Search Results (45,551)

Meta-path-based heterogeneous graph neural networks have received widespread attention for better mining the similarities between heterogeneous nodes and for discovering new recommendation rules. Most existing models depend solely on node IDs for learning node embeddings, failing to leverage attribute information fully and to clarify the reasons behind a user’s interest in specific items. A heterogeneous graph neural network for recommendation named MIMA (multi-feature interaction meta-path aggregation) is proposed to address these issues. Firstly, heterogeneous graphs consisting of user nodes, item nodes, and their feature nodes are constructed, and the meta-path containing users, items, and their attribute information is used to capture the correlations among different types of nodes. Secondly, MIMA integrates attention-based feature interaction and meta-path information aggregation to uncover structural and semantic information. Then, the constructed meta-path information is subjected to neighborhood aggregation through graph convolution to acquire the correlations between different types of nodes and to further facilitate high-order feature fusion. Furthermore, user and item embedding vector representations are obtained through multiple iterations. Finally, the effectiveness and interpretability of the proposed approach are validated on three publicly available datasets in terms of NDCG, precision, and recall and are compared to all baselines. Full article

Background/Objectives: The increase in digital tools in early childhood education highlights the need for evidence-based assessments that support cognitive development and align with educational requirements and technological advances. This study contributes to the evaluation of the Bilingual English Language Learner Assessment (BELLA), designed to enhance early learning through curriculum-aligned tasks in preschool-aged children. Methods: Data were collected from 17 schools, including 506 preschool children, using a mixed-model approach to assess BELLA’s capacity to appraise early numeracy, literacy, science, and social/emotional development. Analyses included a three-way ANOVA to examine the effects of sex, age, and sub-domain on pass rates and mixed-effects models to evaluate interactions between age and domain. Results: The results indicated a significant effect of age on performance across all domains, with older children demonstrating higher pass rates (p < 0.0001). No significant gender bias was detected. The interaction between age and domain was also significant (p < 0.0001), suggesting domain-specific age-related performance trends, which aligns with internal validity requirements. Conclusion: These findings position BELLA within the growing body of literature on digital media use in early childhood assessment and education, highlighting its potential as a curriculum-compliant digital assessment tool that evaluates and supports cognitive development without a gender bias. This study contributes to the field by providing empirical evidence of BELLA’s effectiveness and suggesting future research directions, including the exploration of its bilingual (and potentially multilingual) applications and external validation against existing evidence-based assessments. Full article

The interaction between oral bacteria and dental implant surfaces is a critical factor in the success and longevity of dental implants. With advancements in additive manufacturing technologies, selective laser melting (SLM) has emerged as a prominent method for producing titanium implants with highly controlled microstructures and porosities. These 3D printed titanium surfaces offer significant benefits, such as enhanced osseointegration and improved mechanical properties. However, the same surface features that promote bone cell attachment and proliferation may also provide favorable conditions for bacterial adhesion and biofilm formation. Understanding the dynamics of these interactions is essential for developing implant surfaces that can effectively resist bacterial colonization while promoting tissue integration. This narrative review explores the complex interplay between oral bacteria and SLM-produced titanium porous surfaces, examining current research findings and potential strategies for optimizing implant design to mitigate the risks of infection and ensure successful clinical outcomes. Full article

This study delves into the transformative effects of supercritical carbon dioxide (scCO₂) cannabis extracts and prebiotic substances (dextran, inulin, trehalose) on gut bacteria, coupled with a focus on neuroprotection. Extracts derived from the Białobrzeska variety of Cannabis sativa, utilising supercritical fluid extraction (SFE), resulted in notable cannabinoid concentrations (cannabidiol (CBD): 6.675 ± 0.166; tetrahydrocannabinol (THC): 0.180 ± 0.006; cannabigerol (CBG): 0.434 ± 0.014; cannabichromene (CBC): 0.490 ± 0.017; cannabinol (CBN): 1.696 ± 0.047 mg/gD). The assessment encompassed antioxidant activity via four in vitro assays and neuroprotective effects against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). The extract boasting the highest cannabinoid content exhibited remarkable antioxidant potential and significant inhibitory activity against both enzymes. Further investigation into prebiotic deliveries revealed their proficiency in fostering the growth of beneficial gut bacteria while maintaining antioxidant and neuroprotective functionalities. This study sheds light on the active compounds present in the Białobrzeska variety, showcasing their therapeutic potential within prebiotic systems. Notably, the antioxidant, neuroprotective, and prebiotic properties observed underscore the promising therapeutic applications of these extracts. The results offer valuable insights for potential interventions in antioxidant, neuroprotective, and prebiotic domains. In addition, subsequent analyses of cannabinoid concentrations post-cultivation revealed nuanced changes, emphasising the need for further exploration into the dynamic interactions between cannabinoids and the gut microbiota. Full article

