Search Results (12,912)

As the demand for poultry meat and eggs is increasing in the world, and the use of antibiotics is forbidden in Europe (since 2006), with countries such as the Philippines, Thailand, Bangladesh and China having imposed restriction or prohibitions, researchers and producers have sought for effective non-antibiotic alternatives. Probiotics, prebiotics, synbiotics and phytobiotics are frequently used as alternatives in the field of poultry production. Phytobiotics, plant-derived substances, also referred to as botanicals or phytogenics, are used as animal diets supplements due to their wide range of bioactive compounds (menthol, curcumin, eugenol, allicin and others) and many advantages. They are classified as herbs, spices, plant extracts and essential oils. Some of the benefits offered by the dietary phytobiotics are antimicrobial, antioxidant, digestion stimulant, anti-inflammatory, immunomodulatory, carminative, antiseptic and appetite stimulant, the modulation of gut microbiota and improvement in the intestinal histology. Some representatives of phytobiotics are turmeric, oregano, sage, thyme, black pepper, ginger, garlic, echinacea, rosemary and others. Despite the significant potential of phytobiotics, their widespread adaptation is currently inhibited by challenges regarding cost-effectiveness (high price for raw materials), scarce regulatory frameworks, and inconsistent biological efficacy. The lack of standardization reflects a dual challenge, enclosing both the inherent chemical variability of raw botanical materials and the technical inconsistencies present throughout the industrial manufacturing, and extraction processes as producers use different machinery for extracting and producing the animal feed. To address these systemic impediments, a joint effort across the entire value chain—from primary producers to regulatory authorities—is essential for the development of unified testing protocols and standardization dosage guidelines that ensure the pharmacological safety and reliability of phytobiotic products. Full article

As a key production factor in the era of the intelligent economy, Artificial Intelligence is profoundly reshaping the production methods and energy usage structures of the manufacturing industry. Based on the data of 55 economies from 2002 to 2020, this paper systematically examines the impact and mechanism of AI on carbon emissions embodied in manufacturing production from the perspective of the intelligent economy. The results show that AI presents an “inverted U-shaped” characteristic in relation to carbon emissions embodied in manufacturing production, that is, it has a “carbon-increasing” effect in the early stage and a “carbon-reducing” effect in the later stage. This conclusion remains valid after a series of robustness tests. Mechanism analysis indicates that AI jointly affects carbon emissions embodied in manufacturing production by improving the technical level of manufacturing production and energy utilization efficiency, but there is certain national heterogeneity in the relevant transmission paths, with green inflection points appearing earlier in developed countries. Heterogeneity analysis shows that AI first reduces and then expands the carbon emission gap between different manufacturing industries, and at the same time, the carbon reduction effect on industries varies significantly due to differences in technical gaps, production energy consumption, and the status of intelligent applications. Therefore, China should accelerate the promotion and application of AI in the manufacturing industry, enhance the transmission effect of the manufacturing industry’s production technology level and energy utilization efficiency on carbon emission reduction in the manufacturing industry, and at the same time, rationally plan the industrial layout of AI investment to fully release the carbon emission reduction capacity of AI. Full article

This paper examines the European Central Bank’s institutional capacity and readiness to introduce a digital euro in the context of accelerating digitalization, geopolitical uncertainty, and growing competition in the global monetary system. Rather than treating the digital euro primarily as a technological innovation, the study conceptualizes it as a multidimensional institutional project shaped by regulatory mandates, governance choices, stakeholder expectations and risk considerations. Drawing on institutional theory and stakeholder theory, the analysis adopts a qualitative research design combining semi-structured expert interviews with systematic document analysis of ECB and EU policy material. The findings indicate that while the ECB has developed a structured roadmap encompassing investigation, preparation and potential issuance phases, significant challenges remain across regulative, normative and cognitive dimensions of readiness. These challenges include tensions between privacy and compliance requirements, cybersecurity and interoperability risks, potential effects on financial stability, and the management of public trust and stakeholder acceptance. The paper argues that the success of a digital euro will depend not only on technical feasibility, but on the ECB’s ability to align design and implementation choices with institutional legitimacy and behavioral expectations. By integrating institutional readiness and risk analysis, the study contributes to the literature on central bank digital currencies and offers insights relevant to policymakers concerned with monetary sovereignty and financial resilience in the digital age. Full article

