas exhibit symmetric innovation patterns. The research enriches empirical knowledge in eco-innovation studies while offering context-specific strategic insights. The findings establish theoretical foundations and practical guidance for policy architects designing integrated environmental management systems that enhance innovation capabilities. Full article

Plant-based diets are increasingly attracting attention as they play a significant role in human health and environmental sustainability and are believed to be key components of sustainable food systems. In the present study, both pros and cons of the adoption of plant-based diets are analyzed using a bibliometric method integrated with a qualitative examination of the scientific literature. For the bibliometric study, Bibliometrix software was utilized, examining 3245 scientific articles, downloaded from the Scopus database, and printed between the years 1957 and 2025. The analyses were conducted using R software, version 4.4.1, with access to the Bibliometrix package, version 4.1. The results indicate a remarkable rise, in the last two decades, in the scholarly focus on the influence of plant-based diets on the individual’s health condition as well as the environment. Keyword co-occurrence studies and international collaborations demonstrate a dominance of research focus in both the United States and Europe, with significant contributions from the Asia–Pacific region. Furthermore, the current work offers qualitative identification of the benefits of plant diets from various perspectives like nutritional, economic, ecological, and cultural. It also explores the main dissuaders from adhering to these diets, including perceived nutritional hazards, cost perceptions, low availability, and social prohibitions. Findings emphasize that, in spite of all the barriers, plant food-based diets have a wide-ranging ability to provide tangible benefits at both the individual and population levels, and documented in the scientific literature are recommendations of expert-led education programs, economic incentives, and judiciously framed public policies to overcome these barriers and to make this transition possible towards sustainable food choices. Findings provide a comprehensive understanding of the current lines of inquiry and stage the subsequent work on how to motivate sustainability among the general population. Full article

Pulque, an available traditional Mexican fermented beverage, has deep ethnographic and cultural significance. It was originally consumed by pre-Columbian civilizations, including the Teotihuacanos, Mexicas, Otomies, Zapotecas, Mixtecas, and Maya. It was revered as a sacred drink with both ceremonial and medicinal uses, often reserved for elites and priests. Its production is based on the ancestral extraction and fermentation of aguamiel, a sweet sap obtained from agave plants. While advances in food technology have occurred, traditional techniques for obtaining and fermenting aguamiel remain prevalent, especially in rural communities, reflecting the resilience of indigenous knowledge systems. Recent interest in pulque has focused on its nutritional content and potential health benefits when consumed in moderation, though risks related to excessive intake remain a concern. Moreover, cultural initiatives aim to revitalize indigenous heritage through gastronomic promotion, tourism routes, and festive traditions. This study explores pulque’s production processes, its cultural symbolism, and its evolving role within Mexican society, suggesting that its survival reflects both continuity and adaptation in the face of modernity. This paper is also presented as a narrative integrative review to explore the biocultural significance of pulque across the anthropological, historical, biochemical, and public-health domains. Full article

Silicon carbide (SiC) ceramics have gained significant attention in advanced engineering applications because of their superior mechanical properties, resistance to wear and corrosion, and thermal stability. However, the precision machining of these materials is extremely challenging because of their intrinsic hardness and brittleness. Wire Electrical Discharge Machining (WEDM) has become increasingly popular as a viable technique for processing SiC ceramics because of its ability to produce intricate geometries and high-quality surface finishes. In this review paper, a comprehensive overview of WEDM technology applied to SiC ceramics is presented, emphasizing the influence of process parameters, wire materials, and dielectric fluids on cutting efficiency and quality. This research explores recent experimental findings related to Wire Electrical Discharge Machining (WEDM) and highlights the challenges in reducing material damage. It also presents strategies to improve machining performance. Additionally, potential future directions are discussed, providing a roadmap for further research and the application of WEDM in processing silicon carbide (SiC) and its variants, including solid silicon carbide (SSiC) and silicon-infiltrated silicon carbide (SiSiC). Full article

