Search Results (3,219)

Against the backdrop of the carbon peaking and neutrality (“dual-carbon”) goals and evolving new-type power system dispatch, the share of pumped-storage hydropower (PSH) in power systems continues to increase, imposing stricter requirements on units for higher cycling frequency, greater operational flexibility, and rapid, stable startup and shutdown. Focusing on the entire hot-standby-to-generation transition of a PSH plant, a full-flow-path three-dimensional transient numerical model encompassing kilometer-scale headrace/tailrace systems, meter-scale runner and casing passages, and millimeter-scale inter-component clearances is developed. Three-dimensional unsteady computational fluid dynamics are determined, while the surge tank free surface and gaseous phase are captured using a volume-of-fluid (VOF) two-phase formula. Grid independence is demonstrated, and time-resolved validation is performed against the experimental model–test operating data. Internal instability structures are diagnosed via pressure fluctuation spectral analysis and characteristic mode identification, complemented by entropy production analysis to quantify dissipative losses. The results indicate that hydraulic instabilities concentrate in the acceleration phase at small guide vane openings, where misalignment between inflow incidence and blade setting induces separation and vortical structures. Concurrently, an intensified adverse pressure gradient in the draft tube generates an axial recirculation core and a vortex rope, driving upstream propagation of low-frequency pressure pulsations. These findings deepen our mechanistic understanding of hydraulic transients during the hot-standby-to-generation transition of PSH units and provide a theoretical basis for improving transitional stability and optimizing control strategies. Full article

Fungal communities in the rhizosphere are crucial in maintaining soil health, driving nutrient cycling, and enhancing plant productivity. This study examined the role of intercropping of oats (Avena sativa L.) with vetch (Vicia sativa L.) and their subsequent use as green manure (incorporating fresh plant biomass into soil to enhance nutrient cycling and microbial activity) on fungal diversity and community structure. Three field treatments were organized as follows: (i) unplanted control, (ii) single-oat cultivation, and (iii) oat–vetch intercropping. In the ripening stage of oats development, the plants in the intercropping treatment were ploughed at a depth of 30 cm as green manure. Soil samples at ripening stage and 3 months after ploughing were analyzed. High-throughput sequencing of the ITS2 region, combined with multivariate diversity analyses (alpha and beta diversity, PCA, NMDS, and UniFrac), revealed distinct fungal community profiles across treatments. Ascomycota dominated under conventional and untreated conditions, while Basidiomycota, Mortierellomycota, and Glomeromycota were enriched in intercropped and organically amended plots, notably at intercropping. Intercropping and green manuring significantly increased species richness, evenness, and phylogenetic fungal diversity. These treatments also supported higher abundances of beneficial fungi such as Mortierella, Glomus, and Trichoderma, while reducing potentially pathogenic taxa like Fusarium. Rank–abundance curves and rarefaction analysis confirmed that diversified systems hosted more balanced and complex fungal assemblages. Beta diversity metrics and ordination analyses indicated strong dissimilarities between the conventionally managed and diversified systems. The results showed that intercropping and organic inputs alter fungal community composition and promote microbial resilience and ecological functionality in the rhizosphere. These practices promoted the development of stable and diverse fungal networks essential for sustainable soil management and crop production. Full article

Additive manufacturing (AM) is positioned at a pivotal moment, where its long-promised advantages, e.g., lower cost, reduced environmental burden, and accelerated production, are increasingly tangible yet unevenly realized across industries and regions. This review synthesizes evidence from AM processes for different materials to clarify the technical and economic levers that drive outcomes. Cost performance is shown to depend strongly on design choices, deposition rate, post-processing requirements, and feedstock pricing. Environmental impacts hinge on material production routes, regional energy mix, build utilization, and the extent of material reuse. Lead-time reductions are most significant when components are redesigned for AM, when high-throughput processes are applied to compatible geometries, and when production is geographically localized. Emerging digital tools including machine learning, in situ monitoring, and digital twins are accelerating process stabilization and shortening qualification cycles, while hybrid manufacturing lines demonstrate the value of integrating near-net-shape printing with precision finishing. Drawing from these insights, a pragmatic roadmap is proposed: align parts and supply chains with the most suitable AM processes, decarbonize and streamline feedstock production, and increase system utilization. When these conditions are met, AM can deliver broad, quantifiable improvements in cost efficiency, sustainability, and global adoption. By consolidating fragmented evidence into a unified framework, this review responds to the growing need for clarity as AM moves toward broader industrial deployment. Full article

