Search Results (5,090)

Knowledge Graph Reasoning (KGR) aims to deduce missing or novel knowledge by learning structured information and semantic relationships within Knowledge Graphs (KGs). Despite significant advances achieved by deep neural networks in recent years, existing models typically extract non-linear representations from explicit features in a relatively simplistic manner and fail to fully exploit semantic heterogeneity of relation types and entity co-occurrence frequencies. Consequently, these models struggle to capture critical predictive cues embedded in various entities and relations. To address these limitations, this paper proposes a relation aware spectral decoupling attention network for KGR (RASD). First, a spectral decoupling attention network module projects joint embeddings of entities and relations into the frequency domain, extracting features across different frequency bands and adaptively allocating attention at the global level to model frequency specific information. Next, a relation-aware learning module employs relation aware filters and an augmentation mechanism to preserve distinct relational properties and suppress redundant features, thereby enhancing representation of heterogeneous relations. Experimental results demonstrate that RASD achieves significant and consistent improvements over multiple leading baseline models on link prediction tasks across five public benchmark datasets. Full article

Clouds are closely related to precipitation, as their type, microphysical characteristics, and dynamic properties determine the intensity, duration, and form of rainfall. While geostationary satellites offer continuous cloud-top observations, they cannot capture the full three-dimensional structure of clouds, limiting the accuracy of precipitation forecasting based on geostationary satellite data. However, cloud–precipitation relationships contain valuable physical information that can be leveraged to improve forecasting performance. To further enhance the precision of satellite precipitation forecasting, this study proposes a multi-channel satellite precipitation forecasting method that integrates cloud classification products. The method combines precipitation-prior information from Himawari-8 satellite cloud classification products with multi-channel satellite observations to generate precipitation forecasts for the next four hours. This approach further exploits the potential of satellite observations in precipitation forecasting. Experimental results show that integrating cloud classification products improves the Critical Success Index by 8.0%, improves the Correlation Coefficient by 5.8%, and reduces the Mean Squared Error by 3.0%, but increases the MAE by 4.5%. It is proven that this method can effectively improve the accuracy of multi-channel satellite precipitation forecasting. Full article

The nanoporous structure of coal is crucial for the occurrence and development of coalbed methane (CBM). This study, leveraging the combined characterization of atomic force microscopy (AFM) and Gwyddion software, investigated six anthracite samples with varying degrees of metamorphism (R_o = 2.11–3.36%). It revealed the intrinsic relationships between their nanoporous structures, surface morphologies, fractal characteristics, and coalification processes. The research found that as R_o increases, the surface relief of coal decreases significantly, with pore structures evolving from being macropore-dominated to micropore-enriched, and the surface tending towards smoothness. Surface roughness parameters (Ra, Rq) exhibit a negative correlation with R_o. Quantitative data indicate that area porosity, pore count, and shape factor positively correlate with metamorphic grade, while mean pore diameter negatively correlates with it. The fractal dimensions calculated using the variance partition method, cube-counting method, triangular prism measurement method, and power spectrum method all show nonlinear correlations with R_o, moisture (M_ad), ash content (A_ad), and volatile matter (V_daf). Among these, the fractal dimension obtained by the triangular prism measurement method has the highest correlation with R_o, A_ad, and V_daf, while the variance partition method shows the highest correlation with M_ad. This study clarifies the regulatory mechanisms of coalification on the evolution of nanoporous structures and surface properties, providing a crucial theoretical foundation for the precise evaluation and efficient exploitation strategies of CBM reservoirs. Full article

