Search Results (884)

This study investigates the mechanical properties of titanium (Titanflex®) and cobalt-chromium (Co-Cr) alloys for potential use in removable denture bases. Titanium alloys have gained attention due to their biocompatibility and regulatory concerns surrounding Co-Cr, which has been classified as a carcinogenic, mutagenic, and toxic to reproduction (CMR) substance under EU MDR (2017/745). Using selective laser melting (SLM), test specimens of Titanflex® and Co-Cr alloys were 3D-printed at different angles (0°, 45°, 90°) and compared to conventionally cast Co-Cr samples. Tensile testing was conducted to assess modulus of elasticity (E), proof stress (Rp_0.2), ultimate tensile strength (Rm), elongation parameters (Ag, Agt, At), and maximum load (Fm). Results showed that Titanflex® printed at 45° (Ti45) exhibited the highest Rp_0.2, Rm, and Fm, indicating superior strength and plastic resistance. Ti0 displayed the greatest elongation properties, highlighting titanium’s ductility. Co-Cr alloys demonstrated higher stiffness but lower ductility. Printing orientation significantly influenced mechanical properties, particularly in 3D-printed samples. Overall, Ti45 presented a balanced profile of strength and flexibility, making it a promising candidate for denture bases, while Co-Cr remains a rigid alternative with established clinical use. Future research should explore long-term performance under functional and biological conditions to guide clinical application. Full article

Rapid population growth and accelerating urbanization are intensifying the demand for construction materials, particularly concrete, which is predominantly produced with Portland cement and natural aggregates. This reliance imposes substantial environmental burdens through resource depletion and greenhouse gas emissions. Within the framework of sustainable construction, recycled aggregates and industrial by-products such as fly ash, slags, crushed glass, and other secondary raw materials have emerged as viable substitutes in concrete production. At the same time, three-dimensional concrete printing (3DCP) offers opportunities to optimize material use and minimize waste, yet it requires tailored mix designs with controlled rheological and mechanical performance. This review synthesizes current knowledge on the use of recycled construction and demolition waste, industrial by-products, and geopolymers in concrete mixtures for 3D printing applications. Particular attention is given to pozzolanic activity, particle size effects, mechanical strength, rheology, thermal conductivity, and fire resistance of recycled-based composites. The environmental assessment is considered through life-cycle analysis (LCA), emphasizing carbon footprint reduction strategies enabled by recycled constituents and low-clinker formulations. The analysis demonstrates that recycled-based 3D printable concretes can maintain or enhance structural performance while mix-level (cradle-to-gate, A1–A3) LCAs of printable mixes report CO₂ reductions typically in the range of ~20–50% depending on clinker substitution and recycled constituents—with up to ~48% for fine recycled aggregates when accompanied by cement reduction and up to ~62% for mixes with recycled concrete powder, subject to preserved printability. This work highlights both opportunities and challenges, outlining pathways for advancing durable, energy-efficient, and environmentally responsible 3D-printed construction materials. Full article

Bioplastics are gaining attention as eco-friendly alternatives to conventional plastics, with Polybutylene Adipate Terephthalate (PBAT) emerging as a promising biodegradable substitute for polyethylene (PE) in food packaging. Commercial PBAT is often blended with other plastics or bio-based fillers to improve mechanical properties and reduce costs, though these additives can influence its environmental footprint. Therefore, this study quantifies the environmental impacts of producing PBAT resin blends reinforced with common inorganic fillers and compares end-of-life (EoL) performance against PE. While prior studies have largely assessed virgin PBAT or PBAT/Polylactic Acid (PLA) systems, systematic LCA of commercial-style PBAT blends with inorganic fillers and screening LCA level for comparisons of composting vs. landfill remain limited. The contributions of this study are to: (i) map gate-to-gate environmental hotspots for PBAT-blend conversion, (ii) provide a screening gate-to-grave comparison of PBAT composting vs. PE landfill using ReCiPe 2016 and IPCC GWP100 methods, and (iii) discuss theoretical implications for material substitution in the context of EoL strategies. The results indicated that producing 1 kg of PBAT blend generated a single score impact of 921 mPt with Human Health and Resource categories contributing similarly, and a GWP of 8.64 kg CO₂-eq, dominated by mixing and drying processes. EoL screening showed PBAT composting offered clear advantages over landfilling PE, yielding −53.9 mPt and 11.35 kg CO₂-eq savings, effectively offsetting production emissions. In contrast, landfilling PE resulted in 288.8 mPt and 2.2 kg CO₂-eq emissions. Sensitivity analysis further demonstrated that a 30% reduction in electricity use could decrease impacts by up to 10%, underscoring the importance of energy efficiency improvements and renewable energy adoption for sustainable PBAT development. Full article