Affective communication, encompassing verbal and non-verbal cues, is crucial for understanding human interactions. This study introduces a novel framework for enhancing emotional understanding by fusing speech emotion recognition (SER) and sentiment analysis (SA). We leverage diverse features and both classical and deep learning models, including Gaussian naive Bayes (GNB), support vector machines (SVMs), random forests (RFs), multilayer perceptron (MLP), and a 1D convolutional neural network (1D-CNN), to accurately discern and categorize emotions in speech. We further extract text sentiment from speech-to-text conversion, analyzing it using pre-trained models like bidirectional encoder representations from transformers (BERT), generative pre-trained transformer 2 (GPT-2), and logistic regression (LR). To improve individual model performance for both SER and SA, we employ an extended dynamic Bayesian mixture model (DBMM) ensemble classifier. Our most significant contribution is the development of a novel two-layered DBMM (2L-DBMM) for multimodal fusion. This model effectively integrates speech emotion and text sentiment, enabling the classification of more nuanced, second-level emotional states. Evaluating our framework on the EmoUERJ (Portuguese) and ESD (English) datasets, the extended DBMM achieves accuracy rates of 96% and 98% for SER, 85% and 95% for SA, and 96% and 98% for combined emotion classification using the 2L-DBMM, respectively. Our findings demonstrate the superior performance of the extended DBMM for individual modalities compared to individual classifiers and the 2L-DBMM for merging different modalities, highlighting the value of ensemble methods and multimodal fusion in affective communication analysis. The results underscore the potential of our approach in enhancing emotional understanding with broad applications in fields like mental health assessment, human–robot interaction, and cross-cultural communication. Full article

The steady low-Reynolds-number rotation of a chain of coaxial soft spheres (each with an impermeable hard core covered by a permeable porous layer) about the axis in a viscous fluid is analyzed. The particles may be unequally spaced, and may differ in the permeability and inner and outer radii of the porous surface layer as well as angular velocity. By using a method of boundary collocation, the Stokes and Brinkman equations for the external fluid flow and flow within the surface layers, respectively, are solved semi-analytically. The particle interaction effect increases as the relative gap thickness between adjacent particles or their permeability decreases, which can be significant as the gap thickness approaches zero. A particle’s hydrodynamic torque is reduced (its rotation is enhanced) when other particles rotate in the same direction at equivalent or greater angular velocities, but increases (its rotation is hindered) when other particles rotate in the opposite direction at arbitrary angular velocities. For particles with different radii or permeabilities, the particle interaction has a greater effect on smaller or more permeable particles than on larger or less permeable particles. For the rotation of three particles, the presence of the third particle can significantly affect the hydrodynamic torques acting on the other two particles. For the rotation of numerous particles, shielding effects between particles can be substantial. When the permeability of porous layers is low, relative fluid motion is barely felt by the hard cores of the soft particles. The insights gained from this analysis on the effects of interactions among rotating soft particles may be of great importance in many physicochemical applications of colloidal suspensions. Full article