This study presents a one-dimensional numerical simulation of particulate matter (PM) oxidation and regeneration behavior in gasoline particulate filters (GPFs) under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions. The model incorporates both catalyst activity—represented by activation energy (E) and pre-exponential factor (A)—and exhaust control strategies involving forced fuel cut (FC). PM deposition and oxidation were simulated based on solid-state and gas-phase reactions, with the effects of oxygen concentration and temperature analyzed in detail. The results show that under high catalyst activity (E = 100 kJ mol⁻¹, A = 6.2 × 10⁷), PM oxidation proceeds efficiently even during medium-speed phases, achieving a 98.8% oxidation rate after one WLTC. Conversely, conventional catalysts (E = 120 kJ mol⁻¹, A = 6.2 × 10⁶) exhibited limited regeneration, leaving 0.11 g of residual PM. Introducing forced FC effectively enhanced oxidation by increasing oxygen concentration to 20% and sustaining heat release. A single continuous 100 s FC yielded the highest oxidation (96% reduction), while split FCs reduced peak PM accumulation. These findings demonstrate that optimizing the balance between catalyst activity and FC control can significantly improve GPF regeneration performance, providing a practical strategy for PM reduction in GDI vehicles under real driving conditions. Full article

This study presents the design, real-time implementation, and full-scale experimental validation of a rule-based Energy Management Strategy (EMS) for a dual-stack Fuel Cell Hybrid Electric Vehicle (FCHEV) developed on a Jeep Wrangler platform. Unlike previous studies, predominantly focused on simulation-based analysis or single-stack architectures, this work provides comprehensive vehicle-level experimental validation of a deterministic real-time EMS applied to a dual fuel cell system in an SUV-class vehicle. The control algorithm, deployed on a National Instruments CompactRIO embedded controller, ensures deterministic real-time energy distribution and stable hybrid operation under dynamic load conditions. Simulation analysis conducted over eight consecutive WLTC cycles shows that both fuel cell stacks operate predominantly within their optimal efficiency range (25–35 kW), achieving an average DC efficiency of 68% and a hydrogen consumption of 1.35 kg/100 km under idealized conditions. Experimental validation on the Wrangler FCHEV demonstrator yields a hydrogen consumption of 1.67 kg/100 km, corresponding to 1.03 kg/100 km·m² after aerodynamic normalization (Cd·A = 1.624 m²), reflecting real-world operating constraints. The proposed EMS promotes fuel-cell durability by reducing current cycling amplitude and maintaining operation within high-efficiency regions for the majority of the driving cycle. By combining deterministic real-time embedded control with vehicle-level experimental validation, this work strengthens the link between EMS design and practical deployment and provides a scalable reference framework for future hydrogen powertrain control systems. Full article

This review examines how the integration of circular bioeconomy principles with digital technologies can drive climate change mitigation, improve resource efficiency, and facilitate sustainable biorefinery development. This highlights the urgent need to transition away from fossil fuels and introduces the bio-circular economy as a regenerative model focused on biomass valorization, reuse, recycling, and biodegradability. This study compares linear, circular, and bio-circular approaches and analyzes key policy frameworks in Europe, Latin America, and Asia linked to several UN Sustainable Development Goals. A central focus is the role of digitalization, particularly artificial intelligence (AI), the Internet of Things (IoT), and blockchain. Examples include AI-based biomass yield prediction and biorefinery optimization, IoT-enabled real-time monitoring of material and energy flows, and blockchain technology for supply chain traceability and transparency. Applications in agricultural waste valorization, bioplastics, bioenergy, and nutraceutical extraction are also discussed in this review. Sustainability tools, such as automated life-cycle assessment (LCA) and Industry 4.0 integration, are outlined. Finally, future perspectives emphasize autonomous smart biorefineries, biotechnology–nanotechnology convergence, and international collaboration supported by open data platforms. Full article

