Search Results (10,678)

Driven by the digital transformation of global value chains and the digital economy strategy outlined in China’s 14th Five-Year Plan, international trade competition is increasingly centered on digital technology ecosystems. This study addresses the gap in existing research that often overlooks the critical role of cities as key nodes in digital technology and global value chains, as well as the mechanisms through which the digital economy influences urban export trade. Using panel data from 273 prefecture-level Chinese cities between 2006 and 2022, we apply fixed effects, mediation, and multiple threshold regression models to analyze the mechanisms and nonlinear effects of the digital economy on urban export performance. Results show that the digital economy significantly facilitates urban export trade, with its marginal impact moderated by regional development levels and factor endowment structures. Eastern and central cities exhibit stronger export-driving effects, benefiting from resource agglomeration. Technological innovation and human capital accumulation are identified as the main transmission channels through which the digital economy promotes export upgrading. Additionally, the relationship between digital economy development and export trade demonstrates significant nonlinear characteristics across different regional economic development stages. The study emphasizes bridging the regional digital divide and enhancing technological innovation and human capital efficiency to drive digital transformation and boost urban export vitality. Full article

Background/Objectives: To compare patient-reported outcome measures (PROMs) between digital and conventional impression techniques for implant-supported fixed dental prostheses (iFDPs). Methods: A systematic literature search was conducted in PubMed, Embase, Scopus, and the Cochrane Library databases up to June 2025, following PRISMA guidelines. Human clinical studies reporting PROMs between digital and conventional impression techniques for iFDPs were included. Studies using structured, but not necessarily validated, questionnaires were eligible. Two reviewers independently performed study selection, data extraction, and risk of bias assessment. Where possible, meta-analyses were conducted using a random-effects model to pool comparable outcomes across studies using mean differences (MD) or standardized mean differences (SMD) with 95% confidence intervals (CIs). Results: Out of 1784 records screened, eighteen studies were included. Most studies showed that digital impressions were associated with higher patient satisfaction, compared to conventional impressions. Ten studies contributed data to at least one outcome; pooled analyses included the following: overall satisfaction (k = 5), comfort (k = 7), gagging/nausea (k = 5), esthetic satisfaction (k = 2), unpleasant taste (k = 5), anxiety (k = 5), discomfort (k = 2), pain (k = 5), and overall discomfort (k = 5). Digital impressions were significantly favored (p < 0.05) for anxiety (MD = 13.3, 95% CI: −22 to −4.5), nausea (MD = −26.4, 95% CI −46.8 to −6.0), bad taste (MD = −34.8, 95% CI −58.3 to −11.3), discomfort (SMD = −2.24, 95% CI −3.51 to −0.98), comfort (SMD = 1.77, 95% CI: 0.60 to 2.94), perceived procedure time (SMD = 0.96; 95% CI 0.29 to 1.62), and overall satisfaction (SMD = 0.55; 95% CI 0.01 to 1.09). No statistically significant differences were found for pain or esthetic evaluation. Substantial between-study heterogeneity was observed among the included studies. Conclusions: Current evidence indicates that digital impression workflows enhance the overall patient experience for implant-supported fixed restorations, especially in domains linked to comfort and procedural efficiency. These findings support PROM-informed personalization of impression workflows: screening for gagging, anxiety, or intolerance to impression materials could guide patient-tailored use of intraoral scanning while acknowledging no consistent advantage for pain or esthetic perception. Full article