The GLABROUS1 Enhancer Binding Protein (GeBP) gene family plays a crucial role in plant growth, development, and stress responses. In this study, 28 GeBP genes were identified in Brassica oleracea using HMMER and validated through multiple conserved domain databases. A phylogenetic tree was constructed based on the GeBP protein sequences from B. oleracea, Arabidopsis thaliana, Brassica rapa, and Brassica napus, dividing them into four evolutionary clades (A–D), which revealed a close evolutionary relationship within the genus Brassica. Conserved motif and gene structure analyses showed clade-specific features, while physicochemical property analysis indicated that most BoGeBP proteins are hydrophilic, nuclear-localized, and structurally diverse. Gene duplication and chromosomal localization analyses suggested that both segmental and tandem duplication events have contributed to the expansion of this gene family. Promoter cis-element analysis revealed a dominance of light-responsive and hormone-responsive elements, implying potential roles in photomorphogenesis and stress signaling pathways. Notably, the protein encoded by BolC01g019630.2J possesses both a transmembrane domain and characteristics of the Major Facilitator Superfamily (MFS) transporter family, and it is predicted to localize to the plasma membrane. This suggests that it may act as a molecular bridge between environmental signal perception and transcriptional regulation, potentially representing a novel signaling mechanism within the GeBP family. This unique feature implies its involvement in transmembrane signal perception and downstream transcriptional regulation under environmental stimuli, providing valuable insights for further investigation of its role in stress responses and metabolic regulation. Overall, this study provides a theoretical foundation for understanding the evolutionary patterns and functional diversity of the GeBP gene family in B. oleracea and lays a basis for future functional validation and breeding applications. Full article

Optical fiber composite insulators are essential for photoelectric current measurement, yet insulation failure at embedded optical fiber interfaces remains a major challenge to long-term stability. This study proposes a strategy to replace conventional silicone rubber with cycloaliphatic-like epoxy resin (CEP) as the shed-sheathing material. Three optical fibers with distinct outer coatings, ethylene-tetrafluoroethylene copolymer (ETFE), thermoplastic polyester elastomer (TPEE), and epoxy acrylate resin (EA), were evaluated for their interfacial compatibility with CEP. ETFE, with low surface energy and weak polarity, exhibited poor wettability with CEP, resulting in an interfacial tensile strength of 0 MPa, pronounced dye penetration, and rapid electrical tree propagation. Its average interfacial breakdown voltage was only 8 kV, and the interfacial leakage current reached 35 μA after hygrothermal aging. In contrast, TPEE exhibited high surface energy and strong polarity, enabling strong bonding with CEP, yielding an average interfacial tensile strength of approximately 46 MPa. Such a strong interface effectively suppressed electrical tree growth, increased the average interfacial breakdown voltage to 27 kV, and maintained the interfacial leakage current below 5 μA even after hygrothermal aging. EA exhibited moderate interfacial performance. Mechanism analysis revealed that polar ester and ether groups in TPEE enhanced interfacial electrostatic interactions, restricted the mobility of CEP molecular chain segments, and increased charge traps. These synergistic effects suppressed interfacial charge transport and improved insulation strength. This work offers valuable insight into structure–property relationships at fiber–resin interfaces and provides a useful reference for the design of composite insulation materials. Full article

Understanding the intrinsic relationship between microscopic structures and macroscopic mechanical properties of rock under freeze–thaw (F-T) conditions is essential for ensuring the safety and stability of geotechnical engineering in cold regions. In this study, a series of F-T cycle tests, nuclear magnetic resonance (NMR) measurements, and uniaxial compression tests were conducted on sandstone samples. The mechanisms by which F-T cycles influence pore structure and mechanical behavior were analyzed, revealing their internal correlation. A degradation model for peak strength was developed using mesopore porosity as the key influencing parameter. The results showed that with increasing F-T cycles, the total porosity and mesopore and macropore porosities all exhibited increasing trends, whereas the micropore and different fractal dimensions decreased. The compaction stage in the stress–strain curves became increasingly prominent with more F-T cycles. Meanwhile, the peak strength and secant modulus decreased, while the peak strain increased. When the frost heave pressure induced by water–ice phase transitions exceeded the ultimate bearing capacity of pore walls, smaller pores progressively evolved into larger ones, leading to an increase in the mesopores and macropores. Notably, mesopores and macropores demonstrated significant fractal characteristics. The transformation in pore size disrupted the power-law distribution of pore radii and reduced fractal dimensions. A strong correlation was observed between peak strength and both the mesopore and mesopore fractal dimensions. The increase in mesopores and macropores enhanced the compaction stage of the stress–strain curve. Moreover, the expansion and interconnection of mesopores under loading conditions degraded the deformation resistance and load-bearing capacity, thereby reducing both the secant modulus and peak strength. The degradation model for peak strength, developed based on changes in mesopore ratio, proved effective for evaluating the mechanical strength when subjected to different numbers of F-T cycles. Full article