Postnatal muscle development involves complex transcriptional regulation that remains poorly characterized in goats. This study employed RNA-Seq to profile the Longissimus dorsitranscriptome of Leizhou Black goats across three developmental stages: birth, six months, and two years. We identified dynamic gene expression patterns, widespread alternative splicing events, and stage-specific co-expression networks that collectively orchestrate muscle maturation. A significant transcriptional shift occurred between six months and two years, marked by the downregulation of proliferation-related genes (e.g., RRM2, TOP2A) and the activation of pathways governing muscle contraction and energy metabolism. Functional enrichment analyses highlighted the importance of PI3K-Akt, PPAR, and calcium signaling pathways throughout development. Additionally, 905 novel transcripts were discovered, many enriched in mitochondrial functions, indicating incompleteness in the current goat genome annotation. Weighted gene co-expression network analysis revealed modules correlated with developmental stages, and protein–protein interaction analysis identified hub genes regulating cell cycle progression and muscle function. Key results were validated via qRT-PCR, confirming the temporal expression patterns of genes such as CYP4B1, HACD1, and ACTC1. These findings provide mechanistic insights into the transcriptional reprogramming driving postnatal muscle development and offer valuable genetic resources for improving meat production in goats through molecular breeding. Full article

This study compared CO₂ emissions during a WLTP (Worldwide Harmonized Light-Duty Vehicles Test Procedure) test performed on a chassis dynamometer for the same flex-fuel vehicle, fuelled sequentially with E10 gasoline and E85 fuel. Based on the test data, a CO₂ emissions map was created, describing its dependence on speed and acceleration. The use of a 3D surface enabled the visualisation of the whole dynamics of emissions as a function of engine load in the WLTP cycle, including the identification of distinct emission peaks in areas of high positive acceleration. Analysis of the emission surface enabled the identification of structural differences between the fuels. For E85, more pronounced emission increases are observed in areas of intense acceleration, a consequence of the higher fuel demand resulting from the lower calorific value of bioethanol. In steady-state and moderate-load driving, CO₂ emissions for both fuels are similar. The results confirm that the main differences between E10 and E85 are not simply a shift in emission levels per se, but stem from variations in engine load during the dynamic cycle. Although E85 emits measurable CO₂ emissions, its carbon is not of fossil origin, highlighting the importance of biofuels in the context of greenhouse gas emission reduction strategies and the pursuit of climate neutrality. The presented methodology, combining chassis dynamometer tests with analysis of the speed-acceleration emission map, provides a tool for clearly identifying emission zones and can serve as a basis for further optimisation of engine control strategies and assessing the impact of fuel composition on emissions under dynamic conditions. Full article

Background and Objectives: Dysmenorrhea affects 50–90% of women worldwide and significantly impacts quality of life. This study aimed to determine the nationwide prevalence of dysmenorrhea among Saudi women and evaluate the independent associations between pain severity, associated symptoms, and mental health and quality of life outcomes. Materials and Methods: A cross-sectional study was conducted between May and August 2024 among women aged 18–55 years in Saudi Arabia. Data were collected through an online survey assessing sociodemographic characteristics, menstrual patterns, dysmenorrhea severity (Visual Analogue Scale, VAS 1–10), associated symptoms, mental health (DASS-21), and quality of life (MQLI). Univariate comparisons and multiple linear regression analyses were performed to identify independent predictors of depression, anxiety, stress, and quality of life (QoL). Results: Of 950 women (mean age 28 ± 9.5 years, BMI 24 ± 5.8 kg/m²), 87% reported dysmenorrhea, with 50% experiencing pain every cycle and 55% reporting severe pain (VAS 7–10). Women with severe pain exhibited depression scores 47% higher than those with mild pain (21.8 vs. 14.8, p < 0.001), with similar patterns for anxiety and stress. In multivariate analyses, severe pain (VAS 8–10) was associated with 7–11-point increases in DASS scores (all p < 0.001). Constipation emerged as the strongest symptom-related predictor of depression (β = 4.94, p < 0.001), anxiety (β = 4.79, p < 0.001), stress (β = 3.96, p < 0.001), and reduced quality of life (β = −0.45, p = 0.015). Risk factors included having children, higher BMI, and longer menstrual cycles, while higher income, later menarche, and greater education were protective. Conclusions: Pain severity, not dysmenorrhea presence alone, drives mental health burden. Constipation represents a novel therapeutic target. Integrated care addressing pain, gastrointestinal symptoms, and mental health is essential. Full article