The applications of electromagnetic (EM) field treatment on water in agriculture have garnered increasing attention as a sustainable method to enhance plant growth, water-use efficiency, and metabolic performance. A growing body of evidence suggests that exposure to EM fields can affect water molecules, possibly by influencing hydrogen bonding dynamics, the structuring of water clusters, and electrokinetic properties of the water molecules. These alterations are thought to correlate with plant physiological performance. The methodology of the study was divided into two parts. The first part focused on the preparation of electromagnetically treated water. The second part involved applying this treated water to spinach plants. The present study investigates the physiological responses of Spinacia oleracea L. to irrigation with electromagnetically treated water (EMTW), focusing on elucidating the potential mechanisms that may underlie the observed effects. EMTW was generated using a solenoid-based system operating in dual-frequency ranges (100–1000 Hz and 10–100 kHz), which has been previously shown to influence both the microbiological and electrokinetic properties of aqueous systems. To evaluate the structural and functional implications of EMTW, a combined methodological approach was employed, integrating proton nuclear magnetic resonance (¹H-NMR) spectroscopy, density functional theory (DFT) modeling of water hydrogen bonds and clusters, and comprehensive plant physiological assessments. Plants were cultivated under both controlled and field conditions to assess consistency across environmental settings. Physiological measurements demonstrated that EMTW irrigation increased photosynthetic rate by ~80%, transpiration by 49–67%, stomatal conductance by 78–129%, intercellular CO₂ concentration by 42–80%, and chlorophyll content by 9.3–9.5% compared to control samples. Additionally, phenoloc and flavonoid contents were elevated by 7.4% and 7.6%, respectively, in field-grown plants. These enhancements were statistically significant (p < 0.001 or p < 0.01) under both laboratory and field conditions, confirming the robustness of the observed effects. Full article

The negative impact of disruption events (i.e., departure of key personnel, geopolitical conflicts) on normalized economic operations is self-evident. How complex product R&D networks maintain resilience under disruptions is an unavoidable management issue. Existing research has primarily focused on the effects of inter-organizational interactions under disruption events, while paying little attention to the diversity of multi-agent interactions in complex product R&D network and the deeper logic embedded within them. Combining the attention-based view and sequential attention logic, we take the resilience of complex product R&D networks as the dependent variable to study the selection effects of multi-agent interaction modes in complex product R&D networks under disruption events. A hierarchical linear regression was conducted on 427 questionnaire samples from the high-end equipment manufacturing industry. Empirical results show that complex product R&D networks are prone to two multi-agent interaction modes under disruption events: the focal firm-dominated mode and the multi-agent co-creation mode. Compared with the latter, focal firms show a stronger preference for the former mode in disruptions. Both multi-agent interaction modes contribute to enhancing network resilience. Further research shows that under first-order disruption events (i.e., departure of key personnel), both focal firm-dominated mode and the multi-agent co-creation mode serve as effective resilience governance strategies for complex product R&D networks, with the multi-agent co-creation mode being better than the focal firm-dominated mode. Under second-order disruption events (i.e., geopolitical conflicts), only the multi-agent co-creation mode emerges as an important mechanism for resilience governance of complex product R&D networks. The findings provide a theoretical foundation for complex product R&D networks to select the optimal multi-agent interaction mode to enhance resilience and effectively respond to disruption events. Full article

Cardiovascular diseases are the leading cause of death worldwide, with arrhythmia being a prevalent and potentially fatal condition. The multi-lead electrocardiogram (ECG) is the primary tool for detecting arrhythmias. However, existing detection methods have shortcomings: they cannot dynamically integrate inter-lead correlations with multi-scale temporal changes in cardiac electrical activity. They also lack mechanisms to simultaneously focus on key leads and time segments, and thus fail to address multi-lead redundancy or capture comprehensive spatial-temporal relationships. To solve these problems, we propose a Multi-Scale Lead-Temporal Co-Attention Framework (MS-LTCAF). Our framework incorporates two key components: a Lead-Temporal Co-Attention Residual (LTCAR) module that dynamically weights the importance of leads and time segments, and a multi-scale branch structure that integrates features of cardiac electrical activity across different time periods. Together, these components enable the framework to automatically extract and integrate features within a single lead, between different leads, and across multiple time scales from ECG signals. Experimental results demonstrate that MS-LTCAF outperforms existing methods. On the PTB-XL dataset, it achieves an AUC of 0.927, approximately 1% higher than the current optimal baseline model (DNN_zhu’s 0.918). On the LUDB dataset, it ranks first in terms of AUC (0.942), accuracy (0.920), and F1-score (0.745). Furthermore, the framework can focus on key leads and time segments through the co-attention mechanism, while the multi-scale branches help capture both the details of local waveforms (such as QRS complexes) and the overall rhythm patterns (such as RR intervals). Full article