The increasing demand for portable health monitoring has highlighted the need for automated sleep staging systems that are both accurate and computationally efficient. However, most existing deep learning models for electroencephalogram (EEG)-based sleep staging suffer from parameter redundancy, fixed dilation rates, and limited generalization, restricting their applicability in real-time and resource-constrained scenarios. In this paper, we propose ADG-SleepNet, a novel lightweight symmetry-aware multi-scale dilation-gated temporal convolutional network enhanced with adaptive attention mechanisms for EEG-based sleep staging. ADG-SleepNet features a structurally symmetric, parallel multi-branch architecture utilizing various dilation rates to comprehensively capture multi-scale temporal patterns in EEG signals. The integration of adaptive gating and channel attention mechanisms enables the network to dynamically adjust the contribution of each branch based on input characteristics, effectively breaking architectural symmetry when necessary to prioritize the most discriminative features. Experimental results on the Sleep-EDF-20 and Sleep-EDF-78 datasets demonstrate that ADG-SleepNet achieves accuracy rates of 87.1% and 85.1%, and macro F1 scores of 84.0% and 81.1%, respectively, outperforming several state-of-the-art lightweight models. These findings highlight the strong generalization ability and practical potential of ADG-SleepNet for EEG-based health monitoring applications. Full article

This study focuses on the critical ignition conditions of emulsified matrix, defining the critical hot-spot temperature as the temperature at which the ignition probability of the emulsified matrix reaches 1% under the influence of an internal heat source within a fixed duration. By establishing an experimental system, the critical hot-spot temperature of the emulsified matrix was systematically determined by combining the Langley method with maximum likelihood estimation for statistical analysis. Furthermore, the influence of bubble content and ambient pressure on the critical hot-spot temperature was investigated. The study reveals that the critical hot-spot temperature decreases with increasing ambient pressure (at 1 atm, 2 atm, and 3 atm) and bubble content (at 0%, 1.5%, and 3%). However, under the coupled effects of ambient pressure and bubbles, bubble overflow phenomena may attenuate their influence. Full article

To overcome the limitations of conventional dampers and enhance seismic resilience in multi-span continuous bridges, this study synthesized a magnetorheological shear-stiffening gel (MRSSG) that integrates shear-stiffening (SS) materials with magnetorheological (MR) components, enabling passive rate-sensitive adaptation and magnetic-field-driven directionality. Leveraging this material, we developed a multifunctional MR damper combining high-frequency load-sharing locking and low-frequency magnetically controlled damping mechanisms. Numerical simulations under diverse seismic waves (El Centro, Koyna, and Wenchuan) demonstrated the damper’s effectiveness: it redistributed internal forces from fixed to movable piers, reducing fixed-pier shear forces by up to 62.3% (e.g., from 258,714 kN to 97,419 kN under Wenchuan waves), and under semi-active control via a semi-step on–off strategy, it suppressed displacement responses by >95% at movable-pier deck measurement points. This work establishes a robust solution for improving seismic performance in large-scale civil infrastructure. Full article

The rapid response of emergency vehicles is crucial but often hindered because sirens lose effectiveness in modern traffic due to soundproofing, noise, and distractions. Automatic in-vehicle detection can help, but existing solutions struggle with efficiency, interpretability, and embedded suitability. This paper presents a hardware-constrained Simulink implementation of a yelp siren detector designed for embedded operation. Building on a MATLAB-based proof-of-concept validated in an idealized floating-point setting, the present system reflects practical implementation realities. Key features include the use of a realistically modeled digital-to-analog converter (DAC), filter designs restricted to standard E-series component values, interrupt service routine (ISR)-driven processing, and fixed-point data type handling that mirror microcontroller execution. For benchmarking, the dataset used in the earlier proof-of-concept to tune system parameters was also employed to train three representative machine learning classifiers (k-nearest neighbors, support vector machine, and neural network), serving as reference classifiers. To assess generalization, 200 test signals were synthesized with AudioLDM using real siren and road noise recordings as inputs. On this test set, the proposed system outperformed the reference classifiers and, when compared with state-of-the-art methods reported in the literature, achieved competitive accuracy while preserving low complexity. Full article

