Search Results (166,704)

Integrated energy systems (IESs) are increasingly being deployed and expanded, which integrate various energy infrastructures to enable flexible conversion and utilization among different energy forms. To facilitate collaboration among operators of varying scales and fully leverage the economic and environmental benefits of multi-integrated energy systems (MIESs), this study develops a peer-to-peer (P2P) energy sharing framework for MIES based on asymmetric Nash bargaining. First, an IoT-based P2P energy sharing architecture for MIES is proposed, which incorporates coordinated electricity–heat–gas multi-energy synergy within IES models. Carbon capture systems (CCS) and power-to-gas (P2G) units are integrated with carbon trading mechanisms to reduce carbon emissions. Then, an MIES energy sharing operational model is established using Nash bargaining theory, subsequently decoupled into two subproblems: alliance benefit maximization and individual IES benefit distribution optimization. For subproblem 2, an asymmetric bargaining method employing natural exponential functions quantifies participant contributions, enabling fair distribution of cooperative benefits. Finally, the alternating direction method of multipliers (ADMM) is employed to solve both subproblems distributively, effectively preserving participant privacy. The effectiveness of the proposed method is verified by case simulation, demonstrating reduced operational costs across all IESs alongside equitable benefit allocation proportional to energy-sharing contributions. Carbon emission amounts are simultaneously reduced. Full article

This study investigates the control of the phase-structural state in Ni–45Ti–xCu (x = 5, 7 at.%) shape memory alloys fabricated via a shortened powder metallurgy route: mechanical activation → spark plasma sintering (SPS) → heat treatment. Compact samples were produced from mechanically alloyed powders (650–750 rpm, up to 5 h) and sintered at 900 °C. The structure and microstructure were characterized using X-ray diffraction (to identify B2/B19′/Ni₄Ti₃ phases and assess ordering) and SEM–BSE/EDS (to analyze morphology, porosity, and Ni-rich precipitates). Two post-processing treatments were applied: single-stage annealing (500 °C, 2 h) and a three-stage treatment (900 °C/30 min → water quenching → 300 °C/20 min). Mechanical alloying transformed the initial elemental powder mixture (fcc-Ni, hcp-Ti, fcc-Cu) into a supersaturated fcc-(Ni,Cu,Ti) solid solution with emerging NiTi phases, with a minimum particle size achieved after ~300 min at 750 rpm. SPS compaction yielded a high-density matrix consisting predominantly of the B2 phase. Single-stage annealing preserved B19′ martensite and Ni₄Ti₃ precipitates, particularly in the 5 at.% Cu alloy. In contrast, the three-stage treatment dissolved the Ni₄Ti₃ precipitates, suppressed the formation of B19′ and R phases, and stabilized a highly ordered B2 matrix. Increasing the Cu content from 5 to 7 at.% significantly enhanced the B2 phase fraction, reduced secondary nickel-rich phases, and improved structural homogeneity, evidenced by a continuous neck network and closed porosity. The optimized condition—7 at.% Cu combined with the three-stage annealing—produced a microstructure with >95% B2 phase, <1% Ni₄Ti₃, and ~98% relative density. This forms the prerequisite microstructural state for a narrow transformation hysteresis and high functional cyclic stability. Full article

The growing environmental concern over waste tire accumulation necessitates innovative recycling strategies in construction materials. Therefore, this study aims to develop and evaluate sustainable concrete by integrating waste tire rubber (WTR) aggregates of different sizes and recycled waste tire steel fibers (WTSFs), assessing their combined effects on the mechanical and microstructural performance of concrete through experimental and analytical approaches. WTR aggregates, consisting of fine (0–4 mm), small coarse (5–8 mm), and large coarse (11–22 mm) particles, were used at substitution rates of 0–20%; WTSF was used at volumetric dosages of 0–2%, resulting in a total of 40 mixtures. Mechanical performance was evaluated using density and pressure resistance tests, while microstructural properties were assessed using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The findings indicate systematic decreases in density and compressive strength with increasing WTR ratio; the average strength losses were approximately 12%, 20%, and 31% at 5%, 10%, and 20% for WTR substitution, respectively. Among the WTR types, the most negative effect occurred in fine particles (FWTR), while the least negative effect occurred in coarse particles (LCWTR). The addition of WTSF compensated for losses at low/medium dosages (0.5–1.0%) and increased strength by 2–10%. However, high dosages (2.0%) reduced strength by 20–40% due to workability issues, fiber clumping, and void formation. The highest strength was achieved in the 5LCWTR–1WTSF mixture at 36.98 MPa (≈6% increase compared to the reference/control concrete), while the lowest strength was measured at 16.72 MPa in the 20FWTR–2WTSF mixture (≈52% decrease compared to the reference/control). A strong positive correlation was found between density and strength (r, Pearson correlation coefficient, ≈0.77). SEM and EDX analyses confirmed the weak matrix–rubber interface and the crack-bridging effect of steel fibers in mixtures containing fine WTR. Additionally, a hybrid prediction model combining physics-informed neural networks (PINNs) and CatBoost, supported by data augmentation strategies, accurately estimated compressive strength. Overall, the results highlight that optimized integration of WTR and WTSF enables sustainable concrete production with acceptable mechanical and microstructural performance. Full article

