Search Results (874)

In the era of global energy transition, the development of third-generation photovoltaic technologies, such as dye-sensitized solar cells, has emerged as a paramount challenge in materials engineering. This study is dedicated to the synthesis and implementation of graphene quantum dots as eco-friendly sensitizers within DSSC architectures. The GQDs were synthesized via a microwave-assisted hydrothermal route using biodegradable organic precursors, providing a “green” alternative to conventional, toxic heavy-metal-based materials. The nanocrystalline structure and optoelectronic properties of the sensitizer were verified through UV-Vis and visual photoluminescence assessment. A focal point of this research was the optimization of the GQD concentration on the mesoporous surface of the titanium dioxide photoanode. Measurements were conducted utilizing a custom-designed experimental setup integrated with 3D-printed (FDM) components and an Arduino microcontroller, ensuring precise data acquisition under controlled illumination conditions (405–625 nm). The results indicated an optimal operational point at a fivefold dilution of the stock solution (0.4 g/dm³), which yielded the highest open-circuit voltage ($V_{\mathrm{oc}}$) of 545.4 mV under UV irradiation. The decline in photovoltaic performance observed at higher concentrations was attributed to excessive nanostructure agglomeration, which effectively blocked the mesopores of the semiconductor. Furthermore, the demonstrated high chemical capacitance of the system imparts electrochemical capacitor-like characteristics to the cell, enabling energy stabilization under fluctuating illumination. To elucidate the underlying sensitization mechanisms at the atomic level, computational simulations were conducted utilizing the MACE machine-learning potential and the GFN2-xTB semi-empirical method. The theoretical models revealed that the formation of stable covalent Ti–O–C bridges (chemisorption) is imperative for establishing strong interfacial electronic coupling. Solvation models and molecular dynamics (MD) at 300 K confirmed the thermodynamic and operational robustness of the hybrid system in an aqueous electrolyte. Ultimately, this combined experimental and theoretical work conclusively demonstrates that graphene quantum dots represent an efficient, highly stable, and non-toxic alternative to classic molecular dye sensitizers. Full article

As the primary carrier for oil and gas transportation, pipelines are critical for the entire industry. Pipelines are continuously subjected to corrosion and abrasion in the oil and gas delivery process, leading to gradual wall thickness reduction, shortened service life, and deteriorated operational safety. Ultrasonic testing has been widely adopted for monitoring pipeline wall thickness. Conventional ultrasonic transducers possess rigid configurations, which hinder large-area inspection and exhibit poor adaptability to complex curved components. In contrast, flexible ultrasonic sensors show prominent advantages, with their small size, light weight, and excellent conformal contact with curved surfaces. Flexible piezoelectric thin-film sensors have been used in a wide range of fields. As one of the most representative piezoelectric polymers, poly(vinylidene fluoride–trifluoroethylene) (P(VDF-TrFE)) combines favorable piezoelectric coefficients and intrinsic flexibility, making it popular. Some research groups have investigated the influences of modified filler particles, doping ratios, and fabrication process optimization on the performance of P(VDF-TrFE)-based piezoelectric composites, while others have concentrated on the practical applications of existing flexible piezoelectric sensors. This study emphasizes a rapid customized fabrication strategy for flexible sensors instead of single-specification standardized probes; hence, it does not share the same comparison benchmark as conventional fixed-dimension sensors. Systematic research on flexible piezoelectric thin-film sensors is presented, including piezoelectric material modification, substrate design, laminated structural design, fabrication workflows, establishment of the testing platform, and the development of matched circuit systems. The material preparation and manufacturing processes are optimized, and a scalable technical route for fabricating flexible piezoelectric sensors is proposed. Using this route, flexible piezoelectric thin-film sensors can be rapidly tailored for different application scenarios to satisfy diverse engineering demands. Multiple experiments were conducted on pipeline samples with varying wall thicknesses and curvatures. The results verify that the sensor reaches a measurement precision of 0.01 mm, meeting the demands of high-precision pipeline structural health monitoring. Full article

