Search Results (308)

The Nuri deposit is currently the only Cu-W-Mo deposit in the Gangdese metallogenic belt, Tibet, China, that contains large-scale tonnages for both Cu and WO₃ resources, accompanied by a medium-scale Mo resources. Previous studies have suggested the potential presence of concealed porphyry-type orebodies at depth, yet effective exploration tools for verifying this hypothesis remain lacking. In this study, microscopic identification, electron probe microanalysis (EPMA), and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) were integrated to investigate the mineral chemical characteristics of chlorite from the Nuri deposit. The aim was to evaluate the effectiveness of chlorite geochemistry as an exploration vector for predicting deep concealed porphyry orebodies and to establish corresponding exploration indicators. Chlorite in the deposit can be genetically classified into metasomatic (Chl-I) and hydrothermal (Chl-II) types. Both types are Mg-rich varieties, indicating formation under conditions of low oxygen fugacity and low pH. With decreasing vertical distance to the orebody and toward the southeast direction of the exploration section, the contents of Ti (10–950 ppm) and V (50–820 ppm), as well as the Ti/Sr, Ti/Mn, Ti/Li, and V/Li ratios, progressively increase. In contrast, the concentrations of Li (36–390 ppm), Mn (1270–6730 ppm), Sr (1–510 ppm), and Zn (110–1100 ppm) systematically decrease. These systematic compositional variations demonstrate that chlorite geochemistry is an effective exploration tool in the Nuri mining area and suggest the presence of a concealed mineralization center or porphyry orebody beneath the interval from ZK4501 to ZK4502. Full article

This study investigates the possibility of producing a complex W–Mo–Cr-containing alloy via metallothermic reduction of oxide concentrates in the presence of direct reduced iron (DRI) in an induction furnace under atmospheric conditions. A complex FeAlSiCa alloy was used as a reductant due to its high exothermicity and combined reducing potential. Thermodynamic analysis showed that the reduction of WO₃ and MoO₃ is more favorable compared to Cr₂O₃, which is reflected in the temperature profiles of the process. Experimental results confirmed that the addition of FeAlSiCa leads to intensive exothermic reactions and promotes melt formation. The estimated apparent recovery of W and Mo reached up to ~99%, while Cr estimated apparent recovery remained lower (up to ~70%) due to its higher thermodynamic stability and kinetic limitations. Microstructural analysis revealed a heterogeneous structure consisting of an Fe-based matrix and W–Mo-rich phases, including characteristic “fishbone” morphologies. An increase in reductant amount led to higher Si content in the alloy, indicating the need for composition optimization. The results demonstrate the feasibility of direct complex alloying as an alternative to conventional ferroalloy-based methods and highlight the potential for developing resource-efficient and low-carbon metallurgical technologies. Full article

Reversible emulsion drilling fluids integrate the advantages of water-based and oil-based systems, offering solutions to critical challenges in shale oil and gas development. However, conventional reversible emulsions face limitations including poor stability, high cost, and material scarcity. This research introduces widely available, eco-friendly modified nanocrystalline cellulose (MNCC) as a sustainable alternative. While current reversible drilling fluids primarily depend on organoclays and adopt aqueous phases containing 20–25% CaCl₂ for shale inhibition, pH-responsive MNCC was validated as an effective reversible emulsifier capable of stabilizing emulsions through 48 consecutive phase-inversion cycles. Enhanced emulsion stability was achieved with organoclay at an optimal dosage (≤2.5 g/100 mL), and a composite interfacial film superior to the film formed by pure MNCC was fabricated via the combination of organoclay and MNCC. Increasing the organoclay content elevated the acid requirements for phase inversion (due to its lipophilicity) but reduced the alkali needs. Finally, higher CaCl₂ concentrations in the aqueous phase reduced the acid demand for inversion yet increased alkali consumption and diminished stability in both oil-in-water (O/W) and water-in-oil (W/O) emulsions. These effects are attributed to the dual role of CaCl₂ in compressing the electrical double layer and modifying phase density differences, synergistically governing reversible inversion behavior. This research provides a foundation for applying nanocrystalline cellulose-stabilized reversible emulsion drilling fluids, offering practical solutions for efficient development of sensitive reservoirs like shale. Full article