This study investigates how different vegetation types influence the molecular structure and abundance of soil organic carbon (SOC), as well as their influence on microbial metabolic pathways and community composition. Soil samples were collected from four different sites: a woodland dominated by Drypetes perreticulata (DP), a woodland dominated by Horsfieldia hainanensis (HM), a Zea mays L. field (ZL), and a citrus reticulata orchard (CB). The molecular structure of soil organic carbon (SOC) was characterised using Fourier Transform Infrared (FTIR) spectroscopy, identifying aromatic carbon (ArC), polysaccharide carbon (PSC), alkyl carbon (AlkC), amine carbon (AmC), ether carbon (EtC), and olefin carbon (OleC). Our results indicated significant variations across vegetation types: DG exhibited a significantly higher ArC content, while maize fields showed lower PSC levels. To analyse the relationships between different samples, we employed principal component analysis (PCA), which revealed distinct organic carbon structures across vegetation types, with the forests (DG and HM) significantly differing from agricultural sites (ZL and CB). Additionally, the 16S V3_V4 region of soil bacteria was sequenced using high-throughput sequencing. We employed PICRUSt2 to predict microbial metabolic pathways, revealing consistent core metabolic functions across samples but significant variations in secondary metabolism, with HM samples exhibiting the most distinctive metabolic profiles. Redundancy analysis (RDA) further demonstrated that microbial metabolic pathway variation explained 55.66% of organic carbon structure variance. Key microbial taxa exhibited significant associations with specific carbon source types and functional pathways. These findings highlight the pivotal mechanisms by which different vegetation types regulate soil organic carbon structure and composition by driving changes in microbial metabolic traits and community assembly. This study provides a mechanistic basis for understanding the coupling between vegetation, microorganisms, and carbon cycling, offering significant guidance for optimising vegetation restoration strategies, enhancing soil carbon sequestration capacity, and advancing carbon management practices based on microbial regulation. Full article

Geological Carbon Sequestration (GCS) plays a crucial role in addressing climate change, particularly in oil and gas development. Understanding the reaction of supercritical CO₂ under in situ conditions and its effects on minerals is essential for advancing GCS technology. This study investigates the reaction mechanisms of feldspar (potassium and sodium feldspar) and clay minerals (chlorite, illite, montmorillonite, kaolinite) in CO₂ environments. The impacts on mineral crystal structures, morphologies, and elemental compositions were analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and ion concentration measurements (ICP-OES and ICP-MS). The results show that feldspar minerals exhibit lower reaction rates, with sodium feldspar dissolving faster than potassium feldspar, due to the higher solubility of sodium ions in acidic conditions. Chlorite showed significant crystal structure damage after 30 days, while montmorillonite underwent both dissolution and precipitation, influenced by interlayer cation dissociation. Kaolinite exhibited minimal reaction, primarily showing localized dissolution. Additionally, the formation of siderite (FeCO₃) was observed as Fe²⁺ substituted for Ca²⁺ in CaCO₃, highlighting the role of iron-bearing carbonates in CO₂ interactions. The study provides insights into the factors influencing mineral reactivity, including mineral structure, ion exchange capacity, and solubility, and suggests that chlorite, montmorillonite, and illite are more reactive under reservoir conditions, while kaolinite shows higher resistance to CO₂-induced reactions. These findings offer valuable data for optimizing GCS technologies and predicting long-term sequestration outcomes. Full article