Firefighters are exposed to complex smoke containing volatile, semivolatile, aromatic, and particulate-associated organic contaminants that accumulate on skin, clothing, and protective equipment. Conventional gas sensors monitor only selected airborne species, while passive samplers require laboratory analysis and cannot provide continuous exposure assessment. To address this limitation, we developed a proof-of-concept mass-capacitor that integrates contaminant absorption and electrical sensing within a single polydimethylsiloxane/functionalized carbon nanotube (PDMS/f-CNT) composite coated on interdigitated electrodes (IDEs). Unlike conventional sensors that report the instantaneous concentration of selected compounds, the proposed platform functions as both a sorptive collector and an electrical transducer. It continuously converts contaminant uptake, retention, and release into a time-resolved electrical response. For firefighter applications, this mass-capacitor bridges the gap between passive sorptive samplers and conventional real-time gas sensors. It enables continuous tracking of the cumulative sorbed contamination burden without requiring offline laboratory analysis or restricting the measurement to selected airborne species. A custom potentiostat applied staircase cyclic excitation, while Fast Fourier Transform (FFT)-assisted processing enabled extraction of the differential charge, $\mathsf{\Delta }Q$ as an indicator of contaminant loading. The sensor was evaluated using smoke generated from cotton, paper, wood, and synthetic fibers. Compared with PDMS alone, the PDMS/f-CNT composite produced an approximately 24-fold higher response with minimal humidity interference (≈80% RH). Limits of detection ranged from 0.08 to 0.26 ppm, while repeated smoke exposures produced stepwise increases in ΔQ, demonstrating continuous tracking of cumulative contaminant loading. These results establish the feasibility of the mass-capacitor concept and introduce a new approach for real-time monitoring of the accumulated organic contamination burden rather than the instantaneous concentration of individual airborne compounds. Full article

The Ganjiang River–Poyang Lake Basin is a typical river–lake composite water-system region and a major concentration area of intangible cultural heritage (ICH) in Jiangxi Province. However, officially listed ICH does not simply represent the natural distribution of cultural practices but reflects the combined effects of historical accumulation, environmental contexts, and institutional recognition. Based on 616 national- and provincial-level ICH items, this study employs the nearest neighbor index, kernel density analysis, Lorenz curve, standard deviational ellipse, and Geodetector to examine spatial patterns and associated factors. The results reveal significant spatial clustering (NNI = 0.31, Z = −39.16), characterized by riverine concentration, lakeside distribution, and polycentric development. Traditional craftsmanship and folk customs cluster around Poyang Lake, while traditional drama, folk literature, and quyi extend along the Ganjiang River. Distance to major water systems (q = 0.821), policy support (q = 0.813), and inheritors (q = 0.806) show the highest explanatory power. The findings reveal a spatial process of lake-area accumulation, river-channel diffusion, and nodal support. Full article

Open banking enables customers to provide third parties with financial information, yet this will be successful only when customers are ready to share it. Previous research concentrates on security, trust, and usefulness as direct motivators without paying attention to mechanisms. This research fills this gap by evaluating the effect of Perceived Security Assurance, Trust in Banks and FinTech Providers, and Perceived Usefulness on Willingness to Share Financial Data based on Perceived Data Control, which is based on Privacy Calculus Theory. A combination of cluster and purposive sampling was used to collect data from digital banking users in five regions in Saudi Arabia. There were a total of 384 valid responses that were analysed. SmartPLS 4 was used to run Partial Least Squares Structural Equation Modelling. The results reveal that PSA, TBFP, PUOB, and PDC directly impact WSFD and that PSA, TBFP, and PUOB also have a considerable impact on PDC. The outcomes of the mediation confirm that PDC mediates these relationships partially. Multi-group analysis also shows that these effects are greater amongst users with less experience in FinTech and with younger customers, especially in the pathways that involve perceived data control. The work adds to the theory in two ways. The extension of the Privacy Calculus Theory by adding the perceived control and pointing out the heterogeneity of users in data-sharing behaviour. It also changes the attention from the general adoption intention to the actual data-sharing behaviour in open banking. Practically, the results suggest that to foster customer engagement in open banking ecosystems, it is necessary to improve security, develop trust, prove value, provide user control, and use segment-specific actions. Full article