The construction of urban underground space develops very fast, and tunnel intersection construction has become a common practice, attracting significant attention due to the associated deformation responses and risk control challenges. To systematically review the research landscape and cutting-edge developments in this field, this study conducts a comprehensive analysis based on 744 publications (1994–2025) from the Web of Science Core Collection using bibliometric methods. Firstly, through visual analyses of annual publication trends, journal distributions, and keyword co-occurrences, the study reveals the evolution and research hotspots of the past three decades. Subsequently, three core dimensions are explored in depth: deformation mechanisms and patterns, deformation analysis methods for ground and existing structures, and ground control and reinforcement techniques. The review highlights the following: (1) Research focus has shifted from single construction scenarios to the complex interactions among multiple tunnels, yet the cumulative deformation effects caused by repeated soil disturbances during sequential excavation remain inadequately understood. (2) The bidirectional coupling between existing tunnels and surrounding soil has become a major research focus and challenge. Particularly in the presence of high-stiffness structures, the “free-field” assumption in the commonly used two-stage method is being questioned, necessitating the development of more refined computational theories. (3) Optimization of construction schemes under complex conditions is key to disturbance control, but current research still lacks systematic multi-objective optimization approaches. In addition, this paper analyzes the current research status and future directions to enhance the deformation perception capability and control technologies in tunnel construction influence zones, thereby further improving the safety and intelligence level of tunnel construction. Full article

Part-of-speech (POS) tagging in low-resource, morphologically rich languages (LRLs/MRLs) remains challenging due to extensive affixation, high out-of-vocabulary (OOV) rates, and pervasive polysemy. We propose MRL-POS, a unified Transformer-CRF framework that dynamically selects informative affix features and integrates them with deep contextual embeddings via a novel dual-gating co-attention mechanism. First, a Dynamic Affix Selector adaptively adjusts n-gram ranges and frequency thresholds based on word length to ensure high-precision affix segmentation. Second, the Affix–Context Co-Attention Module employs two gating functions that conditionally amplify contextual dimensions with affix cues and vice versa, enabling robust disambiguation of complex and ambiguous forms. Third, Layer-Wise Attention Pooling aggregates multi-layer XLM-RoBERTa representations, emphasizing those most relevant for morphological and syntactic tagging. Evaluations on Uyghur, Kyrgyz, and Uzbek show that MRL-POS achieves an average F₁ of 84.10%, OOV accuracy of 84.24%, and Poly-F₁ of 72.14%, outperforming strong baselines by up to 8 F₁ points. By explicitly modeling the symmetry between morphological affix cues and sentence-level context through a dual-gating co-attention mechanism, MRL-POS achieves a balanced fusion that both preserves local structure and captures global dependencies. Interpretability analyses confirm that 89.1% of the selected affixes align with linguistic expectations. This symmetric design not only enhances robustness in low-resource and agglutinative settings but also offers a general paradigm for symmetry-aware sequence labeling tasks. Full article

Graph Neural Networks (GNNs) face fundamental algorithmic challenges in real-world applications due to a combination of data heterogeneity, adversarial heterophily, and severe class imbalance. A critical research gap exists for a unified framework that can simultaneously address these issues, limiting the deployment of GNNs in high-stakes domains like financial fraud detection and social network analysis. This paper introduces HAG-CFNet, a novel framework designed to bridge this gap by integrating three key innovations: (1) a heterogeneity-aware message-passing mechanism that uses relation-specific attention to capture rich semantic information; (2) a dual-channel heterophily detection module that explicitly identifies and neutralizes adversarial camouflage through separate aggregation pathways; and (3) a domain-aware counterfactual generator that produces plausible, actionable explanations by co-optimizing feature and structural perturbations. These are supported by a synergistic imbalance correction strategy combining graph-adapted oversampling with cost-sensitive learning. Extensive testing on large-scale financial datasets validates the framework’s impact: HAG-CFNet achieves a 4.2% AUC-PR improvement over state-of-the-art methods, demonstrates superior robustness by reducing performance degradation under structural noise by over 50%, and generates counterfactual explanations with 91.8% validity while requiring minimal perturbations. These advances provide a direct pathway to building more trustworthy and effective AI systems for critical applications ranging from financial risk management to supply chain analysis and social media content moderation. Full article