Amid the global energy transition, geothermal energy, as a clean, stable, and renewable energy source, serves as a core direction for energy structure optimization. The development of medium-deep geothermal reservoirs is dominated by thermo–hydro–mechanical (THM) multi-physics coupling effects, yet the quantitative regulation laws of their operational parameters remain unclear. In this study, a numerical model for geothermal extraction considering THM multi-physics coupling was established. Using the single-factor variable method, simulations were conducted within the set parameter ranges of injection–production pressure difference, well spacing, and injection temperature. The spatiotemporal evolution characteristics of the temperature field, the dynamic temperature–pressure responses at the midpoint of injection–production wells and production wells, and efficiency indicators, such as instantaneous heat extraction power and cumulative heat extraction, were analyzed and quantified. The results show that a larger pressure difference accelerates the expansion of the cold zone in the reservoir, which improves short-term heat extraction efficiency but increases the risk of long-term thermal depletion; a smaller well spacing leads to higher initial heat production power but results in lower long-term cumulative heat extraction due to rapid heat consumption; within the normal temperature range of 16–24 °C, the injection temperature has a negligible impact on heat extraction efficiency. This study clarifies the regulatory laws of operational parameters and provides theoretical support for well pattern design and injection–production process optimization in medium-deep geothermal development. Full article

Industrialized processing has increased the complexity of the food supply chain. Concerns about food-related risks have increased consumer interest in food traceability. Traceability systems are regarded as effective tools for mitigating information asymmetry and enhancing food quality and safety. However, the design of traditional food traceability systems overlooks the risk of information overload. Based on information overload theory, this study designs an artificial intelligence (AI) traceability assistant as an innovative tool to optimize traditional food traceability systems and examines its positive effects. This study focuses on prepared foods as the research objects, selecting three types of prepared foods (Kung Pao chicken, fish-flavored shredded pork, and pickled fish) and three food traceability tasks (preservatives, sweeteners, and drug residues) as experimental stimuli. Through three online scenario experiments, 747 valid responses were collected. This study explores the impact of AI traceability assistant design on positive consumer engagement behaviors and its underlying mechanism. The results reveal that the AI traceability assistant significantly promotes positive consumer engagement behaviors. This positive effect is mediated by perceived system ease of use. Furthermore, perceived product risk positively moderates the impact of the AI traceability assistant on perceived system ease of use. Perceived product risk strengthens the mediating effect of perceived system ease of use. This study contributes a novel theoretical perspective for research on food traceability systems and reveals the underlying mechanism through which the AI traceability assistant exerts its positive effect. In practice, it provides actionable guidance for food producers implementing digital traceability solutions. Full article

The glass-forming ability of short-chain alkanes remains a fundamental challenge in condensed matter physics. This study investigates the structural properties of n-hexane (C₆H₁₄) and decane (C₁₀H₂₂) under two distinct cooling regimes using Raman spectroscopy: fast cooling (~50–100 K/s via contact freezing on a copper substrate at 77 K) and conventional cooling (~1–5 K/s). Despite employing rapid cooling protocols, both alkanes underwent crystallization without forming amorphous phases. n-Hexane formed a defective crystalline structure characterized by broad spectral bands (FWHM ~40–45 cm⁻¹) and diffuse phase transitions in the 180–200 K range, while decane exhibited highly ordered crystalline structures with sharp spectral features (FWHM ~15–20 cm⁻¹) and abrupt transitions at 220–240 K. Quantitative analysis of characteristic Raman bands (skeletal deformations, C-C stretching, and C-H stretching vibrations) revealed fundamental differences in crystallization mechanisms related to molecular chain length. The study demonstrates that contact freezing methods are fundamentally incapable of achieving the extreme cooling rates (>10⁴ K/s) and ultra-thin film conditions (<1 μm) necessary for alkane vitrification. These findings establish spectroscopic diagnostic criteria for distinguishing between defective and well-ordered crystalline structures and define the limitations of conventional cryogenic techniques for glass formation in alkanes. Full article

Laser Powder Bed Fusion (LPBF) technology represents one of the most promising additive manufacturing methods, enabling the production of components with high geometric complexity and a wide range of industrial and biomedical applications. In this study, the influence of both standard and high-productivity process parameters on the microstructure, porosity, surface roughness, and hardness of three commonly used materials, stainless steel 316L, aluminum alloy AlSi10Mg, and titanium alloy Ti6Al4V, was analyzed. The investigations were carried out on samples fabricated using the EOS M290 system, and their characterization was performed with scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), porosity analysis by point counting, Vickers hardness measurements, and optical profilometry. The obtained results revealed significant differences depending on the alloy and the applied parameters. For stainless steel 316L, the high-productivity variant led to grain refinement and stronger crystallographic orientation, albeit at the expense of increased porosity (0.11% vs. 0.05% for the standard variant). In the case of AlSi10Mg alloy, high-productivity parameters enabled a substantial reduction in porosity (from 0.82% to 0.27%) accompanied by an increase in hardness (from 115 HV1 to 122 HV1), highlighting their particular suitability for engineering applications. For the Ti6Al4V alloy, a decrease in porosity (from 0.17% to 0.07%) was observed; however, the increase in mechanical anisotropy resulting from a stronger texture may limit its application in cases requiring isotropic material behavior. The presented research confirms that optimization of LPBF parameters must be strictly tailored to the specific alloy and intended application, ranging from industrial components to biomedical implants. The results provide a foundation for further studies on the relationship between microstructure and functional properties, as well as for the development of hybrid strategies and predictive models of the LPBF process. Full article