This study analyzes the factors that affect the technical efficiency (TE) of firms in the supporting industry in the context of Vietnam’s digitalized economy. Stochastic frontier analysis (SFA), Fixed Effect Models, and System-GMM methods are applied to reach the findings that the quality of human resources, capital intensity, and firm size have positive effects on TE. Furthermore, exogenous environmental factors, such as the domestic demand of an industry impacting all upstream businesses, which use inputs that are products of that industry (BSpill-ratio), and the FDI backward effect (BFSpill), also exhibit positive effects. These confirm that the linkage between domestic supporting industry suppliers and FDI assembly enterprises plays an important role in improving TE. Vietnam’s digital transformation since 2020 has also created some interesting changes in the correlation coefficient. Location, sectors, competitiveness, and investment environment are also considered, and the results suggest that they are all determinants to be considered in management policies at both the firm level and the government level. Our contribution in this study is new policies aligned with many major changes in the world economic context, such as the tough tariff policy implemented by recent presidential administrations and a series of reforms of the Vietnamese Government, as well as strong digital transformation in Vietnam. The key findings of this research are important as they confirm which factors are really determinants for the Vietnamese government to implement investment policies for this industry effectively. Full article

Chronic respiratory diseases claim nearly four million lives annually, making them the third leading cause of death worldwide. Extracorporeal membrane oxygenation (ECMO) is often the last line of support for patients with severe lung failure. Still, its performance is limited by an incomplete understanding of gas exchange in hollow fiber membrane (HFM) oxygenators. Computational fluid dynamics (CFD) has become a robust oxygenator design and optimization tool. However, most models oversimplify O₂ and CO₂ transport by ignoring their physiological coupling, instead relying on fixed saturation curves or constant-content assumptions. For the first time, this study introduces a novel physiologically informed CFD model that integrates the Bohr and Haldane effects to capture the coupled transport of oxygen and carbon dioxide as functions of local pH, temperature, and gas partial pressures. The model is validated against in vitro experimental data from the literature and assessed against established CFD models. The proposed CFD model achieved excellent agreement with experiments across blood flow rates (100–500 $\mathrm{mL}/\min$ ), with relative errors below 5% for oxygen and 10–15% for carbon dioxide transfer. These results surpassed the accuracy of all existing CFD approaches, demonstrating that a carefully formulated single-phase model combined with physiologically informed diffusivities can outperform more complex multiphase simulations. This work provides a computationally efficient and physiologically realistic framework for oxygenator optimization, potentially accelerating device development, reducing reliance on costly in vitro testing, and enabling patient-specific simulations. Full article

Among other uses, DC-DC converters are employed in the auxiliary power modules (APMs) of electric vehicles (EVs), connecting the high-voltage traction battery to the low-voltage auxiliary system (AS). Traditionally, the APM is an isolated two-port, two-level (2L) DC-DC converter, and the auxiliary loads are fed at a fixed voltage level, e.g., 12 V in passenger cars. Dual-active-bridge (DAB) converters are commonly used for this application, as they provide galvanic isolation, high power density and efficiency, and bidirectional power flow capability. However, the auxiliary loads do not present a uniform optimum supply voltage, hindering overall efficiency. Thus, a more flexible approach, providing multiple supply voltages, would be more suitable for this application. Multiport DC-DC converters capable of feeding auxiliary loads at different voltage levels are a promising alternative. Multilevel neutral-point-clamped (NPC) DAB converters offer several advantages compared to conventional two-level (2L) ones, such as greater efficiency, reduced voltage stress, and enhanced scalability. The series connection of the NPC DC-link capacitors enables a multiport configuration without additional conversion stages. Moreover, the modular nature of the ML NPC DAB converter enables scalability while using semiconductors with the same voltage rating and without requiring additional passive components, thereby enhancing the converter’s power density and efficiency. This paper proposes a modulation strategy and decoupled closed-loop control strategy for the generalized multiport 2L-NL NPC DAB converter interfacing the EV traction battery with the AS, and its performance is validated through hardware-in-the-loop testing and simulations. The proposed modulation strategy minimizes conduction losses in the converter, and the control strategy effectively regulates the LV battery modules’ states of charge (SoC) by varying the required SoC and the power sunk by the LV loads, with the system stabilizing in less than 0.5 s in both scenarios. Full article