Large language models (LLMs) are an emerging artificial intelligence-driven technology, based on transformer architecture. LLMs are widely used in modern education, both by learners and tutors, as standalone tools or integrated into e-learning systems, where they can support personalization, adaptive learning, automated assessment and feedback, content generation, and intelligent tutoring. LLMs offer many benefits for learners, but they also have significant limitations. One approach to address the limitations of LLMs is to combine them with other intelligent technologies. The primary goal of this systematic survey is to identify appropriate supporting technologies, mechanisms of use, and methodological approaches able to help overcome the limitations of LLMs and support their responsible and effective use in education. For this reason, analysis and discussion of recent scientific research (published over the last four years) accessible through Google Scholar, ACM, IEEE Xplore, or indexed in Scopus or Web of Science (WoS) is performed. A bibliometric analysis of results from the initial general query strings is used to refine and formulate more specific search queries during the literature retrieval process in the selected databases. Full-text exploration of relevant search results serves as a source for critical analysis and deductions leading to the following conclusion: LLMs should be integrated into e-learning systems, combined with knowledge graphs, ontologies, learning analytics, and multimodal reasoning to enhance reliability, improve pedagogical effectiveness, and enable true personalization. New pedagogical approaches are also needed to ensure the effective use of LLMs in both tutoring and assessment contexts. Therefore, the authors propose methodological guidelines for integrating LLMs in complex modular educational systems. Full article

The development of efficient, single-phase-excitable white-light phosphors remains a critical challenge for solid-state lighting applications. In this work, white-light-emitting CaWO₄:Eu³⁺/g-C₃N₄ composites were successfully developed by integrating red-emitting CaWO₄:7%Eu³⁺ with blue-emitting graphitic carbon nitride (g-C₃N₄). Under 365 nm near-UV excitation, the composite exhibits dual-band emission originating from the ⁵D₀ → ⁷F₂ transition of Eu³⁺ (~616 nm) and the intrinsic band-edge luminescence of g-C₃N₄ (~460 nm). The optimal white-light performance is achieved at a g-C₃N₄ content of 0.5 wt%, yielding CIE chromaticity coordinates of (0.294, 0.324) and a correlated color temperature (CCT) of 7673 K. This sample demonstrates a photoluminescence quantum yield (PLQY) of 3.25%. Moreover, the CaWO₄:Eu³⁺/g-C₃N₄ composite shows enhanced thermal stability, retaining 78% of its initial emission intensity at 175 °C, with an activation energy of 0.41 eV—significantly higher than that of the pristine CaWO₄:Eu³⁺ (0.22 eV). These results indicate that the CaWO₄:Eu³⁺/g-C₃N₄ heterostructured phosphor is a promising candidate for single-phase-excitable white-light applications. Full article

Tree detection is a core task in forest inventory and mapping, yet reliable stem identification remains difficult in dense and structurally complex forests. This study systematically reviews the literature on terrestrial laser scanning (TLS)-based tree detection to summarize methodological development, identify persistent challenges, and highlight research gaps. Records were retrieved from Scopus and Web of Science (WoS). Following PRISMA 2020, 39 articles were included and analyzed using Bibliometrix v 5.2.1 package in R Studio 2026.01.1 and qualitative content coding. The reviewed studies were published between 2011 and 2025 in 20 peer-reviewed journals and involved 169 authors from 73 institutions across 24 countries. The literature was organized into three developmental phases: foundational development (2011–2015), rapid growth (2016–2020), and refinement and integration (2021–2025). Across these phases, methods evolved from geometric fitting and clustering to voxel-based and increasingly integrated workflows. Reported performance varied markedly with scan configuration, forest structure, and algorithm design, ranging from very low detection rates to near-complete detection under favorable conditions. Overall, TLS shows strong potential for forest inventory; however, dense stands, multilayered forests, and regeneration-rich environments remain major challenges. Full article

