Search Results (13,392)

Compared to traditional marine productivity, marine new-quality productivity (MNQP) is composed of advanced productive forces driven by the deepening application of new technologies, is characterized by the rapid emergence of new industries, new business models, and new modes of operation, and is marked by a substantial increase in total factor productivity in the marine economy. It has, therefore, become a new engine and pathway for China’s development into a maritime power. The main research approaches and conclusions of this paper are as follows: ① Using a combined order relation analysis method–Entropy Weight Method (G1-EWM) weighting method that integrates subjective and objective factors, we measured the development level of China’s MNQP from 2006 to 2021 across two dimensions: “factor structure” and “quality and efficiency”. The findings indicate that China’s MNQP is developing robustly and still holds considerable potential for improvement. ② Utilizing Gaussian Kernel Density Estimation and Spatial Markov Chain analysis to examine the dynamic evolution of China’s MNQP, the study identifies breaking the low-end lock-in of MNQP as crucial for accelerating balanced development. Spatial imbalances in China’s MNQP may exist both at the national level and within the three major marine economic zones. ③ To further examine potential spatial imbalances, Dagum Gini decomposition was employed to assess regional disparities in China’s MNQP. The DER polarization index and EGR polarization index were used to analyze spatial polarization levels, revealing an intensifying spatial imbalance in China’s MNQP. ④ Finally, geographic detectors were employed to identify the factors influencing spatial imbalances in China’s MNQP. Results indicate that these imbalances result from the combined effects of multiple factors, with marine economic development emerging as the core determinant exerting a dominant influence. The core conclusions of this study provide theoretical support and practical evidence for advancing the enhancement of China’s MNQP, thereby contributing to the realization of the goal of building a maritime power. Full article

Utilizing forestry and agricultural byproducts like wood and hemp residues advance sustainable additive manufacturing (AM), while reducing material costs. This study investigated the development and characterization of wood–sodium silicate composites incorporating hemp hurd and hemp fibers for AM applications. Formulations varied by wood fiber type (unsifted, 40 mesh, and pellet), sodium silicate concentration (50–60 wt%), and hemp hurd content (0–15 wt%). Properties evaluated include particle size and bulk density of the constituent materials, rheological behavior, extrusion performance, composite bulk density, and flexural and compressive strengths. Rheology and extrusion were largely influenced by the liquid content. Mixtures with low liquid content (50 wt% sodium silicate) had high motor power and low viscosity. As liquid content increased, motor power decreased, while viscosity increased up to 55 wt% and then decreased at 60 wt%. Mechanical properties correlated with particle size, where finer particles enhanced strength. A cost analysis was conducted using raw material prices to determine the economic feasibility of each formulation. Finally, the formulations were evaluated based on strength-to-cost ratios, extrudability and processability. The formulation with pellet wood fibers, 55 wt% sodium silicate, and 10 wt% hemp hurd achieved a high ratio of 73.0 MPa/$ while maintaining low motor power. This formulation offered additional benefits which are discussed qualitatively. Full article

The construction sector generates a substantial proportion of Australia’s total solid waste, underscoring the urgent need for sustainable and circular resource management approaches to mitigate environmental impacts. This study evaluates the environmental performance and circularity potential of construction and demolition waste (C&DW) management across five Australian states. Three representative building cases were modelled using both national-average and state-specific recycling rates and electricity generation mixes. A Life Cycle Assessment (LCA) was conducted to compare two end-of-life pathways: landfill and recycling. Key parameters, including transport distance and substitution ratio, were also examined to assess their influence on carbon outcomes. The results show that regional variations in electricity generation mix and recycling rate have a strong influence on the total Global Warming Potential of C&DW management. States with cleaner electricity grids and higher recycling rates, such as South Australia, exhibited notably lower recycling-related emissions than those relying on fossil-fuel-based power. The findings highlight the importance of incorporating regional characteristics into sustainability assessments of C&DW management and provide practical insights to support Australia’s transition toward a circular and low-carbon construction industry. Full article

Energy management strategies (EMSs) play a critical role in improving both the efficiency and durability of fuel cell electric vehicles (FCEVs). To overcome the limited adaptability and insufficient durability consideration of existing deep reinforcement learning-based EMSs, this study develops a degradation-aware energy management strategy based on the Soft Actor–Critic (SAC) algorithm. By leveraging SAC’s maximum-entropy framework, the proposed method enhances exploration efficiency and avoids premature convergence to operating patterns that are unfavorable to fuel cell durability. A reward function explicitly penalizing hydrogen consumption, power fluctuation, and degradation-related operating behaviors is designed, and the influences of reward weighting and key hyperparameters on learning stability and performance are systematically analyzed. The proposed SAC-based EMS is evaluated against Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) strategies under both training and unseen driving cycles. Simulation results demonstrate that SAC achieves a superior and robust trade-off between hydrogen economy and degradation mitigation, maintaining improved adaptability and durability under varying operating conditions. These findings indicate that integrating degradation awareness with entropy-regularized reinforcement learning provides an effective framework for practical EMS design in FCEVs. Full article