To address the challenges of enhancing driving stability and energy efficiency in distributed-drive electric vehicles, this paper proposes an extenics coordinated torque distribution control method that integrates energy efficiency optimization and vehicle stability. The primary contribution was the development of a vehicle stability assessment method grounded in extenics control theory, which was used to obtain the vehicle’s phase plane and stability region. Subsequently, an objective function with constraints for in-wheel motor torque distribution was formulated, targeting both optimal energy efficiency and maximum tire stability margin. Furthermore, the extension distances from the actual vehicle state to the stability boundaries were computed to determine adaptive weighting coefficients for these dual objectives. Finally, a Matlab/Simulink 2018a and Carsim2019 co-simulation platform was built to implement and test the proposed method. Simulations under the NEDC urban driving cycle and double-lane-change driving conditions were conducted to evaluate the following three distribution strategies: energy-optimal, stability-oriented, and extenics coordinated control. The results demonstrated that, regarding vehicle stability performance, extenics coordinated control showed a slightly inferior performance to the stability-oriented approach but substantially outperformed the energy-optimal strategy. In terms of energy consumption, the energy-optimal strategy achieved the lowest loss and the stability-oriented strategy showed the highest, while the extenics coordinated control presented intermediate results of 5.4 × 10⁹ J and 9.7 × 10⁷ J, respectively, under two driving conditions, representing reductions of 2.17% and 11.2% compared to the stability-oriented method. The proposed torque distribution method establishes an effective balance between energy-optimal and stability-oriented objectives. This method not only ensures satisfactory driving stability, but also reduces energy loss in in-wheel motors. Full article

In today’s rapidly evolving business environment, digitalization has emerged not only as a technological trend but also as a strategic imperative. This paper develops a conceptual framework that examines how Industry 4.0 (I4.0) technologies and tools drive strategic innovation and enable the transformation of business models. Based on a systematic literature review, the framework identifies a set of organizational and contextual preconditions (strategic vision, organizational culture, digital skills, infrastructure, financial resources, and regulatory conditions) that can act as either enablers or barriers to innovation. The analysis reveals that these preconditions give rise to two contrasting innovation cycles: a virtuous cycle, where favourable conditions amplify the adoption of digital technologies and foster business model transformation, and a vicious cycle, where unfavourable conditions reinforce technological inertia and hinder strategic development. By integrating insights from innovation management, digital transformation, and business model theory, the framework offers a nuanced understanding of how technology and strategy intersect and provides actionable guidance for managers seeking to move beyond operational improvements toward reimagining value creation, delivery, and capture in the digital age. Full article

This study investigates the effect of Reynolds number on unsteady buffet characteristics of the OAT15A supercritical airfoil under transonic conditions (Ma = 0.73, AOA = 3.5°) using DDES based on the SST k-ω turbulence model coupled with the γ-Reθ transition model. Results show that, compared with fully turbulent conditions, the free-transition cases exhibit a more downstream shock position and higher lift. Under fully turbulent conditions, higher Reynolds numbers drive the shock downstream and enhance its stability. Under free-transition conditions, the shock moves downstream at low Reynolds numbers but shifts upstream at high Reynolds numbers due to changes in the transition location. During the unsteady buffet cycle at low Reynolds numbers, the lift increases as the shock moves downstream and the separation region shrinks. The lift reaches its maximum when the separation is minimal, corresponding to a quiet flow state with weak acoustic emission. As the lift decreases, a large separation region forms behind the shock, forcing the shock upstream and reducing the lift to its minimum. At high Reynolds numbers, the buffet cycle changes: the shock becomes more stable; trailing-edge vortex shedding intensifies; lift oscillation amplitude decreases; and buffet frequency increases. Full article