Background/Objectives: Digitalization creates new opportunities for social participation and access to services; however, individuals who lack access to digital resources or the ability to use them effectively are often unable to benefit from these developments. This uneven distribution reflects differences in digital capital that enhance technical competence and support psychosocial dimensions, contributing to empowerment. Such inequalities are particularly pronounced where age- and gender-based disadvantages intersect, generating distinctive forms of exclusion and vulnerability. Within the framework of digital capital theory, this study aims to explore how older women learners’ digital capital is shaped through a structured Digital Competence Training Program and how its growth influences their empowerment experiences. Methods: This qualitative case study utilized semi-structured interviews with 13 older women learners, two policymakers, and an educator. Results: Learners achieved gains beyond technical skills, including greater autonomy, self-confidence, and social connectedness. Despite technical and structural limitations, participants described the program as transformative, strengthening competence and belonging. Conclusions: The training program is an important pathway for strengthening older women’s digital capital and fostering empowerment beyond technical skill acquisition. However, its transformative potential depends on broader structural and institutional conditions, underscoring the need for inclusive, community-based digital education policies to sustain digital participation in later life. Full article

This study focuses on a critical issue in Heterotrophic Prestressed Concrete Pavement (HPCP), the closure pour, which is prone to weak interfacial bonding, stress concentration, and cracking under repeated aircraft loads. To overcome these shortcomings, a novel prefabricated integrated anchorage (PIA) device is designed, integrating the functions of both a tensioning end and an anchoring end. Based on the PIA, a continuous tensioning construction process is introduced, which eliminates the traditional closure pour by utilizing the casting space of the subsequent slab to tension the preceding one. Finite element analysis demonstrates that the PIA device exhibits complex stress alternation under prestressing, with the most critical cross sections located at depths of 100 to 150 mm. A parametric study further reveals a linear relationship between the tension angle and the maximum principal stress in the PIA. In the HPCP system, prestressing establishes a predominant compressive stress field in the slab, effectively enhancing crack resistance. However, localized stress concentration and tension–compression alternation occur not only around the PIAs but also notably at the slab corners. These results confirm that the PIA device and its associated continuous construction method not only overcome the drawbacks of closure pours but also provide an innovative, efficient, and sustainable technical pathway for improving the quality and performance of airfield pavement engineering. Full article

High-efficiency electric motors represent a core enabling technology for sustainable industrial systems, providing substantial opportunities to reduce electricity consumption, operating costs, and associated greenhouse gas emissions across motor-driven processes. This paper presents a structured synthesis of recent progress in high-efficiency motor technologies within the IE3–IE5 efficiency classes, with emphasis on design innovations in electromagnetic optimization, advanced materials, and thermal management that collectively improve efficiency retention, reliability, and service lifetime under practical duty cycle conditions. Beyond component-level advances, the review analyses how high-efficiency motor–drive systems are being embedded within Industry 5.0 manufacturing environments, where human-centric automation and data-driven intelligence extend motor functionality toward adaptive, condition-aware operation. In this context, the integration of IoT-enabled sensing, AI-based analytics, and digital twin models supports predictive maintenance, real-time condition assessment, fault diagnostics, adaptive control, and duty cycle-responsive energy optimization, thereby improving both energy management and operational resilience. The paper also discusses implementation considerations that commonly constrain industrial adoption, including interoperability with legacy infrastructure, control architecture compatibility, data quality and model robustness, cybersecurity concerns, and lifecycle-oriented sustainability requirements such as material criticality and end-of-life pathways. Representative industrial case studies are synthesized to illustrate typical deployment architectures, observed implementation effects, and recurring technical challenges, together with practical mitigation strategies. This article advances the viewpoint that, under the Industry 5.0 paradigm, the value of high-efficiency motors is evolving from a component-level efficiency upgrade to a cyber-physical enabling asset that shapes lifecycle carbon performance and manufacturing resilience; realizing this shift requires integrated co-design spanning electromagnetics, thermodynamics, information science, and control. Full article