This review highlights recent advances in the application of Bayesian optimization to chemical synthesis. In the era of artificial intelligence, Bayesian optimization has emerged as a powerful machine learning approach that transforms reaction engineering by enabling efficient and cost-effective optimization of complex reaction systems. We begin with a concise overview of the theoretical foundations of Bayesian optimization, emphasizing key components such as Gaussian process-based surrogate models and acquisition functions that balance exploration and exploitation. Subsequently, we examine its practical applications across various chemical synthesis contexts, including reaction parameter tuning, catalyst screening, molecular design, synthetic route planning, self-optimizing systems, and autonomous laboratories. In addition, we discuss the integration of emerging techniques, such as noise-robust methods, multi-task learning, transfer learning, and multi-fidelity modeling, which enhance the versatility of Bayesian optimization in addressing the challenges and limitations inherent in chemical synthesis. Full article

The scientific study of emotion remains fraught with conceptual ambiguity, methodological limitations, and epistemological blind spots. This theoretical paper argues that existing paradigms frequently capture synthetic rather than natural emotional states—those shaped by social expectations, cognitive scripting, and performance under observation. We propose a conceptual framework that distinguishes natural emotion—spontaneous, embodied, and interoceptively grounded—from synthetic forms that are adaptive, context-driven, and often unconsciously rehearsed. These reactions often involve emotional scripts rather than genuine, spontaneous affective experiences. Drawing on insights from affective neuroscience, psychological measurement, artificial intelligence, and neurodiversity, we examine how widely used tools such as EEG, polygraphy, and self-report instruments may capture emotional conformity rather than authenticity. We further explore how affective AI systems trained on socially filtered datasets risk replicating emotional performance rather than emotional truth. By recognizing neurodivergent expression as a potential site of emotional transparency, we challenge dominant models of emotional normalcy and propose a five-step agenda for reorienting emotion research toward authenticity, ecological validity, and inclusivity. This post-synthetic framework invites a redefinition of emotion that is conceptually rigorous, methodologically nuanced, and ethically inclusive of human affective diversity. Full article

Natural resource assets inherently integrate tripartite synthesis of legal, economic, and ecological attributes. They serve dual critical functions as foundational elements supporting the evolution of new-quality productive forces and pivotal mechanisms safeguarding ecosystemic integrity. It has become a global consensus and direction of action to advance comprehensive supervision of natural resource assets and practice the concept of “Community of Life for Human and Nature”. Under the background of the super-ministry system restructuring in China, comprehensive supervision of natural resource assets remains challenged by system fragmentation in supervision objectives and multifaceted interest conflicts among stakeholders. In light of this, this research focuses on the theoretical justification and system optimization of the comprehensive supervision of natural resource assets in China. Using comparative analysis and normative analysis methods, we validate the system’s function on the comprehensive supervision of natural resource assets, summarize foreign experiences, and ultimately aim to explore the optimization pathway of the legal system for the comprehensive supervision of natural resource assets. The results show the following: (1) The choice of the legal system for the comprehensive supervision of natural resource assets emerges as the functional product aligning societal objectives, the rational paradigm for achieving efficient resource allocation, and the adaptive response to the external effects of common property. (2) The system supply of comprehensive supervision of natural resource assets in foreign countries is characterized by normative convergence in conceptual elements and typological categorization in objectives and objects. Therefore, this research recommends that, in order to optimize the system of the comprehensive supervision of natural resource assets in China, (1) in terms of protection of source, natural resource assets should be categorized, with operational natural resource assets focusing on management and public welfare natural resource assets focusing on conservation. (2) In terms of valuation, the economic valuation of natural resource assets should be integrated with ecosystem service assessments to enhance fair market equity. (3) In terms of method, the big data center should be established to enable the synergistic integration of technological innovation and system reforms. (4) In terms of subject, requiring the participation of various government departments, non-governmental organizations, the general public, and other parties could realize the connection of different legal bases for the comprehensive supervision of natural resource assets and the balance of multiple rights and interests, which should help to achieve balanced resource efficiency and biodiversity conservation and safeguard national ecological security. Full article