Digital technologies are increasingly adopted in corporate liquidity management, yet whether financial digitalization enables firms to achieve more effective working capital adjustment remains insufficiently understood. Financial shared services (FSS) may strengthen information integration, process standardization, and operational coordination, but existing research provides limited evidence on how external supply chain conditions shape the relationship between FSS and working capital adjustment effectiveness. Prior studies have focused primarily on adjustment speed rather than adjustment effectiveness, namely the extent to which firms maintain working capital close to target levels. Using panel data from Chinese A-share listed firms from 2014 to 2023, this study examines whether FSS is associated with the effect of working capital adjustment (DEV) and whether supply chain concentration moderates this relationship. Drawing on dynamic trade-off theory and information asymmetry theory, this study employs high-dimensional fixed-effects models to examine how internal information capabilities and external supply chain conditions jointly shape working capital adjustment. The findings show that firms adopting FSS tend to exhibit smaller deviations from target working capital levels, which is consistent with more effective adjustment. However, this association becomes weaker as supply chain concentration increases, suggesting that external dependence may constrain firms’ ability to translate enhanced internal information capabilities into improved working capital outcomes. Further analysis suggests that customer concentration plays a more prominent moderating role. This study extends the understanding of digital-enabled financial management beyond internal process improvement and identifies supply chain structure as an important boundary condition relevant to the value of FSS. Full article

This study examines how a food supplier’s perceptions of customer trustworthiness relate to its customer concentration, the extent to which a supplier’s sales are unevenly distributed across its major customers, and how customer concentration is associated with procedural fairness perceptions and relationship marketing performance amid market uncertainty in the food supply industry. The multilevel model results show that trustworthy relationships are more strongly associated with perceptions of procedural fairness in stable food supply markets, where product demand, price forecasts, retail sales, and input costs are more predictable. While high customer concentration promotes perceptions of procedural fairness, customer trustworthiness is more strongly related to those perceptions when the food supplier has a more diverse customer base. More importantly, customer trustworthiness is not directly related to food suppliers’ relationship marketing performance. Rather, customer trustworthiness shapes a food supplier’s perceptions of procedural fairness, which, in turn, provides an active pathway to improved relationship marketing performance. The study contributes to a better understanding of customer trustworthiness and procedural fairness in the development of sustainable food supply networks amid market uncertainty. Full article

Continuous inter-firm collaboration gives rise to technological innovation networks (TIN), which increasingly shape firms’ stakeholder perceptions and reputation. This study examines how TIN characteristics influence corporate reputation using Chinese A-share listed firms from 2018 to 2022. The results show that TIN scale, heterogeneity, and openness significantly enhance corporate reputation, while tie strength has no significant effect. Further analyses reveal that the employee income gap mediates the relationship between TIN scale and reputation with an inverted U-shaped effect. In addition, TIN heterogeneity improves reputation by enhancing investment efficiency, and TIN openness contributes to reputation enhancement by reducing customer concentration risk. These findings advance understanding of the reputational value of innovation networks and provide implications for network strategy and stakeholder management. Full article

Conventional spinal braces often suffer from poor fit and low breathability, with most 3D-printing research focusing on scoliosis rather than general support. This study evaluated the biomechanical performance and range of motion (ROM) restriction of a semi-custom 3D-printed brace (3DP) compared with two traditional braces (Medi-H, Medi-S). Sixteen participants performed static standing, flexion, extension, and pick-up tasks while wearing each brace. Interface pressure was recorded across seven anatomical regions, and thoracic (C7–T8) and lumbar (T8–L3) ROM were assessed simultaneously using repeated-measures ANOVA. Results showed that 3DP and Medi-H provided significantly greater overall pressures than Medi-S. During flexion and pick-up tasks, 3DP delivered enhanced support to the middle lumbar region and erector spinae, whereas Medi-H concentrated greater pressure on the spine, particularly during extension. Thoracic and lumbar ROM were restricted comparably across all braces (20–30°). In conclusion, 3DP achieves an equivalent restriction of sagittal motion to traditional braces while offering superior regional support to the upper and middle lumbar regions. Full article

Although digital transformation is increasingly regarded as a vital pathway toward corporate decarbonization, its environmental impacts can spread beyond the boundaries of the undergoing firms. This study explores whether digital transformation implemented by focal firms affects the carbon emission intensity of their upstream suppliers and downstream customers. Using data from Chinese A-share-listed companies over the period of 2009–2023, we find that focal firms’ digital transformation significantly reduces the carbon emission intensity of upstream and downstream partners. Supply chain concentration and partner digitalization partially mediate this relation, indicating that changes in supply chain structure and the diffusion of digital capabilities constitute important channels through which carbon reduction effects are transmitted. The effect is stronger for partners with higher total factor productivity, demonstrating that the efficacy of digital spillovers depends partly on firms’ productive efficiency and absorptive capacity. Further analysis shows that such effects are more prominent with heavily polluting industries, among smaller firms, and in industries with weaker competition. The results remain robust to alternative variable measurements, model specification, and treatments for potential endogeneity. These findings show that digital transformation generates environmental spillovers through vertical supply chain relationships and highlight the role of focal firms in facilitating supply chain carbon emission reduction. Full article