A persistent interdisciplinary gap continues to hinder the development of Health 4.0 educational initiatives. Biomedical Engineering programs typically emphasize physiology and instrumentation while providing limited exposure to modern software ecosystems, whereas Informatics curricula often overlook the physical and physiological foundations of bio-instrumentation. To address this dual deficiency, this paper presents a low-cost and modular educational intervention aligned with the “Computing, Electronics, and Health for Everybody” philosophy. The proposed approach is a hands-on technical workshop that translates core biomedical signal-processing concepts into an accessible learning experience using the Arduino platform and the AD8232 ECG sensor. The intervention was implemented simultaneously across universities in Chile, Peru, and Ecuador, involving a total of $n=92$ undergraduate engineering students. Learning outcomes were evaluated using a pre–post assessment design. The results demonstrate a statistically significant improvement in participants’ conceptual understanding of ECG signal components ($p<0.001$), with mean scores increasing across all evaluated dimensions. In addition, students reported higher confidence in interpreting physiological signals and applying interdisciplinary reasoning. These findings indicate that the proposed intervention effectively supports interdisciplinary learning for software-oriented engineering students by introducing core biomedical acquisition and signal-processing concepts through an accessible and scalable educational framework. Full article

Persistent cloud cover and frequent rainfall in subtropical regions throughout the year significantly limit the applicability of optical remote sensing for tree species identification, thereby constraining dynamic forest monitoring and precise management of forest resources. To address this challenge, this study proposes a tree species identification method that integrates multi-source remote sensing temporal features. By combining multi-temporal optical imagery from Sentinel-2 and dual-polarisation Synthetic Aperture Radar (SAR) data from Sentinel-1, we constructed a comprehensive feature set that incorporates spectral, structural, and phenological attributes, including various vegetation indices, backscatter coefficients, and polarimetric decomposition parameters. Through correlation analysis and assessment of temporal feature variability, five distinct integration strategies (T1-T5) were developed to classify six typical subtropical tree species: Pinus massoniana, Pinus elliottii, Acacia, Eucalyptus grandis, Mangrove, and Other hardwoods, using a random forest classifier. The results indicate that the multi-source feature fusion approach significantly outperforms single-source models, with the T5 strategy achieving the highest overall accuracy (OA) of 95.33% and a Kappa coefficient of 0.94. The red-edge vegetation indices and SAR polarimetric features were identified as major contributors to improving the classification accuracy of hardwood species. This study demonstrates that multi-source remote sensing data fusion can effectively mitigate the spatiotemporal constraints of optical imagery, providing a viable solution and technical framework for high-accuracy remote sensing classification in complex subtropical forest environments. Full article

Cassava mosaic disease (CMD) is a major constraint to cassava production in sub-Saharan Africa, particularly in Burkina Faso, where it poses a serious threat to rural food security. This study examined the impact of adopting innovative cassava mosaic disease management practices on cassava yields in the Guiriko and Nando regions of Burkina Faso. To address potential biases arising from differences in characteristics between adopters and non-adopters, an econometric approach based on the instrumental variables (IV) method within a counterfactual framework was employed to estimate the local average treatment effect (LATE). The data were drawn from a survey conducted in September 2023 among 511 cassava producers. The results indicate that the adoption of innovative cassava mosaic disease management practices had a positive and statistically significant effect on agricultural yields. Productivity gains were estimated at 29% in the Guiriko region and 41% in the Nando region, highlighting spatial heterogeneity in impacts. These findings suggest that promoting the diffusion of such practices can substantially improve cassava productivity and reduce the vulnerability of rural households. In addition, the analysis showed that socioeconomic and technical factors, including farmers’ age, membership in cassava producer organizations, household income levels, and the use of chemical fertilizers, also influence productivity outcomes. Overall, the study underscores the importance of strengthening agricultural extension services, supporting producer organizations, and promoting appropriate technologies to maximize the benefits of cassava mosaic disease management practices for food security and rural development. Full article