Electromagnetic scattering is a routine tool for rapid, non-contact characterization of particle media. In previous work, the interaction targets of scattering intensity, scattering efficiency, and extinction efficiency of Bessel pincer light-sheet beams were all aimed at dielectric spheres. However, most particles in nature are charged. Considering the boundary condition on a charged sphere, the beam shape coefficients (BSCs) (pmn,qmn) of the charged spherical particle illuminated by a Bessel pincer light-sheet beam are obtained. The extinction, scattering, and absorption efficiencies are derived under the generalized Lorenz–Mie theory (GLMT) framework. This study reveals the significant differences in scattering characteristics of Bessel pincer light-sheet beams on a charged particle compared to traditional beams. The simulations show a few apparent differences in the far-field scattering intensity and efficiencies between charged and natural spheres under the influence of dimensionless size parameters. As dimensionless parameters increase, the difference between the charged and neutral spheres decreases. The effects of refractive index and beam parameters on scattering, extinction, and absorption coefficients are different but tend to converge with increasing dimensionless parameters. When applied to charged spheres with different refractive indices, the scattering, extinction, and absorption efficiencies of Bessel pincer light-sheet beams change with variations in surface charge. However, once the surface charge reaches saturation, these efficiencies become stable. This study is significant for understanding optical manipulation and super-resolution imaging in single-molecule microbiology. Full article

The implementation of corporate social responsibility (CSR) in conjunction with proficient investor relations management (IRM) can enhance the reputation and appeal of enterprises, thereby fostering the sustainable development of enterprises. This paper examines the correlation between CSR and IRM by exploring the potential misinterpretation of socially responsible actions by listed companies as “hypocrisy”. We use the fixed effect model, moderating effect model and instrumental variable method to examine the correlation between CSR and IRM. The findings indicate that actively fulfilling corporate social responsibility can enhance interaction and communication between listed companies and investors in the capital market, thereby mitigating the risk of being perceived as “hypocrisy”. This positive effect is particularly pronounced when companies are experiencing poor operational performance. These conclusions remain robust even after conducting various tests to address endogeneity concerns. In terms of the underlying mechanisms, corporate social responsibility primarily enhances investor relations management through strengthening network communication and on-site interactions. Moreover, enterprises are more inclined to proactively interact with investors in the capital market when companies face severe financial difficulties, stringent financing constraints, or poor quality of information disclosure. Additionally, our study extends its analysis to elucidate how corporate social responsibility can mitigate the risk of stock price crashes from the perspective of investor relations management. Full article

The present research explores water-lean amine-based solvents to enhance carbon capture and provide sustainable solutions for CO₂ emissions challenges. A computational approach is employed to evaluate the co-solvent’s impact on CO₂ capture in MDEA-based systems. The performance of the following systems is examined: MDEA-NMP, MDEA-MAE-NMP, MDEA-MeOH, MDEA-MAE-MeOH, MDEA-EG, MDEA-MAE-EG, and MDEA-MAE with varying water concentrations. The Radial Distribution Function (RDF) analysis revealed significant interactions between amine groups, CO₂, and water molecules in each system. The results indicate that the MDEA-NMP (40% H₂O) and MDEA-EG (40% H₂O) systems had strong interactions, indicating their potential for CO₂ capture. However, adding MAE decreased interaction intensities, indicating a less favorable performance. Complementing the RDF findings, the Mean Square Displacement (MSD) analysis quantified CO₂ diffusivity across temperatures (313 K, 323 K, and 333 K). MDEA-NMP (40% H₂O) demonstrated the highest diffusivity, indicating superior CO₂ mobility and capture efficiency. MDEA-MeOH (40% H₂O) also showed moderate diffusivity, further supporting its effectiveness. However, solvent systems incorporating MAE consistently displayed lower diffusivity, reinforcing the observation from the RDF analysis. The temperature effect on the diffusivity of selected blends does not follow the regular pattern in a co-solvent-based system, whereas in an aqueous system, it increases with temperature. These molecular dynamic simulations highlight the critical role of solvent composition in optimizing CO₂ capture efficiency. Applying these insights can improve solvent formulations, enhance effectiveness, and reduce costs. Full article