In this study, aiming to develop novel biocomposites that offer competitive properties while retaining their renewable and biodegradable characteristics, a biodegradable polymer matrix (Mater-Bi^® HF51L2) was reinforced with natural particles extracted from the culm and leaf of Cymbopogon flexuosus (lemongrass). Particles (<500 µm) were incorporated at 10 and 20 wt.% via twin-screw extrusion followed by compression moulding. Morphological analysis via SEM revealed distinct structural differences between culm- and leaf-derived particles, with the latter exhibiting smoother surfaces, higher density, and better dispersion in the matrix, resulting in lower void content. Quasi-static mechanical tests showed increased stiffness with filler content, particularly for leaf-based composites. This material, at 20 wt.% filler loadings, enhanced the tensile and flexural moduli of the neat Mater-Bi approximately three and two times, respectively, a result attributed to enhanced interfacial adhesion. Rheological measurements (rotational and capillary) indicated significant increases in complex viscosity, particularly for leaf-filled systems, confirming restricted polymer chain mobility and good matrix–filler interaction. Dynamic mechanical thermal tests (DMTA) results showed an increased storage modulus and a shift in glass transition temperature (T_g) for all biocomposites in comparison to Mater-Bi matrix. Specifically, the neat matrix had a T_g of −28 °C, which increased to −24 °C and −18 °C for the 20 wt.% culm-reinforced and leaf-reinforced biocomposites, respectively. Overall, the leaf-derived particles demonstrated superior reinforcing potential, effectively improving the mechanical, rheological, and thermal properties of Mater-Bi-based biocomposites. Full article

Improving the well-being of rural residents remains a major policy challenge in developing countries. Previous studies have largely neglected the role of village leadership in influencing residents’ well-being. This study addresses this gap by examining the relationship between entrepreneurial village cadres (EVCs), defined as village leaders with entrepreneurial experience, and the subjective well-being (SWB) of rural residents in China. Using nationally representative data from the 2022 China Rural Revitalization Survey (CRRS), we found that EVCs significantly improve rural residents’ SWB. These results are robust to a series of identification strategies, including instrumental variable estimation and propensity score matching. Mechanism analysis reveals that EVCs exert their positive influence through three key channels: promoting income growth, enhancing democratic governance, and improving public services. Further heterogeneity analysis suggests that the effects of EVCs on SWB are more pronounced among non-poor households and in villages with external financial support. These findings enrich the literature on grassroots governance and well-being economics, while also offering practical implications for aligning leadership recruitment with broader goals of inclusive rural development. Full article

Green technological innovation integrates the two major strategies of innovation-driven development and green development and serves as a crucial pathway to achieving the goal of high-quality and sustainable development in the Yangtze River Economic Belt (YREB). Against the backdrop of regional integration, it is of great significance to study the coordinated development trend of green technological innovation, with urban agglomerations as the unit of study. This study takes 108 cities in the YREB as research objects, constructs a Green Technological Innovation Efficiency (GTIE) measurement framework based on a two-stage DEA model, and decomposes GTIE into Technological Innovation Efficiency (TIE) and Green Production Capacity (GCP). On this basis, using the System GMM model, this study examines the mechanism by which the economic connection structure affects GTIE, TIE, and GCP from the perspective of urban agglomeration spatial networks. The empirical results show that from 2006 to 2020, the overall GTIE of the YREB showed a steady upward trend, and its spatial pattern evolved from “high in the east and low in the west” to “coordinated development of the three major urban agglomerations.” The three urban agglomerations played a core leading role in the diffusion of regional green innovation. Specifically, the economic integration development of urban agglomeration spatial networks significantly promoted the improvement of GTIE; the spatial network structure of TIE within the urban agglomerations exerted a significant positive spillover effect on GCP, while the GCP network structure also showed a significant feedback effect on TIE. Overall, through strengthening the inter-city flow of innovative factors and collaboration, regional integration has effectively promoted the coordinated growth and diffusion of green technological innovation, providing important support for the high-quality improvement of regional productivity and contributing to the sustainable development of the region. Full article