The western region of the Tarim Basin is a typical deep and ultra-deep oil and gas reservoir with complex geological conditions in China. This area includes a thick salt–gypsum layer, high-pressure brine layers, and other formations with high pressures and a complex pressure system. These geological features present challenges such as a high risk of drilling fluid contamination by formation fluids, the deep burial of subsalt reservoirs, high temperatures, and difficulty in designing drilling fluids. In this paper, by systematically screening and optimizing key additives, a diesel oil-based drilling and completion fluid system resistant to 220 °C ultra-high temperatures with a density of 2.60 g/cm³ was developed. The overall performance was evaluated. Utilizing an independently developed high-temperature emulsifier (BZ-PSE), an organically modified lithium silicate viscosity modifier (BZ-CHT), and compounded fluid loss reducers (BZ-OLG/BZ-OSL), the system maintained excellent rheological stability (yield point > 4.3 Pa) and filtration control capacity (HTHP fluid loss < 4.8 mL) even after aging at 220 °C. The system demonstrated a resistance to contamination by 30–50% composite brines, 15% salt–gypsum cuttings, and 10% cement, proving its capability to effectively handle extremely thick mud shale, salt–gypsum layers, and high-pressure brine. Field tests were conducted in wells GL 3C, DB X, Boz 13X, and Boz 3X. The results indicated that the high-temperature, high-density diesel oil-based drilling fluids and completion fluids can effectively address the technical challenges posed by wellbore instability in thick salt–gypsum layers, high-pressure brine invasion, and performance degradation under ultra-high temperature conditions, providing reliable technical support for the safe and efficient drilling of similar complex formations. Full article

Shale gas “sweet spot” prediction serves as a pivotal technical link in shale gas exploration and development, directly governing the efficiency of exploration deployment and the economic viability of development projects. To address the research gap in sweet spot prediction for complex synclinal structures, this study establishes an integrated geology–engineering–economics evaluation framework, incorporating artificial intelligence (AI)-assisted parameter optimization and dynamic weight adjustment. This innovative approach overcomes the inherent limitations of single-parameter and static evaluation methods commonly employed in new exploration areas. Focusing on the Upper Ordovician Wufeng Formation to Lower Silurian Longmaxi Formation shale sequences within the Anchang Syncline of northern Guizhou, a comprehensive geological characterization of shale reservoirs was accomplished through the fine processing of 3D seismic data (dominant frequency: 30 Hz; signal-to-noise ratio: 8.5) and statistical analysis of logging data. Prestack elastic parameter inversion technology was utilized to quantitatively predict key geological sweet spot parameters, including the total organic carbon (TOC) content and total gas content, with model validation conducted using core test data. Coupled with prestack and poststack seismic attribute analysis, engineering sweet spot evaluation indicators—encompassing fracture development, in situ stress, the pressure coefficient, and the brittleness index—were established with well-defined quantitative criteria. By integrating multi-source data from geology, geophysics, and engineering dynamics, a three-dimensional evaluation system encompassing “preservation conditions–reservoir quality–engineering feasibility” was constructed, with the random forest algorithm employed for sensitive parameter screening. Research findings indicate that high-quality shale in the study area exhibits a thickness ranging from 17 to 22 m, characterized by a TOC content ≥ 4%, gas content of 4.3–4.8 m³/t, effective porosity of 3.5–5.25%, and brittleness index of 55–75. These properties collectively manifest the “high organic matter enrichment, high gas content, and high brittleness” characteristics. Through multi-parameter weighted comprehensive evaluation using the Analytic Hierarchy Process (AHP), complemented by sensitivity testing, sweet spots were classified into three grades: Class I (63 km²), Class II (31 km²), and Class III (27 km²). An optimized well placement scheme for the southern region was proposed, taking into account long-term production dynamics and economic assessment. This study establishes a multi-parameter, multi-technology integrated sweet spot evaluation system with strong transferability, providing a robust scientific basis for the large-scale exploration and development of shale gas in northern Guizhou and analogous complex structural regions worldwide. Full article