Understanding how main plant functional strategies scale from species to communities is critical for guiding restoration in tropical disturbed areas by unsustainable livestock grazing; yet, the patterns and drivers of functional trait space along successional trajectories remain poorly understood. Here, we investigated functional trait space using principal component analyses (PCAs) based on eight traits related to leaf, stem, and seed morphology across 226 tree species and 33 forest communities along a chronosequence of natural regeneration following cattle ranching abandonment in deforested landscapes of the Colombian Amazon. We identified three species-level functional axes—namely, the ‘Structural–Reproductive Allocation Axis’, the ‘Mechanical Support and Tissue Investment Axis’, and the ‘Leaf Economics Axis’—and two community-level axes: the ‘Colonization–Longevity Axis’ and the ‘Persistence–Acquisition Axis’. These axes aligned with the life-history strategies of short-lived pioneers, long-lived pioneers, and old-growth species, and reflected their relationships with key environmental drivers. Community-level functional composition reflected species-level patterns, but was also shaped by soil properties, microclimate, and tree species richness. Forest age and precipitation promoted conservative strategies, while declining soil fertility suggested a decoupling between above- and belowground recovery. Functional richness and divergence were highest in mid-successional forests dominated by long-lived pioneers. Our findings highlight the role of environmental and successional filters in shaping functional trait space and emphasize the value of functionally diverse communities. Particularly, our results indicate that long-lived pioneers (LLP) such as Astrocaryum chambira Burret and Pouteria campanulata Baehni, with traits like large height, intermediate wood density, and larger seed size, represent ideal candidates for early enrichment strategies due to their facilitation roles in succession supporting restoration efforts in regenerating Amazonian forests. Full article

Biodegradable polyesters have gained attention due to their sustainability benefits, considering the escalating environmental challenges posed by synthetic polymers. Advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), are expected to significantly accelerate research in polymer science. This review article explores “bio” polymer informatics by harnessing insights from the AI techniques used to predict structure–property relationships and to optimize the synthesis of bioplastics. This review also discusses PolyID, a machine learning-based tool that employs message-passing graph neural networks to provide a framework capable of accelerating the discovery of bioplastics. An extensive literature review is conducted on explainable AI (XAI) and generative AI techniques, as well as on benchmarking data repositories in polymer science. The current state-of-the art in ML methods for ring-opening polymerizations and the synthesizability of biodegradable polyesters is also presented. This review offers an in-depth insight and comprehensive knowledge of current AI-based models for polymerizations, molecular descriptors, structure–property relationships, predictive modeling, and open-source benchmarked datasets for sustainable polymers. This study serves as a reference and provides critical insights into the capabilities of AI for the accelerated design and discovery of green polymers aimed at achieving a sustainable future. Full article

Understanding three-dimensional (3D) auxetic structural responses to impact loading remains challenging due to large deformations involving failure evolution and the interaction between geometric and material instabilities. In this study, the Generalized Interpolation Material Point Method (GIMP) is used to investigate representative auxetic structures, with the focus on the negative Poisson’s ratio effect on the responses to impact loading. Using a cubic lattice model for 3D re-entrant structures, simulations with different impact speeds are performed to evaluate corresponding energy absorption characteristics and deformation behaviors. Three constitutive models for lattice materials (linear elasticity, elastoplasticity, and damage) are employed to analyze the corresponding variations in auxetic structural performance. The computational results indicate that distinct deformation mechanisms are mainly associated with microstructural geometry, while the constitutive modeling effect is not significant. The findings demonstrate the importance of the process–structure–property relationship in the impact performance of protective structures. Verification against theoretical predictions of the Poisson’s ratio–strain relationship confirms the potential of GIMP in effectively engineering auxetic structures for general applications. Full article