Glasses with compositions (52.5 − x/2)B₂O₃:(12.5 − x/2)SiO₂:25La₂O₃:5ZnO:5CaO:0.5Eu₂O₃:xWO₃, x = 0, 2.5, 5, 7.5, 10, 20 (mol%) were prepared by conventional melt-quenching method and investigated by X-ray diffraction analysis, DSC analysis, DR-UV-Vis spectroscopy and photoluminescence spectroscopy. Physical parameters like density, molar volume, oxygen molar volume and oxygen packing density were also determined. Their values, as well as DR-UV-Vis spectroscopy results, indicate that the tungstate ions incorporate into the base borosilicate glass as tetrahedral WO₄ and octahedral WO₆ groups. With increasing WO₃ content over 5 mol%, WO₆ units are progressively linked to each other by W-O-W bonds, leading to the formation of a more connected and homogeneous glass network. Glasses are characterized by a high glass transition temperature (over 650 °C) and good thermal stability. The emission intensity of the Eu³⁺ ion increases with the introduction of WO₃ due to the occurrence of non-radiative energy transfer from the tungstate groups to the active ion. The most intense luminescence peak observed at 612 nm suggests that the glasses are potential materials for red emission. Full article

The rapid adoption of generative artificial intelligence (AI) systems has transformed health information seeking, raising questions about their role as intermediaries in non-professional health self-consultation. This study compares Google Search and ChatGPT as paradigmatic models of algorithmic mediation of health information, focusing on accuracy, biases, information quality and potential harms. A scoping review was conducted following the PRISMA-ScR framework. Empirical studies published between 2023 and 2025 were retrieved from PubMed/MEDLINE, Web of Science (WoS) and Scopus. After screening and eligibility assessment, 63 original empirical studies were included. The results indicate that ChatGPT consistently outperforms Google Search in terms of factual accuracy and information quality, achieving moderate to high DISCERN scores (4–5 out of 5) and showing moderate to strong correlations with expert clinical evaluations. Users also tend to value ChatGPT responses positively due to their clarity, coherence and perceived empathy. However, these advantages coexist with significant structural limitations. Hallucinations are reported in an estimated 31–45% of references, source provenance remains opaque, linguistic complexity is high, and actionability is limited, with only around 40% of responses providing clearly actionable guidance. In contrast, Google Search offers greater source traceability and verifiability, but at the cost of fragmented information and higher exposure to commercial content. The review identifies critical research gaps related to behavioural impacts, critical health literacy, equity of access, professional integration and vulnerable contexts. Overall, the findings highlight the need for hybrid human–AI models, professional mediation and critical AI literacy to ensure safe, equitable and trustworthy use of generative AI in public health communication. Full article

New glass-free low-temperature co-fired microwave dielectric composites with compositions (1–4x/3)Ba₃(VO₄)₂–xBaWO₄–(2x/3)Li₃VO₄ (x = 0.3–0.7) were fabricated by reactive liquid-phase sintering of (1–x)Ba₃(VO₄)₂–xLi₂WO₄ mixtures at 850 °C. During sintering, Li₂WO₄ is fully consumed by reacting with Ba₃(VO₄)₂ to form BaWO₄ and Li₃VO₄ while providing a transient liquid phase that promotes densification. As a result, the sintered ceramics achieve high relative densities of ≈94–98% at 850 °C. The relative fractions of Ba₃(VO₄)₂, BaWO₄, and Li₃VO₄ can be systematically tailored by adjusting the initial Li₂WO₄ content, enabling effective control of the temperature coefficient of the resonant frequency (${\tau }_f$) and the quality factor (Q × f). With increasing Li₂WO₄ content, the ${\tau }_f$ values shift from +23.97 to −45.48 ppm/°C, owing to the increasing contributions of the negative ${\tau }_f$ phases BaWO₄ and Li₃VO₄, while the Q × f values increase moderately from 44,300 to 47,300 GHz. The optimal microwave dielectric properties are obtained for x = 0.5, meaning ${\epsilon }_r$ = 9.19, Q × f = 45,900 GHz, and ${\tau }_f$ = −1.15 ppm/°C when sintering at 850 °C for 1 h. Chemical compatibility tests confirmed that the composites exhibit no detectable reaction with Ag electrodes, indicating that the Ba₃(VO₄)₂–BaWO₄–Li₃VO₄ system is a promising glass-free dielectric for LTCC applications requiring low firing temperature, near-zero thermal drift, and reliable electrode compatibility. Full article