Post-combustion amine absorption is the most mature CO₂ capture technology, while membrane separation is a promising alternative due to its modularity and operational simplicity. Process intensification through exhaust gas recirculation (EGR) has also gained attention for increasing flue gas CO₂ concentration and reducing capture energy demand. However, comprehensive techno-economic comparisons of absorption, membrane, and hybrid systems under EGR-integrated NGCC conditions remain limited. This study presents a techno-economic assessment of multiple CO₂ capture configurations for a 450 MW NGCC power plant. Process simulations were performed using Aspen Plus and Aspen Custom Modeler to evaluate absorption, membrane, and hybrid systems integrated with conventional and selective EGR. The analysis considers full steam cycle integration and compares energy consumption, net plant efficiency, levelized cost of electricity (LCOE), and CO₂ avoidance cost. The results show that EGR significantly improves carbon capture performance. Among all cases, selective EGR combined with amine absorption delivers the best performance, reducing the energy penalty by more than 30% compared with standalone absorption and by over 70% relative to membrane separation. This configuration achieves an LCOE of approximately 72 USD/MWh and a CO₂ avoidance cost of about 39 USD/tCO₂, outperforming the selective EGR–membrane system (77 USD/MWh and 51 USD/tCO₂). These findings demonstrate that integrating selective EGR with amine absorption is a highly promising strategy for improving the technical and economic feasibility of CCSU in NGCC power plants. Full article

The growing demand for functional foods and personalized nutrition has increased interest in three-dimensional printing (3DP) as a technology for developing customized food products. Jostaberry (Ribes × nidigrolaria), a fruit rich in antioxidant compounds, has rarely been explored in 3DP food applications. This study evaluated the suitability of jostaberry for producing 3DP snacks and investigated the effects of starch type (corn or wheat) and storage (12 days/4 °C) on physicochemical properties, bioactive compounds, antioxidant capacity, and microbiological stability. Both starch type and storage significantly influenced product characteristics, whereas storage was the main factor affecting stability. During storage, moisture loss, changes in total soluble solids, color differences, and reductions in organic acid concentrations were observed. Although condensed tannins and anthocyanins decreased by 27.6% and 37.3%, respectively, total phenolic content remained relatively stable, suggesting compound-specific changes rather than an overall loss of phenolics. Compared with wheat starch, corn starch resulted in higher total flavonoid and hydroxycinnamic acid contents, whereas wheat starch retained higher malic acid concentrations. Antioxidant capacity also gradually decreased during storage. Despite these changes, the 3DP snacks remained microbiologically stable and complied with food safety requirements throughout the storage period. These findings demonstrate that jostaberry is a promising functional ingredient for 3DP snacks, providing high bioactive potential and acceptable refrigerated storage stability. Full article

Microneedle (MN) arrays offer a novel and minimally invasive platform for transdermal drug delivery. This study presents an approach for the design and fabrication of MN array models for biomedical applications using custom 3D-printed micro-molds. Material analysis of the polyvinyl alcohol (PVA) and polyvinylpyrrolidone (PVP) matrix in a 3:1 weight ratio was conducted under varying geometric configurations, curcumin (CUR) dosages, and target penetration depths of 300 to 500 μm. Computational simulation using computer-aided design (CAD) and finite element analysis (FEA) on ANSYS (Canonsburg, PN, USA) measured for total deformation, stress distribution, insertion pressure, and factor of safety. Elimination criteria were applied, narrowing down to specific models that were experimentally validated through material formulation, micro-molding, and material characterization. The selected MN models were analyzed by insertion and penetration efficiency testing on porcine skin. The results showed that higher CUR concentrations reduced mechanical strength and Young’s modulus, while mid-range dosages (2–6 mg) combined with optimized geometric spacing produced MNs with maintained structural integrity and effective performance. Conical microneedles demonstrated the most favorable balance of mechanical stability, controlled swelling behavior, and high insertion efficiency. The study recommends this approach as a feasible and reproducible method for localized wound-healing applications. Full article