The search for a simple, scalable, and eco-friendly method for synthesizing micro-sized photocatalysts is an urgent task. Plasma technologies are highly effective and have wide possibilities for targeted synthesis of novel materials. The mass-average temperature of plasma treatment is higher than the stability temperature of anatase and brookite, the most photoactive polymorphs of titanium dioxide. In this work, by optimizing the plasma treatment conditions and selecting source materials, a method for synthesizing micro-sized photocatalyst based on heterocomposite TiO₂/ZnO particles with high anatase content is proposed. The synthesis method involves treating a powder mixture of titanium and zinc by low-temperature argon plasma under atmospheric conditions. The relationship between the structural-phase composition, morphology, and photocatalytic properties of the microparticles was investigated. A model for the synthesis of composite microparticles containing anatase, rutile, and heterostructural contact with zinc oxide is proposed. The photocatalytic degradation of methylene blue and metronidazole was studied to evaluate both sensitized and true photocatalytic processes. The metronidazole degradation confirmed the intrinsic photocatalytic activity of the synthesized composites. Additionally, the features of photocatalysis under UV and solar irradiation were studied, and a photocatalysis mechanism is proposed. The synthesized micro-sized heterocomposite photocatalyst based on TiO₂/ZnO contained anatase (36%), rutile (60), and brookite (4%) and showed a photocatalytic activity during the methylene blue degradation process under UV irradiation (high-pressure mercury lamp, 250 W): 99% in 30 min. Full article

Structural composite materials are being used more than ever in aeronautics, automotive and naval, or in renewable energies fields. To reconcile the contradictory needs for higher performances and lower costs, it is crucial to ensure the real-time monitoring of as many features as possible during the manufacturing process to feed a digital twin able to minimise post-fabrication controls. For thermoset composites, little information is available regarding the evolution of the polymer’s core properties during infusion and curing. The local kinetics of reticulation, in several areas of interest across the thickness of a structural composite part, are valuable data to record and analyse to guarantee the materials’ performances. This paper investigates a novel strategy curing in the core of an epoxy matrix with crosslinkable quantum-resistive nanocomposite sensors (xQRS). First, the electrical behaviour of the sensor during isothermal curing is considered. Then, the influence of the dynamic percolation and the epoxy crosslinking reaction on the resistance is examined. The evidence of a relationship between the curing state of the resin and the evolution of the xQRS resistance makes its use in the process monitoring of thermoset composites promising, especially in cases involving large and thick parts. Full article

Peat soil is a significant global carbon storage pool, accounting for one-third of the global soil carbon pool. Its greenhouse gas emissions have a significant impact on climate change. Seasonal freeze–thaw cycles are common natural phenomena in high-latitude and high-altitude regions. They significantly affect the mineralization of soil organic carbon and greenhouse gas emissions by altering the physical structure, moisture conditions, and microbial communities of the soil. In this study, through the construction of an indoor simulation experiment of the typical freeze–thaw cycle models in spring and autumn in the Greater Xing‘an Range region of China and the Jinchuan peatland of Jilin Longwan National Nature Reserve, the physicochemical properties, greenhouse gas emission fluxes, microbial community structure characteristics, and key metabolic pathways of peat soils in permafrost and seasonally frozen ground areas were determined. The characteristics of greenhouse gas emissions and their influencing mechanisms for peat soil in northern regions under different freeze–thaw conditions were explored. The research found that the freeze–thaw cycle significantly changed the chemical properties of peat soil and significantly affected the emission rates of CO₂, CH₄, and N₂O. It also clarified the interaction relationship between soil’s physicochemical properties (such as dissolved organic carbon (DOC), dissolved organic nitrogen (DON), ammonium nitrogen (NH₄⁺), soil organic carbon (SOC), etc.) and the structure and metabolic function of microbial communities. It is of great significance for accurately assessing the role of peatlands in the global carbon cycle and formulating effective ecological protection and management strategies. Full article