Resting-state functional connectivity (rsFC) provides insight into the intrinsic organization of brain networks and is increasingly recognized as a sensitive marker of age-related neural changes. Functional near-infrared spectroscopy (fNIRS) offers a portable and cost-effective approach to measuring rsFC, including in naturalistic settings. However, its sensitivity to age-related alterations in network topology remains poorly characterized. Here, we applied graph-based analysis to resting-state fNIRS data from 57 healthy participants, including 26 young adults (YA, 18–30 years) and 31 older adults (OA, 50–77 years). We observed that older adults exhibited a marked attenuation of low-frequency oscillation (LFO) power across all hemoglobin contrasts, corresponding to a 5–6-fold reduction in spectral power. In addition, network analysis revealed altered topological organization under matched sparsity conditions, characterized by reduced degree heterogeneity and increased segregation in older adults, with the strongest differences observed in the default mode (DMN), auditory, and frontoparietal control (FPC) networks. Network visualizations further indicated a shift toward more right-lateralized and posterior hub organization in older adults. Together, the coexistence of reduced oscillatory power and increased connectivity suggests that fNIRS-derived rsFC reflects combined neural and non-neural hemodynamic influences, including increased coherence arising from age-related vascular and systemic physiological processes. Overall, our findings demonstrate that fNIRS is sensitive to age-related changes in large-scale hemodynamic network organization. At the same time, sensitivity to non-neural hemodynamics highlights the need for cautious interpretation, but it may provide complementary, clinically relevant signatures of aging-related changes. Full article

This paper proposes a regional inertia estimation method in power systems using ambient data measured by phasor measurement units (PMUs). The proposed method employs band-pass filtering to suppress the low-frequency influence of mechanical power and to attenuate high-frequency noise and discrepancies between rotor speed and electrical frequency. By utilizing a simple first-order AutoRegressive Moving Average with eXogenous input (ARMAX) model, this process allows the inertia constant to be directly identified. This method requires no prior model order selection, rotor speed estimation, or computation of the rate of change of frequency (RoCoF). The proposed method was validated through simulation on three benchmark systems: the Kundur two-area system, the IEEE Australian simplified 14-generator system, and the IEEE 39-bus system. The method achieved area-level inertia estimates within approximately ±5% error across all test cases, exhibiting consistent performance despite variations in disturbance models and system configurations. The estimation also maintained stable performance with short data windows of a few minutes, demonstrating its suitability for near real-time monitoring applications. Full article

Carbon capture is pivotal for achieving carbon neutrality; however, its high energy consumption severely limits the operational flexibility of power plants and remains a key challenge. This study, targeting a full flue gas carbon capture scenario for a 1000 MW coal-fired power plant, identified the dual-element (“steam” and “power generation”) coupling convergence mechanism. Based on this mechanism, a comprehensive set of mathematical model equations for the “carbon–electricity–heat” coupling process is established. This model quantifies the dynamic relationship between key operational parameters (such as unit load, capture rate, and thermal consumption level) and system performance metrics (such as power output and specific power penalty). To address the challenge of flexible operation, this paper further proposes two innovative coupled modes: steam thermal storage and chemical solvent storage. Model-based quantitative analysis indicated the following: (1) The power generation impact rate under full THA conditions (25.7%) is lower than that under 30% THA conditions (27.7%), with the specific power penalty for carbon capture decreasing from 420.7 kW·h/tCO₂ to 366.7 kW·h/tCO₂. (2) Thermal consumption levels of the capture system are a critical influencing factor; each 0.1 GJ/tCO₂ increase in thermal consumption leads to an approximate 2.83% rise in unit electricity consumption. (3) Steam thermal storage mode effectively reduces peak-period capture energy consumption, while the chemical solvent storage mode almost fully eliminates the impact on peak power generation and provides optimal deep peak-shaving capability and operational safety. Furthermore, these modeling results provide a basis for decision-making in plant operations. Full article