Background and Objectives: Type 2 diabetes (T2DM) substantially increases cardiovascular risk; beyond the well-recognized left-ventricular involvement in diabetic cardiomyopathy, emerging data indicate subclinical right-ventricular (RV) dysfunction may also be present. This study aimed to evaluate whether speckle-tracking echocardiography identifies subclinical right-ventricular systolic dysfunction in type 2 diabetes, despite normal conventional indices and preserved global systolic function. Materials and Methods: We conducted a cross-sectional, single-center study in accordance with STROBE recommendations, enrolling 77 participants, 36 adults with T2DM, and 41 non-diabetic controls, between December 2024 and July 2025. All participants underwent comprehensive transthoracic echocardiography, including conventional parameters (tricuspid annular plane systolic excursion (TAPSE), tricuspid annular systolic velocity (TV S’), right ventricular fractional area change (RVFAC)) and deformation imaging (right ventricular global longitudinal strain (RV GLS), right ventricular free wall longitudinal strain (RVFWS)) using speckle-tracking echocardiography. Biochemical and clinical data, including glycosylated hemoglobin (HbA1c), were recorded. Correlation and ROC curve analyses were performed to explore associations and predictive value. Results: The mean age was comparable between the two groups (62.08 ± 9.54 years vs. 60.22 ± 13.39 years; p = 0.480). While conventional RV parameters did not differ significantly between groups, diabetic patients had significantly lower RV GLS (−13.86 ± 6.07% vs. −18.59 ± 2.27%, p < 0.001) and RVFWS (−15.64 ± 4.30% vs. −19.03 ± 3.53%, p < 0.001). HbA1c levels correlated positively with RV strain impairment (RVFWS r = 0.41, p < 0.001). Both RV GLS and RVFWS were independent predictors of RV dysfunction in logistic regression analysis. ROC analysis showed good diagnostic performance for RV GLS, AUC = 0.84 with an optimal cut-off −17.2% (sensitivity 86.1% and specificity 80.5%) and RVFWS, AUC = 0.76 with cut-off −17.6% (sensitivity 77.8; specificity 80.5%) in identifying early myocardial involvement. Conclusions: RV systolic dysfunction may occur early in T2DM, even when traditional echocardiographic indices remain within normal limits. Speckle-tracking echocardiography, particularly RV GLS and RVFWS, offers sensitive detection of subclinical myocardial impairment, reinforcing its value in early cardiovascular risk stratification among diabetic patients. Full article

Chatbots, search engines and Database Query Systems are invaluable sources of information for decision-making processes in the data-driven world in which we live today. In this study, we explore the extent to which classical and Quantum Query Systems can support future decisions, taken at a moment where the query service may be inaccessible and the decision has to be based solely on information collected in the past. We show that encoding information at the quantum level allows Query Systems to support future or delayed decisions. More precisely, Grover’s algorithm can be employed in order to extract the desired answer from a large superposition of question–answer pairs obtained through a single interrogation of the system. The method works best for binary answers and can be applied to queries encompassing hundreds or thousands of questions in one query. Extensions are possible if we allow more than one query to be addressed to the system. By comparison, a classical system would require hundreds or thousands of queries in order to offer the same level of support for delayed decisions. Full article

Based on the photoconductive effect of photosensitive films, a designed light pattern was projected onto a hydrogenated amorphous silicon (a-Si:H) photosensitive chip to generate virtual light-induced electrodes for cellular electrical detection. To obtain high-quality cellular signals, this study aims to explore the effect of electrical excitation on a-Si:H photosensitive chip. Firstly, the electrochemical impedance spectroscopy (EIS) and volt-ampere characteristics of the a-Si:H photosensitive chip were characterized. EIS data were fitted to extract equivalent circuit models (ECMs) for both the chip and system. Then analog experiments were performed to verify the ECMs, and the results were consistent with the circuit simulation. Finally, applied alternating current (AC) or direct current (DC) signals to the chip and recorded the electrical signals of the cultured cardiomyocytes on the a-Si:H photosensitive chip. The results demonstrated that applying a high-frequency small AC signal to the chip reduced the background noise of the system by approximately 85.1%, and applying a DC bias increased the amplitude of the detection signal by approximately 142.7%. Consequently, the detection performance of the a-Si:H photosensitive chip for weak bioelectrical signals was significantly enhanced, advancing its applicability in cellular electrophysiological studies. Full article