The formulation of solid cosmetic products with elevated water content poses considerable challenges, particularly in the context of lip care products, where water contributes to hydration, enhances texture, and facilitates the dissolution of hydrophilic active ingredients. Conventionally, these products are based on water-in-oil (W/O) emulsions embedded in a solid matrix, stabilised primarily by synthetic emulsifiers. However, an increase in consumer demand for eco-friendly formulations has resulted in a heightened interest in natural emulsifiers. In this study, the performance of IDRAWAX^® REVO, a natural emulsifying and structuring agent, was evaluated in solid W/O formulations with varying water concentrations. The findings indicate that IDRAWAX^® REVO efficiently stabilises emulsions across diverse oil and water contents, thereby preserving product uniformity and stability. These findings emphasise the potential of this approach to streamline the formulation of water-based solid cosmetics, thus obviating the necessity for synthetic emulsifiers. This work represents a significant advancement in the field of solid cosmetic formulation, thereby facilitating the development of innovative products that exhibit enhanced properties and optimised textures. Full article

Eye tracking has become a central method in human–computer interaction (HCI), supported by advances in sensing technologies and AI-based gaze analysis. Despite this rapid growth, a comprehensive and up-to-date overview of eye-tracking research across the broader HCI landscape remains lacking. This study combines records from Web of Science (WoS) and Scopus to analyse 1033 publications on eye tracking in HCI published between 2020 and 2025. After merging and deduplicating the datasets, we conducted bibliometric network analyses (keyword co-occurrence, co-citation, co-authorship, and source mapping) using VOSviewer and performed a qualitative content analysis of the 50 most-cited papers. The literature is dominated by journal articles and conference papers produced by small- to medium-sized research teams (mean: 3.9 authors per paper; h-index: 29). Keyword and overlay visualisations reveal four principal research axes: deep-learning-based gaze estimation; XR-related interaction paradigms within HCI; cognitive load and human factors; and usability- and accessibility-oriented interface design. The most-cited studies focus on gaze interaction in immersive environments, deep learning for gaze estimation, multimodal interaction, and physiological approaches to assessing cognitive load. Overall, the findings indicate that eye tracking in HCI is evolving from a measurement-oriented technique into a core enabling technology that supports interaction design, cognitive assessment, accessibility, and ethical considerations such as privacy. This review identifies research gaps and outlines future directions for benchmarking practices, real-world deployments, and privacy-preserving gaze analytics in HCI. Full article

With the continuous growth in the scale of engineering simulation and intelligent manufacturing workflows, more and more problem-solving tasks are migrating to cloud computing platforms to obtain elastic computing power. However, a core operational challenge for cloud platforms lies in the difficulty of stably obtaining high-quality scheduling solutions that are both efficient and free of symmetric redundancy, due to the coupling of multiple constraints, partial resource interchangeability, inconsistent multi-objective evaluation scales, and heterogeneous resource fluctuations. To address this, this paper proposes a Dual-Improved Whale Optimization Algorithm (DI-WOA) accompanied by a modeling framework featuring discrete–continuous divide-and-conquer modeling, a unified monetization mechanism of the objective function, and separation of soft/hard constraints; its iterative trajectory follows an augmented Lagrangian dual-rollback mechanism, while being rooted in a three-layer “discrete gene–real-valued encoding–decoder” structure. Scalability experiments show that as the number of tasks J increases, the DI-WOA ranks optimal or sub-optimal at most scale points, indicating its effectiveness in reducing unified billing costs even under intensified task coupling and resource contention. Ablation experiment results demonstrate that the complete DI-WOA achieves final objective values (OBJ) 8.33%, 5.45%, and 13.31% lower than the baseline, the variant without dual update (w/o dual), and the variant without perturbation (w/o perturb), respectively, significantly enhancing convergence performance and final solution quality on this scheduling model. In robustness experiments, the DI-WOA exhibits the lowest or second-lowest OBJ and soft constraint violation, indicating higher controllability under perturbations. In multi-workload generalization experiments, the DI-WOA achieves the optimal or sub-optimal mean OBJ across all scenarios with H = 3/4, leading the sub-optimal algorithm by up to 13.85%, demonstrating good adaptability to workload variations. A comprehensive analysis of the experimental results reveals that the DI-WOA holds practical significance for stably solving high-quality scheduling problems that are efficient and free of symmetric redundancy in complex and diverse environments. Full article