This paper presents the effect of specimens’ shape and size on the modulus of elasticity and compressive strength of high strength concrete. The European Standard EN 12390-13 allows not only for different procedures but also for different shapes and sizes of test specimens. However, it does not provide a relationship between specimen size and shape and elastic modulus. The aim of the research was to determine the influence of the shape and size of specimens on the measured values of the secant and dynamic modulus of elasticity and compressive strength. The analysis was carried out on cube and cylindrical specimens of various sizes and slenderness. Concrete with the mean strength of f_cm,cyl = 101.9 MPa was used for the tests. The research used 64 specimens of various sizes and shapes. Compared to the results obtained for the basic cylindrical specimen (150 × 300), the differences reached 19% for E_d and 14% for E_c,s. The results indicate that in the case of the tested composite the key factor influencing the value of the elastic modulus and compressive strength of specimens is its individual structure that determines its density, while the scale and shape of the specimens have less effect on the mechanical properties. Full article

The toxicity of lead in conventional perovskites and their inherent chemical instability impede the commercialization of perovskite-based optoelectronics. Therefore, it is vital to develop chemically stable and environmentally friendly Pb-free alternatives. Recently, zero-dimensional (0D) all-inorganic Cs₂ZnCl₄ doped with Sn(II) has emerged as a promising candidate, exhibiting superior chemical robustness, minimal biotoxicity, and exceptional optoelectronic properties. In this work, pressure effects on structure and optical properties in Sn(II)-doped all-inorganic zero-dimensional halide perovskite are investigated both experimentally and theoretically. The structure–property relationship of Sn(II)-doped Cs₂ZnCl₄ is studied using high-pressure techniques. Piezochromism, accompanied by a remarkable change in emission color from orange/red and green to orange/yellow, was obtained from 1 atm to 22.5 GPa. Angle dispersive synchrotron X-ray diffraction (ADXRD) patterns and Raman spectra manifest that the material underwent an isostructural phase transition followed by amorphization with increasing pressure. The piezochromism and band gap engineering originate from the pressure-induced lattice compression and isostructural phase transition. This work advances STE emission studies and provides a robust strategy to boost emission efficiency and to construct multifunctional materials with piezochromism in environmentally friendly perovskites, thus facilitating diverse future applications. Full article

The utilisation of empirical correlations for the estimation of thermodynamic functions is a valuable approach for reducing experimental effort and for validating existing data. Established correlations and group contribution methods provide reliable heat capacity estimates for simple organic compounds. The present work assesses the extent of deviations introduced by employing conventional heat capacity correlations for diols. For this purpose, heat capacity differences between the solid, liquid and gas phases are evaluated based on experimentally determined vapour pressures, enthalpies of vaporisation, heat capacities in the solid and liquid phases, and quantum chemical calculations. It is demonstrated that the structural characteristics of diols result in a significant overestimation of heat capacities when conventional empirical methods are applied. Deviations in the range of 30–50 J·K⁻¹·mol⁻¹ were observed when compared to consistent experimental data. As part of the evaluation, new group contribution parameters were developed for calculating heat capacities in the solid and liquid phases. Based on these improved data, inconsistencies in literature values for enthalpies of vaporisation (on the order of 10–15 kJ mol⁻¹) could be resolved. Furthermore, a new correlation was derived that allows for the reliable prediction of enthalpies of vaporisation for α,ω-alkanediols from pentanediol to decanediol. The resulting data provide significant advantages for the design of technical processes involving diols as renewable sources and for the accurate modelling of their phase behaviour. Full article