Neurodevelopmental disorders represent a significant health concern, leading to a wide range of clinical, cognitive, and social impairments. Although the exact causes of these disorders remain unclear, genetic, epigenetic, and environmental factors all contribute to their emergence. Recently, the role of neuroglia in the pathophysiology of these conditions has received increasing attention. Various glial mechanisms (e.g., neuroinflammation, neurotransmitter regulation, gliosis) have been implicated in both shared and distinct features of these disorders. The identification of novel etiological factors may facilitate the development of new therapeutic modalities targeting glial dysfunction. This review provides a comprehensive overview of neuroglia and summarizes the current understanding of neurodevelopmental disorders and co-occurring disruptive behavioral disorders from a glial perspective. Furthermore, gaps in the literature are highlighted, and potential strategies for addressing these gaps and integrating findings into clinical practice are discussed. Full article

Basic magnesium sulfate cement (BMSC) has attracted increasing attention as a low-carbon alternative to traditional Portland cement. Therefore, this study investigates the feasibility of using carbonated boron mud (CBM), an industrial solid waste, as a partial substitute for magnesium oxide (MgO) in BMSC. Prior to its incorporation into the cementitious matrix, boron mud (BM) underwent rapid carbonation treatment to improve its reactivity, microstructure compatibility, and CO₂ sequestration potential. Experimental results from macroscopic and microscopic analyses confirmed the effectiveness of the carbonation process, showing that the carbonate ions carried by the CBM were successfully incorporated into the cementitious system. These carbonate ions reacted with MgO to form stable magnesium carbonate phases, effectively suppressing the formation of magnesium hydroxide (Mg(OH)₂), which typically detracts from strength and stability. Compared to BMSC specimens containing untreated BM, the CBM-modified BMSC exhibited significantly improved mechanical performance and excellent volume stability. Furthermore, the carbonation pre-treatment effectively mitigated volumetric instabilities associated with rapid MgO hydration, thereby promoting a more favorable environment for the formation of the crucial 5·1·7 phase (5Mg(OH)₂·MgSO₄·7H₂O). Overall, this research presents a promising strategy for producing CBM-BMSC, offering a sustainable approach to CO₂ utilization and enhancing the volume stability of magnesium-based cements, providing a new direction for improving the sustainability of the concrete industry and advancing the development of magnesium cements. Full article

Chitosanases are glycoside hydrolases (GHs) that catalyze the endo- or exo-type cleavage of β-1,4-glycosidic linkages in chitosan, enabling the selective production of chitooligosaccharides (COSs) with well-defined structures and diverse bioactivities. Owing to their substrate specificity and environmentally friendly catalytic action, chitosanases have garnered increasing attention as sustainable biocatalysts for COS production, with broad application potential in agriculture, food, medicine, and cosmetics. This review provides a comprehensive overview of recent advances in chitosanase research, focusing on the catalytic mechanisms and structure–function relationships that govern substrate selectivity and functional divergence across different GH families. Microbial diversity and heterologous expression systems for chitosanase production are discussed in parallel with biochemical characterization to support the rational selection of enzymes for specific biotechnological applications. Advances in protein engineering and computational approaches are highlighted as strategies to improve catalytic efficiency, substrate range, and stability. In addition, bioprocess optimization is addressed, with emphasis on fermentation using low-cost substrates and the application of immobilized enzymes and nano-biocatalyst systems for green and efficient COS production. Summarizing and discussing previous findings are essential to support future research and facilitate the development of next-generation chitosanases for sustainable industrial use. Full article