Mastitis, an inflammatory disease caused by the invasion of various pathogenic microorganisms into mammary gland tissue, is a core health issue plaguing the global dairy industry. The consequences of this disease are manifold. In addition to directly compromising the health and welfare of dairy cows, it also precipitates a substantial decline in lactation function, a precipitous drop in raw milk production, and alterations in milk composition (e.g., increased somatic cell counts and imbalanced ratios of milk protein to fat). These changes result in a marked degradation of milk quality and safety, and in turn, engender significant economic losses for the livestock industry. Therefore, the establishment and implementation of a comprehensive prevention and control system is a key strategy to effectively curb the occurrence of mastitis, reduce its incidence rate, and minimise economic losses. This review systematically explores the complex etiological factors and pathogenic mechanisms of mastitis in dairy cows, and summarises various diagnostic methods, including milk apparent indicators monitoring, pathogen detection, physiological parameter monitoring, omics technologies, and emerging technologies. Furthermore, it undertakes an analysis of treatment protocols for mastitis in dairy cows, with a particular emphasis on the significance of rational antibiotic use and alternative therapies. Moreover, it delineates preventive measures encompassing both environmental and hygiene management, and dairy cow health management. The objective of this paper is to provide a comprehensive and scientific theoretical basis and practical guidance for dairy farming practices. This will help to improve the health of dairy cows, ensure a stable supply of high-quality dairy products, and promote the sustainable and healthy development of the dairy farming industry. Full article

This article investigates fundamental inequalities within a golden-like statistical manifold (GLSM) equipped with a semi-symmetric metric connection (SSMC). We explore key geometric and analytical properties, including curvature relations and inequalities analogous to those in classical information geometry. The interplay between the golden-like structure and the SSMC yields new insights into the underlying differential geometric framework. Our results extend known inequalities in the statistical manifold (SM), providing a foundation for further studies in optimization and divergence theory within this generalized framework. Full article

Background/Objectives: Spasticity is a common and disabling sequela of stroke that limits voluntary movement and functional recovery. Vibration therapy (VT) has been proposed as a non-invasive neuromodulatory intervention, but the existing studies report inconsistent outcomes due to methodological heterogeneity. This study aimed to evaluate the overall effectiveness of VT in reducing post-stroke spasticity and to identify optimal stimulation parameters via meta-analytic and meta-regression approaches. Methods: A systematic review and meta-analysis were conducted following the PRISMA 2020 guidelines. Standardized effect sizes (Hedges’ g) were calculated based on the within-group pre–post changes and compared across the groups. Meta-regression and subgroup analyses explored seven potential moderators, including the vibration frequency, amplitude, and time since stroke onset. Results: Thirteen randomized controlled trials (RCTs) involving whole-body or focal vibration interventions in stroke populations were included. Vibration therapy significantly reduced spasticity, yielding a moderate overall effect size (Hedges’ g = −0.50; 95% CI: −0.65 to −0.34; p < 0.001). The greatest treatment effects were observed when VT was applied during the late subacute to early chronic phase (6–12 months post-stroke), with low-frequency (<20 Hz) and low-amplitude (≤0.5 mm) stimulation. The frequency, amplitude, and stroke onset emerged as significant moderators (p < 0.05). Conclusions: Vibration therapy is an effective and clinically meaningful intervention for post-stroke spasticity, particularly when delivered with low-intensity parameters during the optimal recovery window. These findings support the development of individualized VT protocols and provide evidence to guide future rehabilitation strategies. Full article