As an innovative foundation type specifically developed for seabed conditions characterized by shallow overburden overlying bedrock, driven embedded rock-socketed jacket offshore wind turbines achieve high bearing capacity by embedding the pile tips into the bedrock. However, the mechanical behavior of this foundation system has not yet been fully clarified. In this study, based on the engineering conditions of an offshore wind power project in Fujian, a 1:100 scaled physical model test is conducted to validate Plaxis 3D finite-element model. On this basis, a parametric sensitivity analysis is conducted to investigate the influences of key geotechnical properties, pile rock-socketed depth, and geometric parameters, with the aim of elucidating the mechanisms governing the lateral loading behavior of the jacket foundation. The results show that the numerical simulations are in good agreement with the experimental measurements. Among all piles, the front-row pile exhibits the most significant displacement at the pile top at the mudline, reflecting the asymmetry in load transfer and deformation of the pile foundation system. The ultimate bearing capacity varies by about 91.7% among different bedrock types, while the influence of rock weathering degree on the lateral bearing performance of the foundation is about 4.7%. The effects of Pile rock-socketed depth and geometric parameters on the lateral bearing capacity of the foundation are approximately 15.2% and 80.8%, respectively. A critical threshold for rock-socket depth exists at about 6D (where D is the pile diameter), beyond which further improvements in embedment depth result in diminishing improvements in lateral bearing capacity. Full article

Semantic segmentation of transmission-line point clouds is fundamental to intelligent power inspection and grid asset management, as segmentation accuracy directly influences defect detection and facility assessment tasks. However, transmission-line point clouds collected across different voltage levels often show significant variations in density and geometric structure due to heterogeneous LiDAR sensors and flight configurations. Combined with the high cost of large-scale manual annotation, these factors limit the scalability of existing supervised segmentation methods. To overcome these challenges, we propose a geometry-consistency-guided unsupervised domain adaptation framework tailored for cross-voltage transmission-line point-cloud segmentation. The framework employs KPConvX as the backbone and integrates three progressive components. First, a geometric consistency constraint enhances robustness to spatial variations and enables extraction of structural features invariant across voltage levels. Second, a domain feature alignment module reduces distribution shifts through global feature transformation. Third, a minimum-entropy-based pseudo-label refinement strategy improves the reliability of pseudo-labels during self-training. Experiments on a multi-voltage transmission-line dataset demonstrate the effectiveness of the proposed method. With the KPConvX backbone, the framework achieves 66.1% mean Intersection over Union (mIoU) and 94.3% overall accuracy on the unlabeled 110 kV target domain, exceeding the source-only baseline by 15.6% mIoU and outperforming several state-of-the-art UDA methods. This work provides an efficient, annotation-friendly solution for cross-voltage point-cloud segmentation and offers a promising direction for domain adaptation in complex power-grid environments. Full article

A reading of the American Revolution and the post-Civil War Reconstruction period through the lens of W.E.B. Du Bois’s early writings provides new insights into his theory of racial monopoly capitalism. Many Americans saw the 1776 revolution as an idealistic fight for liberty, for the slaveholding elite who held disproportionate power within the revolutionary coalition; however, consolidating power and defending their property and expansionist ambitions were primary objectives. For them, the Revolution was a strategic move to establish racial nationalism and preserve slaveholder control over economic growth and national power. A century later, Du Bois’s analysis of the “bargain of 1876” revealed a similar consolidation of power, influencing both his research on the revolutionary period and his writings on Reconstruction. The political deal in 1876 abandoned the promise of Reconstruction’s “abolition democracy,” restoring white supremacist rule. Du Bois saw this as the victory of monopoly capital, which used racism to weaken interracial labor solidarity and enforce a system of super-exploitation. By linking 1776 to 1876, Du Bois demonstrated that U.S. capitalist development had been shaped by racial oppression from its settler-colonial roots through the rise of monopoly capitalism, consistently blocking the achievement of a true, non-racial democracy. Full article

As sustainability becomes a strategic priority, the Information Technology (IT) sector faces pressure on both reducing its environmental impact and leading in innovation. This study examines how Green Human Resource Management (GHRM) practices influence employees’ Green IT Attitudes (GITA) and beliefs within the IT industry. Guided by the Belief–Action–Outcome (BAO) framework, it explores how HR strategies can foster eco-conscious mindsets that support sustainable behaviour. A quantitative cross-sectional design was used, collecting data through a validated questionnaire. The study was conducted in Australia, focusing on IT professionals employed. Responses from 112 IT professionals, determined through G*Power sample estimation, were analysed using SPSS 28.0.1 with regression techniques to assess the relationship between GHRM practices and environmental attitudes and beliefs. Results indicate that GHRM practices have a modest but significant positive effect on employees’ green IT attitudes and beliefs, supporting the view that structured HR initiatives can shape sustainability-driven mindsets. The findings emphasize the strategic role of HR in embedding sustainability within organizational culture, particularly in technology-driven environments. The study offers practical guidance for IT organizations aiming to integrate sustainability into internal systems by leveraging HRM. Future research should examine moderating variables and long-term behavioural effects, enhancing our understanding of sustainability-focused HRM in the digital era. Full article