The metal-free polymeric semiconductor graphitic carbon nitride (g-C₃N₄) has emerged as a promising material for photocatalytic applications due to its responsiveness to visible light, adjustable electronic structure, and stability. This review systematically summarizes recent advances in preparation strategies, including thermal polycondensation, solvothermal synthesis, and template methods. Additionally, it discusses modification approaches such as heterojunction construction, elemental doping, defect engineering, morphology control, and cocatalyst loading. Furthermore, it explores the diverse applications of g-C₃N₄-based materials in photocatalysis, including hydrogen (H₂) evolution, carbon dioxide (CO₂) reduction, pollutant degradation, and the emerging field of piezoelectric photocatalysis. Particular attention is given to g-C₃N₄ composites that are rationally designed to enhance charge separation and light utilization. Additionally, the synergistic mechanism of photo–piezocatalysis is examined, wherein a mechanically induced piezoelectric field facilitates carrier separation and surface reactions. Despite significant advancements, challenges persist, including limited visible-light absorption, scalability issues, and uncertainties in the multi-field coupling mechanisms. The aim of this review is to provide guidelines for future research that may lead to the development of high-performance and energy-efficient catalytic systems in the context of environmental and energy applications. Full article

Background and Objectives: Endometrial adenocarcinoma is among the most prevalent malignancies of the female reproductive system, and therapeutic options remain limited, particularly in advanced stages. In recent years, natural agents, especially flavonoids, have gained considerable interest for their capacity to enhance the effectiveness of chemotherapeutic drugs and modulate tumor-related molecular mechanisms. Hesperidin, a citrus-derived flavonoid, is recognized for its antioxidant and anti-inflammatory effects, while Gemcitabine, a nucleoside analog, is widely used in cancer treatment. Investigating their combined effects on endometrial carcinoma cells could yield novel insights into multimodal therapeutic development. This current study aimed to assess the impact of Hesperidin (Hes) and Gemcitabine (Gem) on ISHIKAWA cells, a human endometrial adenocarcinoma model, with particular attention to pathways associated with hypoxia, angiogenesis, apoptosis, and oxidative stress. Materials and Methods: ISHIKAWA cells were treated with varying concentrations of Hes (50–200 µM) and Gem (10–50 nM), either individually or together, for 24 and 48 h. Cell viability was determined using the MTT assay, while apoptosis was measured by Caspase-3/7 activity and NucBlue nuclear staining. Intracellular reactive oxygen species (ROS) generation was quantified via DCFH-DA fluorescence. Expression levels of HIF-1α, VEGF, Bax, Bcl-2, and Caspase-3 were examined by RT-qPCR. Synergistic interactions were analyzed with the Chou–Talalay combination index. Biological enrichment was further explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Results: Both Hes and Gem significantly decreased ISHIKAWA cell viability in a concentration- and time-dependent manner (p < 0.001). The combined treatment induced stronger apoptotic effects, as reflected by increased Caspase-3/7 activity and nuclear morphological changes. RT-qPCR demonstrated upregulation of Bax and Caspase-3, together with downregulation of Bcl-2, HIF-1α, and VEGF. While Hes reduced intracellular ROS, Gem elevated it; their combination produced a balanced oxidative response. All dose combinations displayed strong synergism (CI < 1). GO and KEGG enrichment confirmed the involvement of apoptosis-, angiogenesis-, and hypoxia-related pathways. Conclusions: Co-treatment with Hes and Gem exhibits synergistic anticancer activity in endometrial cancer cells by promoting apoptosis, suppressing angiogenesis- and hypoxia-related gene expression, and modulating oxidative stress. This combined therapeutic approach highlights its potential as a promising adjuvant option, warranting further evaluation in in vivo and translational studies. Full article

The extraction of lithium from clay-type lithium ores has attracted significant attention, but the leaching behavior of associated elements, such as Rb, K, and Sr, remains less explored. This study quantitatively investigated the leaching behaviors and mechanisms of Li, Rb, K, Sr, and Mg in clay-type lithium ore through water leaching and roasting–water leaching processes. The results show that during direct water leaching, the leaching efficiency of K ranged between 10% and 13%, while Li and Sr exhibited lower extraction rates, requiring prolonged high-temperature leaching. Rb dissolution was minimal, and the leaching efficiency of Mg was significantly affected by temperature. In contrast, roasting–water leaching significantly enhanced the leaching efficiency, achieving extraction rates of 90.65% for Li, 92.91% for Rb, 75.85% for K, and 36.99% for Sr. However, Mg leaching was suppressed to below 1%. Roasting disrupted the original silicate and carbonate lattices, generating new phases that altered the ore’s microstructure into aggregated dense phases and needle-like porous phases upon water leaching, thereby facilitating the release of Li, Rb, K, and Sr. A research finding was that the new phase generated by magnesium inhibited its leaching, which indirectly enhanced subsequent Li, Rb, K, and Sr extraction and separation. These findings provide a quantitative foundation for optimizing multi-element co-extraction from clay-type lithium ores. Full article