The degradation of municipal solid waste (MSW) in landfills involves complex physical, chemical, and biological interactions that span multiple spatial and temporal scales. To better understand these dynamics, this study develops a comprehensive model that couples microbial, chemical, thermal, and hydraulic fields. The model captures bidirectional feedback mechanisms, such as heat and acid production from microbial metabolism, which in turn influence microbial activity and reaction pathways. A simplified one-dimensional formulation was solved using the finite difference method and validated against historical temperature data from real landfills. Simulation results indicate that temperature peaks at approximately 45 °C around the fifth year, followed by a gradual decline. pH and substrate concentration decrease over time but exhibit minimal variation with depth. The degradation rate reaches its maximum within two years and subsequently declines. These trends highlight the critical roles of temperature in initiating rapid degradation and substrate concentration in determining the endpoint of the reaction. This model provides a theoretical foundation for interpreting energy and mass transformation processes in landfills and offers practical insights for optimizing landfill management, reducing pollution, facilitating resource recovery and providing a theoretical model and prediction tool for sustainable waste management. Full article

Congenital heart defects (CHDs) occur in 50–75% of patients with 22q11.2 deletion syndrome (22q11.2DS), ranging from mild to severe manifestations. The genetic and environmental factors contributing to variable CHD phenotypes in 22q11.2DS are largely unknown. In this study, we used a mouse model of 22q11.2DS, termed Df1/+, to evaluate the effect of maternal vitamin A (VitA) dietary imbalance (supplementation or deficiency) on the incidence of aortic arch defects (AADs), which is a common type of CHD observed in both 22q11.2DS patients and Df1/+ mouse embryos. While most groups showed a previously observed 30% AAD incidence, two groups exhibited significantly higher rates: (1) Df1/+ embryos from WT mothers on a VitA-Supl diet (51% AADs) and (2) Df1/+ embryos from Df1/+ mothers on a VitA-Def diet (45% AADs). Thus, a low or high maternal VitA diet can increase the frequency of AADs in embryos depending on the maternal genotype. Transcriptomic analysis of the hearts of these high-risk embryos at embryonic day (E)18.5 revealed downregulation of key genes (Hdac3, Ptgds, Sirt5, Pfkm, and Lclat1) associated with energy metabolism pathways, such as oxidative phosphorylation and glycolysis, suggesting impaired cardiac recovery mechanisms. In conclusion, our findings demonstrate that altered VitA exposure can exacerbate AAD incidence in a maternal-genotype-dependent manner, highlighting the complex interplay between embryonic and maternal genetic background and environmental factors in CHDs associated with 22q11.2DS. Full article

Galectin-3 (Gal-3) is a histologic marker of pancreatic cancer and a potential therapeutic target. This study aimed to characterize a novel sulfated agarose-derived oligosaccharide (DP9) from marine algae, Gracilaria lemaneiformis, evaluate its Gal-3 inhibitory activity, and investigate its anti-pancreatic cancer mechanisms. Through controlled acid hydrolysis, a series of odd-numbered oligosaccharides (DP3-11) were obtained, in which DP9 showed the strongest Gal-3 inhibition in hemagglutination assays. Structural analysis confirmed DP9’s unique composition including an alternating β (1→4)-D-galactose and α (1→3)-3,6-anhydro-L-galactose backbone, featuring partial 6-O-methylation on β-D-galactose and 6-O-sulfation on 3,6-anhydro-α-L-galactose residues. Molecular docking revealed DP9’s binding to Gal-3’s carbohydrate recognition domain through key hydrogen bonds (His158, Arg162, Lys176, Asn179 and Arg186) and hydrophobic interactions (Pro117, Asn119, Trp181 and Gly235), with the sulfate group enhancing binding affinity. In vitro studies demonstrated DP9’s selective anti-pancreatic cancer activity against BxPC-3 cells, including inhibition of cell proliferation; S-phase cell cycle arrest; induction of apoptosis; and suppression of migration and invasion. Mechanistically, DP9 attenuated the Gal-3/EGFR/AKT/FOXO3 signaling pathway while showing minimal cytotoxicity to normal cells. This study first demonstrated that agarose-derived odd-numbered oligosaccharides (DP9) can serve as effective Gal-3 inhibitors, which proved its potential as a marine oligosaccharide-based therapeutic agent for pancreatic cancer. Full article