Traditional rapid coagulation processes often compromise the quality of selenium-enriched tofu, leading to suboptimal texture and substantial nutrient loss. This study regulated the gel properties and nutrient retention of selenium-enriched tofu by controlling magnesium ion (Mg²⁺) release from a water-in-oil (W/O) emulsion coagulant through shear rate adjustment (6000–12,000 r/min). The results demonstrated that at the optimal shear rate of 8000 r/min, sustained Mg²⁺ release facilitated the formation of a homogeneous and dense microstructure accompanied by significantly increased β-sheet content. Compared with conventional methods, the resulting tofu exhibited significant improvements in resilience (increased from 38.73% to 42.54%), water-holding capacity, and nutrient retention, with the selenium content rising from 44.42% to 54.57%. Conversely, deviations from this optimal condition produced either mechanically weak gels or structurally compromised networks with reduced nutrient retention capacity. This study establishes the regulation of shear rate to control Mg²⁺ release rate as an effective strategy for producing premium selenium-enriched tofu with synchronized optimization of texture and nutritional value, providing new insights for improving the overall quality of functional plant-based protein gels. Full article

Plant oils are increasingly explored as sustainable functional ingredients in topical emulsions due to their emollient properties and reported photoprotective potential. This study aimed to formulate physically stable W/O emulsions containing selected plant oils (olive, avocado, sesame, flaxseed, and grape seed oils) at two concentrations (15% and 30%) and to evaluate their physicochemical, rheological, occlusive, and UV-protective properties. All formulations were confirmed as W/O systems with skin-compatible pH values and demonstrated shear-thinning, non-Newtonian flow with varying degrees of thixotropy. Increasing oil content from 15% to 30% reduced shear stress, consistency index, and viscoelastic moduli, indicating a softer internal structure. Moreover, the viscosities of the emulsions were not solely determined by the viscosities of the individual oils, suggesting significant interactions with the emulsifier system. High occlusion factors were demonstrated for all emulsions, with the highest values observed for 30% olive- and grape seed oil–based formulations. Spectrophotometric SPF assessment revealed measurable UV-protective activity only for emulsions containing 30% olive, avocado, or flaxseed oil (SPF > 1). All formulations exhibited satisfactory physical stability under mechanical and thermal stress. These findings demonstrate that plant oils can modulate the structure and performance of W/O emulsions and may serve as valuable supportive ingredients in the development of photoprotective cosmetic products. Full article

This work focuses on testing and validating a prototype device for measuring mass transfer phenomena in biomass drying processes, patented by the Universitat Politècnica de València (UPV) and Escuela Politécnica del Litoral (ESPOL), WO2025/109237 A1. The first step involved evaluating and calibrating the sensors of the measuring device to ensure accurate and consistent measurements. Subsequently, extensive tests were conducted to validate the prototype’s functionality for obtaining mass diffusivity and the mass transfer coefficient by convection at the solid-air interface. Finally, the results obtained were compared with those provided by existing predictive theoretical models in the literature. Areas for improvement in the theoretical models were identified, and adjustments were made to optimize prediction. The study highlights that the theoretical Sherwood method for estimating the mass transfer coefficient shows discrepancies with experimental data, mainly due to the assumption that the transfer coefficient remains constant during drying, whereas it actually varies with the material’s moisture content. This leads to inaccuracies that affect the efficiency of industrial drying systems. The prototype proved effective in measuring both diffusivity and mass transfer coefficient, validating the method. Full article