In this work, the conformational behaviors of ring polyelectrolyte in tetravalent salt solutions are discussed in detail through molecular dynamics simulation. For simplification, here we have neglected the effect of the twisting interaction, although it has been well known that both bending and twisting interactions play a deterministic in the steric conformation of a semiflexible ring polymer. The salt concentration C_S and the bending energy b take a decisive role in the conformation of the ring polyelectrolyte (PE). Throughout our calculations, the b varies from b = 0 (freely joint chain) to b = 120. The salt concentration C_S changes in the range of 3.56 × 10⁻⁴ M ≤ C_S ≤ 2.49 × 10⁻¹ M. Upon the addition of salt, ring PE contracts at first, subsequently re-expands. More abundant conformations are observed for a semiflexible ring PE. For b = 10, the conformation of semiflexible ring PE shifts from the loop to two-racquet-head spindle, then it condenses into toroid, finally arranges into coil with the increase of C_S. As b increases further, four phase transitions are observed. The latter two phase transitions are different. The semiflexible ring PE experiences transformation from toroid to two racquet head spindle, finally to loop in the latter two phase transitions. Its conformation is determined by the competition among the bending energy, cation-bridge, and entropy. Combined, our findings indicate that the conformations of semiflexible ring PE can be controlled by changing the salt concentration and chain stiffness. Full article

The root microbiota plays a crucial role in assisting the plant host in combating various biotic and abiotic stresses, notably drought, which poses a significant threat to global food security. Despite extensive efforts to understand the shifts in rhizosphere and endosphere bacteriomes, there remains a gap in comprehending how drought stress influences the co-occurring network patterns within these compartments and their ecological functional potentials. To address this gap, a pot experiment was conducted with two treatments: continuous flooding as a control and drought treatment. Bulk soil, rhizosphere, and endosphere samples were collected and subjected to high-throughput sequencing and bioinformatics analysis. The results revealed that drought stress significantly reduced the rice biomass but increased the Shannon diversity index in both the rhizosphere and endosphere bacterial communities with no observable effect on richness across compartments. Additionally, drought treatment markedly altered the community structure and bacterial assemblages in these compartments, resulting in the specific enrichment of Actinobacteriota, Gemmatimonadetes, and Patescibacteria, while Bacteroidetes and Firmicutes were depleted in the rhizosphere and endosphere. Furthermore, drought heightened the complexity of the co-occurring networks and the proportions of positive links across all sampling compartments; this effect was accompanied by an increase in the number of connectors in the bulk soil and rhizosphere, as well as module hubs in the rhizosphere. Functional potential prediction indicated that drought stress significantly altered multiple potential ecological functions across all sampling compartments, particularly enriching functions related to the oxidation of sulfur, manganese, and hydrogen in the bulk soil, while functions associated with iron oxidation were significantly depleted in the rhizosphere. Overall, our results demonstrate that under drought stress, rice may specifically enrich certain bacterial taxa and enhance their positive interactions within its root system to improve adaptation. Full article

Albendazole (ABZ) is a highly effective yet poorly water-soluble antiparasitic drug known to form salts (ABZ-FMA, ABZ-DTA, and ABZ-HCl) with fumaric acid (FMA), D-tartaric acid (DTA), and hydrochloric acid (HCl). This research utilized a range of analytical techniques, including Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance hydrogen spectroscopy (¹H NMR), powder X-ray diffraction (PXRD), dynamic vapor sorption (DVS), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM), to validate and characterize the solid-state properties of these drug salts. This study also assessed the solubility and intrinsic dissolution rate (IDR) of these salts under different pH conditions compared to the active pharmaceutical ingredient (API) and conducted stability studies. Moreover, the in vivo pharmacokinetic performance of ABZ salt was evaluated. The results of this study reveal that the new solid form of ABZ is primarily associated with amino acid esters and benzimidazole groups, forming intermolecular interactions. All three ABZ salts significantly improved the solubility and dissolution rate of ABZ, with ABZ-HCl demonstrating the optimal performance. Importantly, the drug salt exhibited robust physical stability when exposed to adverse conditions, including strong light irradiation (4500 ± 500 lux), high humidity (92.5 ± 5% relative humidity), elevated temperatures (50 ± 2 °C), and accelerated test conditions (40 °C/75 ± 5% relative humidity). Lastly, the in vivo pharmacokinetic analysis demonstrated that ABZ salt led to a substantial increase in AUC_(0–24) and C_max compared to ABZ. This elevation in solubility in aqueous solvents signifies that ABZ salt exhibits characteristics that can enhance oral bioavailability and pharmacokinetics. These findings provide potential solutions for the development of more effective and innovative drug formulations. Full article