Background/Objectives: Large language models (LLMs) show promise for clinical decision support, yet their accuracy in interpreting specialized medical guidelines remains uncertain. Retrieval-augmented generation (RAG) may enhance performance by grounding responses in authoritative knowledge bases. This study aimed to compare the accuracy, comprehensiveness, and safety of RAG-enhanced versus standard LLMs for answering clinical questions derived from the German S3 guideline for oral cavity carcinoma. Methods: We conducted a prospective, single-blind benchmark study evaluating six LLMs: one RAG-enhanced model (Custom GPT with guideline access), one consensus-based model (ConsensusGPT), and four standard models (DeepSeek-V3.2, Mistral Small 3.2, Qwen3-Next-80B, GPT-OSS-120B). Fifty clinical questions covering 17 guideline domains were presented to each model three times, yielding 900 evaluations. Three expert reviewers assessed responses using 5-point Likert scales for accuracy, comprehensiveness, and clarity, under a single-blind procedure, the effectiveness of which was tested by a pre-specified manipulation check. We then ran a paired within-model experiment in which each base model was queried with and without guideline access through a transparent, openly released retrieval pipeline, and scored every response with a condition-blind automated judge alongside deterministic retrieval metrics computed from the logs. Secondary outcomes included hallucination rates and guideline citation behavior. Inter-rater reliability was assessed using intraclass correlation coefficients (ICCs). Results: In a paired within-model design that held each base model fixed, adding transparent guideline retrieval improved accuracy—significantly in the three weaker open-weight models (Mistral, Qwen3, and GPT-OSS) and directionally in the already-strong DeepSeek and GPT-5 bases. Because a pre-specified blinding check found that experts could still identify retrieval-augmented answers with 98.5% accuracy, we anchored causal interpretation on measures that do not depend on the human raters, ranked by their independence: deterministic, log-derived retrieval metrics first, and then an automated, condition-blind LLM judge, whose agreement with the experts (Spearman ρ = 0.81, 95.7% within-one agreement) establishes shared calibration rather than independence from their bias. Deterministically from the retrieval logs, citation groundedness rose from 0% to 51–89% and retrieval recall@5 was 92%. On the judge, content-level hallucination fell from 42% to 4% and accuracy rose by a pooled +0.64 points (95% CI 0.47–0.80); the accuracy gain persisted after adjustment for response length (+0.48, 95% CI 0.22–0.73), which retrieval shortened rather than lengthened. The accuracy gain was large for weaker base models and small or non-significant for already-strong ones, whereas the hallucination and auditability gains were consistent across all models. The human ratings reproduced the judge’s accuracy effect (+0.61, 95% CI 0.49–0.74), and GPT-5 run through the transparent pipeline showed no significant difference from the proprietary Custom GPT (judge accuracy 4.48 vs. 4.58). Conclusions: Guideline retrieval yields a reproducible, largely base-independent improvement in the safety and auditability of LLM answers to clinical guideline questions, with accuracy gains concentrated in weaker base models. Because retrieval-augmented answers are recognizable to experts, rigorous evaluation should rely on rater-independent measures, and residual hallucination continues to require human oversight. Full article

As VR hardware advances, hardware-related factors inducing motion sickness are expected to be gradually resolved; consequently, software-based mitigation methods are garnering significant attention. While various software-based methods exist, they often rely on modifying the content itself, presenting a significant drawback: difficulty in immediate application to existing content. Meanwhile, the Visual Guide (VG) technique reduces sickness by superimposing a separate image onto the content. This approach offers the distinct advantage of being easily applicable to existing content. However, motion sickness mitigation via visual guides suffers from a drawback: the added imagery can distract from the content, thereby reducing user concentration. To address this, this paper proposes a mitigation method utilizing the transparency of the visual guide to minimize the loss of focus on the content. To evaluate the proposed method, experiments were conducted to collect EEG data, Simulator Sickness Questionnaire (SSQ) scores, and responses to a custom-designed concentration questionnaire. Under the tested conditions, the 60-s fade-out condition showed a favorable descriptive balance between lower mean SSQ score changes and preserved concentration. Because corrected pairwise post-hoc comparisons were not performed and the EEG analysis was based on whole-session average power spectral density, these findings should be interpreted as condition-level trends rather than definitive pairwise or event-related effects. Full article