The growing global demand for energy, driven by population growth and industrial development, has increased the importance of renewable sources such as wind energy. In this context, Türkiye has made remarkable progress in expanding its wind energy capacity, particularly in the Aegean Region. The Bergama district, located in the northern part of İzmir, stands out as a promising area for sustainable wind power plant investments due to its favorable average wind speeds of 8–9 m/s measured at a hub height of 100 m. This study proposes an intelligent fuzzy multi criteria decision framework to determine the most suitable sites for wind power plant installation in the Bergama region. The evaluation process is structured around four main criteria, economic, technical, environmental, and social, each comprising five sub-criteria. Six alternative locations are comparatively assessed using an integrated Fuzzy Analytic Hierarchy Process and Fuzzy Weighted Sum Model approach. The combined model enabled effective handling of uncertainty in decision parameters and provided a consistent ranking of alternatives. Based on the results, Site 6 emerged as the most suitable location due to its superior wind resource characteristics, technical feasibility, and accessibility advantages, and the proposed approach offers a decision support framework for regional planners to guide strategic wind energy development. Full article

Background: Ports play a strategic role in the efficiency and sustainability of European transport corridors; however, empirical evidence on their performance remains limited, particularly for Eastern European countries. This study aims to assess the technical efficiency and productivity dynamics of Romanian ports along the Danube corridor in a context of structural change and evolving cargo flows. Methods: Technical efficiency is estimated using an output-oriented Data Envelopment Analysis (DEA) model under variable returns to scale, followed by bias correction and determinant analysis employing the Simar–Wilson bootstrap procedure. Productivity change is examined separately using the Malmquist Productivity Index based on original DEA distance functions. Results: The analysis reveals substantial heterogeneity in efficiency levels across ports, with bias-corrected estimates indicating that efficiency differentials are structural rather than statistical. Cargo specialization emerges as the main determinant of efficiency, while location effects are found to be asymmetric. Efficiency levels are largely stable over time, and productivity change is modest, being driven exclusively by efficiency change, with no evidence of technological progress. Conclusions: These findings suggest that the performance of ports along the Romanian Danube corridor is shaped primarily by structural and organizational factors rather than temporal dynamics, underlining the importance of targeted policy interventions focusing on traffic consolidation, port specialization, and coordinated spatial and hinterland planning to enhance inland port performance within European transport corridors. Full article

This study introduces a Blasting Safety Index (BSI), a composite analytical framework for quantifying the cumulative mechanical, environmental, and geotechnical effects of quarry blasting operations. The index integrates ground vibration expressed as Peak Particle Velocity (PPV), noise, dust concentration, and slope stability, each normalized and weighted according to its operational relevance, to provide a unified measure of blasting-related risk. Field application in a pyroxenic andesite quarry is presented as a demonstrative pilot case illustrating the internal coherence and operational feasibility of the proposed framework and resulted in a BSI value of 0.91, classifying the operation as high risk despite full compliance with individual regulatory thresholds. Within the applied weighting structure, PPV represented the dominant contribution to the composite index, reflecting its widely documented influence on blast-induced safety outcomes. The proposed methodology offers a transparent, measurement-based decision-support tool for operational control, regulatory communication, and environmental impact assessment. Owing to its compatibility with digital monitoring ecosystems, the BSI supports the advancement of sustainable, risk-aware, and technically optimized blasting practices within modern quarry operations. Full article

Engineering education is increasingly expected to prepare graduates capable of addressing sustainability challenges, public safety concerns, and ethical responsibilities. However, in many civil and environmental engineering curricula, sustainability and ethics are still treated as supplementary topics rather than being systematically embedded in core technical courses. This study reports a sustainability-oriented curriculum reform implemented in a Building Water Supply and Drainage Engineering course, integrating Education for Sustainable Development (ESD) principles into CDIO-aligned project-based learning activities. A single-group pre–post quasi-experimental design was adopted with 100 undergraduate students. Quantitative data were collected using a competency-based questionnaire, and paired-sample t-tests, effect sizes, and 95% confidence intervals were applied to examine changes in students’ self-reported competencies. Qualitative data were obtained from reflective learning reports and analyzed through thematic analysis. The results indicate statistically significant improvements in sustainability awareness, ethical and professional responsibility, human-centered design, and systems thinking, with large effect sizes. These findings provide context-specific descriptive evidence supporting the feasibility of embedding sustainability and ethical responsibility within discipline-specific technical engineering courses. Nevertheless, the absence of a control group and the reliance on self-reported measures limit causal interpretation. Future research is recommended to adopt comparative or longitudinal designs and incorporate more objective performance-based assessments. Full article