To explore the impact of different factors on the effectiveness of borehole gas extraction, in situ stress tests were conducted in a test mining area. A theoretical model of gas migration within the coal matrix–fracture system was established. Based on field data, a numerical model was constructed to study the variation patterns of the effective extraction radius under different extraction conditions. Using the response surface methodology, the interactions of different factors and their impact on the effective extraction radius were analyzed, resulting in a response surface model for each factor and the effective extraction radius. The results indicate that the initial permeability of the coal seam has the greatest impact on the extraction radius, with a maximum range of 2.027 m. The influence of extraction time, extraction negative pressure, and borehole diameter decreases sequentially. The borehole diameter has the least impact, with a range of 0.608 m. The response surface model has good significance, with a coefficient of determination (R²) of 0.9957, and it can explain over 99.57% of the response values. The response surface between the initial permeability of the coal seam and extraction time shows the greatest degree of distortion, indicating a significant interaction effect on the extraction radius. In contrast, the response surface between extraction time and extraction negative pressure shows the least degree of distortion, indicating that their interaction effect is the least significant. These findings can provide a theoretical reference for improving borehole design and enhancing gas extraction efficiency. Full article

Onion (Allium cepa L.), a globally cultivated vegetable crop, possesses a shallow root system, making it vulnerable to abiotic stresses. The increasing frequency of extreme weather events in recent years necessitates sustainable solutions to enhance onion growth. Biostimulants offer a promising and accessible approach to promote onion growth and quality in an environmentally friendly and sustainable manner. This study investigated the effects of nine commercial microbial biostimulants (LALRISE Mycorrhizae, LALRISE Bacillus, Mighty Mycorrhizae, MycoApply, Spectrum DS, Spectrum Myco, Spectrum, Tribus Original, and Tribus Continuum) and one non-microbial commercial biostimulant (Kelpak—seaweed extract) on the seedling growth of three onion cultivars: Carta Blanca (white), Don Victoro (yellow), and Sofire (red). The results indicated that biostimulants did not significantly affect onion seed germination, but germination rates did vary among the onion cultivars. These cultivars also exhibited significant morphological and biomass differences, with principal component analysis revealing a more obvious effect on root growth compared to shoot growth. Kelpak seaweed extract increased the plant height, leaf area, and shoot fresh weight and dry weight of onion seedlings but decreased the root-to-shoot dry-weight ratio. The effects of microbial biostimulants on onion seedling growth depended on both the onion cultivar and Kelpak seaweed extract. In general, LALRISE Mycorrhizae, Mighty Mycorrhizae, Spectrum Myco, Spectrum DS, and Tribus Continuum exhibited positive effects on seedling growth in certain onion cultivars. Furthermore, the benefits of microbial biostimulants were amplified when combined with Kelpak seaweed extract application. These findings suggest a synergistic interaction between microbial and non-microbial biostimulants, leading to enhanced onion seedling growth. Further research is required to evaluate the long-term effects of these biostimulants on onion plant growth after transplanting to fields. Full article

Melilotus officinalis has been traditionally used as an anti-inflammatory agent; nevertheless, a comprehensive evaluation of its efficacy and safety and comparison with standard drugs are lacking. Taking into consideration concerns with current therapies, like efficacy limitations, side effects, and resistance, we aimed to develop a natural gel and cream based on Melilotus officinalis extract and explore their anti-inflammatory potential. After the chemical analysis of the extract confirmed the presence of coumarin, p-coumaric acid, gallic acid, and quercetin, formulations were prepared and subjected to physical and chemical stability evaluations over 6 months. The safety potential was tested in rats, while the anti-inflammatory activity was assessed both via in silico tests and in a rat model of inflammation. The examined formulations showed stable physical characteristics at the defined storage conditions and did not exert any sign of adverse skin reaction. The gel formulation exhibited a remarkable effect in inflammation reduction comparable with hydrocortisone. The in silico results suggest that coumarin, p-coumaric, and gallic acid bind to COX-1 and COX-2 with a lower affinity compared to diclofenac. On the other hand, quercetin demonstrated comparable inhibitory activity and stronger interaction compared to the control drug. Our results indicate that the examined formulations are stable and safe and may be promising dermal products for the alleviation of inflammatory skin conditions. Full article