Ultra-high voltage (UHV) power transmission has become a prerequisite for the development of clean energy. However, arcs generated by UHV circuit breakers can easily lead to safety incidents, and developing arc-extinguishing gases with low global warming potential (GWP) presents certain challenges. It is a fact that fluorolefins, as a class of fluorinated compounds with low GWP, show high application potential in replacing traditional arc-extinguishing agents. In this study, all six conjugated perfluorinated compounds, including C₆F₆ and C₆F_8, were calculated within the density functional theory (DFT) framework at the B3LYP/6-311+G(d,p) level. The dipole moments, HOMO/LUMO energy gaps, and the inherent aromaticity of annular molecules under external electric fields of these fluorinated molecules are investigated accordingly. By analyzing these results, it is found that the influence of the conjugated structure on the stability of arc-extinguishing gases under high-voltage conditions was partially elucidated, providing useful insights for the subsequent development of environmentally friendly and high-performance arc-extinguishing gases. Full article

Oxidative stress contributes significantly to chronic disease burden, necessitating identification of accessible dietary antioxidant sources. Pigeon peas (Cajanus cajan L.) contain substantial bioactive compounds, yet most exist in bound forms with limited bioavailability. This study evaluated wild fermentation combined with systematic extraction optimization to enhance antioxidant recovery from pigeon peas. Seeds underwent wild fermentation in brine solution, followed by extraction under varying conditions (seven solvent systems, three temperatures, and three-time durations). Multiple complementary assays assessed antioxidant capacity (total phenolic content, DPPH radical scavenging, ferric reducing power, and ABTS activity). Fermentation substantially improved antioxidant properties across all parameters, with particularly pronounced effects on radical scavenging activities. Extraction optimization identified 70% methanol at 40 °C for 24 h as optimal, demonstrating marked improvements over conventional protocols. Strong intercorrelations among assays confirmed coordinated enhancement of multiple antioxidant mechanisms rather than isolated changes. The findings demonstrate that both biotechnological processing and analytical methodology critically influence antioxidant characterization in pigeon peas. This integrated approach offers practical guidance for developing antioxidant-rich functional foods, particularly relevant for resource-limited settings where pigeon peas serve as dietary staples. The study establishes foundation for translating fermentation technology into nutritional interventions, though further research addressing bioavailability, microbiological characterization, and bioactive compound identification remains essential. Full article

The paper offers a practical method for selecting an electric pump and battery pack for low-thrust liquid rocket engines. The approach combines 0D/1D modeling of hydraulic, electromechanical, and thermal subsystems in a single environment and is supplemented by sensitivity analysis, correlation analysis, and Monte Carlo simulation with N = 3000 iterations to verify the stability of the estimates. The methodology has been tested on mission profiles in the 5–50 kN thrust range and shows that the electric pump scheme is most effective at low thrusts, while an increase in thrust leads to a disproportionate increase in energy and thermal loads and narrows the scope of applicability. The determining factors remain the hydraulic efficiency of the pump η_pump and the oxidizer pressure; electrical parameters such as bus voltage and internal battery resistance have less influence and become noticeable at high power levels. Modeling confirms the stability of the obtained estimates; at a thrust of 20 kN, the spread of the battery block mass is close to ±10%. The proposed methodology provides quantitative guidelines in the early stages of design and helps to justify the scope of application of electric pump liquid rocket engines; expansion beyond low thrust requires progress in battery technologies. Full article

As shallow coal resources become increasingly depleted, coal mining is extending to greater depths, making mine thermal hazards an increasingly prominent issue. This paper proposes a novel system for synergistic geothermal energy extraction from deep coal mine aquifers and coal seam cooling, aimed at achieving integrated geothermal exploitation and mine thermal hazard control. Based on a high-temperature mine in the Yuanyanghu Mining Area of Ningxia, a dual-stage, single-branch three-dimensional numerical model was established to simulate the effects of water injection pressure, water injection temperature, and level spacing on the system’s cooling performance and geothermal energy extraction efficiency. The results indicate that increasing injection pressure enhances early-stage geothermal energy extraction capacity and coal seam cooling rate, but the heat extraction power declines over long-term operation as the produced water temperature approaches the injection temperature. Lowering injection temperature significantly improves water–rock heat exchange efficiency, accelerates coal seam cooling, and increases geothermal energy extraction. Increasing level spacing helps improve geothermal energy extraction power but weakens the direct cooling effect on the coal seam. Considering the influence patterns of each parameter, the optimal combination was determined as water injection pressure of 10 MPa, water injection temperature of 10 °C, and level spacing of 80 m, which delivers the best overall performance by enabling rapid coal seam cooling and sustained geothermal energy extraction, with a cumulative geothermal output reaching 129.45 MW after 10 years of operation. This study provides a theoretical basis and technical reference for the integrated management of thermal hazards and geothermal resource development in deep coal mines. Full article