In the context of global climate change and growing food security challenges, this study provides a comprehensive analysis of the yields of three staple crops (wheat, corn and rice) in the Yellow River Basin of China, employing multiple quantitative analysis methods including the Mann–Kendall trend test, center of gravity transfer model and hotspot analysis. Our research integrates yield data covering these three crops from 72 prefecture-level cities across the Yellow River Basin, during 2000 to 2023, to systematically examine the temporal variation, spatial variation and spatial agglomeration characteristics of the yields. The study uses GeoDetector to explore the impacts of natural and socioeconomic factors on changes in crop yields from both single-factor and interactive-factor perspectives. While traditional statistical methods often struggle to simultaneously handle complex causal relationships among multiple factors, particularly in effectively distinguishing between direct and indirect influence paths or accounting for the transmission effects of factors through mediating variables, this study adopts Structural Equation Modeling (SEM) to identify which factors directly affect crop yields and which exert indirect effects through other factors. This approach enables us to elucidate the path relationships and underlying mechanisms governing crop yields, thereby revealing the direct and indirect influences among multiple factors. This study conducted an analysis using Structural Equation Modeling (SEM), classifying the intensity of influence based on the absolute value of the impact factor (with >0.3 defined as “strong”, 0.1–0.3 as “moderate” and <0.1 as “weak”), and distinguishing the nature of influence by the positive or negative value (positive values indicate promotion, negative values indicate inhibition). The results show that among natural factors, temperature has a moderate promoting effect on wheat (0.21) and a moderate inhibiting effect on corn (−0.25); precipitation has a moderate inhibiting effect on wheat (−0.28) and a moderate promoting effect on rice (0.17); DEM has a strong inhibiting effect on wheat (−0.33) and corn (−0.58), and a strong promoting effect on rice (0.38); slope has a moderate inhibiting effect on wheat (−0.15) and a moderate promoting effect on corn (0.15). Among socioeconomic factors, GDP has a weak promoting effect on wheat (0.01) and a moderate inhibiting effect on rice (−0.20), while the impact of population is relatively small. In terms of indirect effects, slope indirectly inhibits wheat (−0.051, weak) and promotes corn (0.149, moderate) through its influence on temperature; DEM indirectly promotes rice (0.236, moderate) through its influence on GDP and precipitation. In terms of interaction effects, the synergy between precipitation and temperature has the highest explanatory power for wheat and rice, while the synergy between DEM and precipitation has the strongest explanatory power for corn. The study further analyzes the mechanisms of direct and indirect interactions among various factors and finds that there are significant temporal and spatial differences in crop yields in the Yellow River Basin, with natural factors playing a leading role and socioeconomic factors showing dynamic regulatory effects. These findings provide valuable insights for sustainable agricultural development and food security policy-making in the region. Full article

In urban construction, the efficient demolition of concrete structures imposes high-precision requirements on blasting technology. The mesoscopic evolution mechanism of concrete blasting damage is the key to optimizing blasting parameters. In this study, a numerical model of concrete blasting is established using Particle Flow Code (PFC). By comparing it with an experimental model containing a blast hole and a horizontal single fissure, the rationality and reliability of the model in simulating blasting damage evolution are verified. On this basis, four groups of control variable schemes are designed (concrete particle size distribution, aggregate content, prefabricated fissure inclination angle, and fissure length) to systematically explore the effects of mesoscopic structures and macroscopic defects on blasting damage. The results show that larger concrete particles make it easier for damage cracks to avoid large particles, forming sparse and irregular crack networks. A higher aggregate content enhances the “obstruction-guidance” effect of aggregate distribution on damage. When the aggregate content is 40%, the vertical damage expansion is the most prominent, reaching up to 3.05 cm. Fissure inclination angle affects the damage direction by guiding the propagation path of stress waves. Fissures inclined at 30°~60° serve as preferential damage channels, while 90° vertical fissures make vertical damage more significant. An increased fissure length expands the damage range, and the damage degree is the highest for a 40 mm long fissure, being 1.29 times that of a 30 mm fissure. The research results reveal the mesoscopic evolution laws of concrete blasting damage, providing a theoretical basis for the optimization of engineering blasting parameters and safety control. Full article