Under global climate change, the response of mountain forest soil carbon pools to elevation is central to carbon cycle research, and Pinus yunnanensis stands, which span a wide elevation range, serve as a typical subject for studying how soil properties in mountain ecosystems respond to elevation gradients. To reveal the variation patterns and underlying regulatory mechanisms of soil nutrients and organic carbon components in Pinus yunnanensis stands across different altitudinal gradients, this study took Pinus yunnanensis stands at three altitude gradients (1604 m, 2377 m, 3206 m) within Yunnan Province as research objects, collected stratified soil samples, and determined soil chemical properties, organic carbon components, enzyme activity, and microbial biomass. The results showed that changes in elevation significantly influence soil nutrient content: soil pH gradually decreases with increasing elevation; soil organic carbon, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, and readily available potassium first increase then decrease with elevation, reaching their highest levels at Jin’an Town (JA); total phosphorus and total potassium gradually increase with elevation, peaking at Xiaozhongdian Town (XZD); particulate organic carbon, mineral-bound organic carbon, and microbial biomass carbon follow similar patterns to organic carbon, all showing enrichment in the surface layer; JA exhibits the highest carbon cycle enzyme activity and bacterial biomass, while XZD shows dominant fungal biomass. Partial Least Squares Path Modeling (PLS-PM) analysis indicates that elevation strongly positively drives microbial biomass, indirectly regulating enzyme activity and chemical properties, ultimately jointly influencing organic carbon components. In conclusion, soil properties varied markedly, and under stable precipitation, the thermal gradient emerged as the primary driver; the mid-elevation site (2377 m) showed optimal soil functioning, with peak nutrient and carbon stocks linked to heightened microbial and enzymatic activity, and path modeling confirmed that temperature, via microbial mediation, is the key regulator of soil organic carbon dynamics in these pine forests. Full article

Rural Sub-Saharan Africa (SSA) faces limited transport options, with many dispersed settlements dependent on poorly maintained roads. Light delivery vehicles (LDVs) can improve mobility, but conventional internal combustion engine vehicles are costly to operate and contribute to emissions. Electric vehicle (EV) conversions offer a practical alternative by extending vehicle life and reducing energy, maintenance, and environmental costs. This study presents a simulation-based framework to guide LDV conversion design for rural SSA. The framework includes component sizing, subsystem modeling, and full-vehicle benchmarking under representative conditions. Scenario-based simulations include trips ranging from shorter local access routes to longer remote trips on both paved and dirt roads, allowing the conversion’s performance to be quantified under representative conditions. A sensitivity analysis indicates that road grade, aerodynamic drag, and rolling resistance are the primary factors driving energy use variation. Using the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) drive cycle, the conversion energy consumption (∼217 Wh/km) comparable to that of commercial electric vans, though the range is reduced relative to its battery capacity. The framework establishes a benchmark for EV conversion performance in SSA and supports broader adoption of sustainable rural mobility solutions. Full article

Altitude-driven environmental changes influence the persistence of soil organic carbon (SOC) via microbial metabolic pathways. However, the degree to which the network robustness of microbial communities directly predicts the persistence of organic carbon in alpine mountain forests remains unclear. This study focused on the Qilian Sabina przewalskii forest, situated along an altitude gradient of 2900–3400 m in the Qilian Mountains, systematically exploring the organization of soil microbial communities, the co-occurrence networks’ robustness, and their predictive capacity for organic carbon storage. The results indicate that altitude, as a critical driving factor, not only alters the physicochemical properties, microbial composition, and diversity of the soil but also significantly impacts its complexity and network robustness. The complexity and robustness of the microbial network are highest in the mid-altitude region (3100–3200 m), which is conducive to the development of robust microbial networks. Both bacterial α diversity and network robustness exhibit positive correlations with SOC, whereas fungal diversity shows a negative correlation with SOC. Furthermore, statistical modeling revealed that indices of microbial co-occurrence network robustness were stronger predictors of SOC storage than classical alpha-diversity indices. The structural equation model reveals that microbial biomass nitrogen (MBN) serves as a key mediating factor linking microbial diversity and SOC. Soil characteristics emerge as the primary direct driving factor, whereas the robustness of microbial networks exerts a significant yet minor direct and mediating influence. This study underscores that the robustness of microbial networks, rather than their diversity, is a critical predictor of soil organic carbon in high-altitude mountain forests. It offers a novel theoretical framework for understanding the mechanisms of the carbon cycle in mountain forest ecosystems in the context of climate warming. Full article