The COVID-19 pandemic has caused market turmoil and economic distress. To understand the effect of the pandemic on the U.S. financial systemic risk, we analyze the explanatory power of detailed COVID-19 data on three market-based systemic risk measures (SRMs): Conditional Value at Risk, Distress Insurance Premium, and SRISK. In the time-series dimension, we use the Dynamic OLS model and find that financial variables, such as credit default swap spreads, equity correlation, and firm size, significantly affect the SRMs, but the COVID-19 variables do not appear to drive the SRMs. However, if we focus on the first wave of the COVID-19 pandemic in March 2020, we find a positive and significant COVID-19 effect, especially before the government interventions. In the cross-sectional dimension, we run fixed-effect and event-study regressions with clustered variance-covariance matrices. We find that market capitalization helps to reduce a firm’s contribution to the SRMs, while firm size significantly predicts the surge in a firm’s SRM contribution when the pandemic first hits the system. The policy implications include that proper market interventions can help to mitigate the negative pandemic effect, and policymakers should continue the current regulation of required capital holding and consider size when designating systemically important financial institutions. Full article

The ecotoxicity induced by macrolides has attracted widespread attention, but their impacts on the nitrogen metabolism and symbiotic environmental bacteria of microalgae remain unclear. This study examined the effects of roxithromycin (ROX) on the growth, chlorophyll levels, and nitrogen metabolism of Chlorella pyrenoidosa; investigated the changes in the composition and functions of environmental bacterial communities; and finally, analyzed the relationship between microalgae and environmental bacteria. The results indicated that all concentrations of ROX (0.1, 0.25, and 1 mg/L) inhibited microalgae growth, but the inhibition rates gradually decreased after a certain exposure period. For instance, the inhibition rate in the 1 mg/L treatment group reached the highest value of 43.43% at 7 d, which then decreased to 18.93% at 21 d. Although the total chlorophyll content was slightly inhibited by 1 mg/L ROX, the Chl-a/Chl-b value increased between 3 and 21 d. The nitrate reductase activities in the three treatments were inhibited at 3 d, but gradually returned to normal levels and even exceeded that of the control group at 21 d. Under ROX treatment, the consumption of NO₃⁻ by microalgae corresponded to the nitrate reductase activity, with slower consumption in the early stage and no obvious difference from the control group in the later stage. Overall, the diversity of environmental bacteria did not undergo significant changes, but the abundance of some specific bacteria increased, such as nitrogen-fixing bacteria (unclassified-f-Rhizobiaceae and Mesorhizobium) and organic contaminant-degrading bacteria (Limnobacter, Sphingopyxis, and Aquimonas). The 0.25 and 1 mg/L ROX treatments significantly enhanced the carbohydrate metabolism, cofactor and vitamin metabolism, amino acid metabolism, and energy metabolism of the environmental bacteria, but significantly downregulated nitrogen denitrification. This study provides new insights into the environmental bacteria-driven recovery mechanism of microalgae under antibiotic stress. Full article

Many companies engage in earnings manipulation that obscures their actual financial condition and sustainability efforts, undermining the credibility of financial reports and eroding stakeholder trust. To address these concerns, the United Kingdom has strictly adhered to International Financial Reporting Standards (IFRS), enhancing financial transparency and reducing the risk of manipulation. This study applies agency theory to examine the effects of earnings management and IFRS adoption on corporate sustainability performance, while also assessing the moderating roles of institutional ownership and board independence. Data were drawn from 248 companies listed on the London Stock Exchange between 2002 and 2024, using purposive sampling and sourced from Thomson Reuters Eikon DataStream. Advanced estimation techniques, specifically the Augmented Mean Group (AMG) and fixed effects models with Driscoll-Kraay standard errors, were employed to address cross-sectional dependence and slope heterogeneity. The results indicate that earnings management, as measured by discretionary accruals, has a significant negative impact on sustainability performance. In contrast, the adoption of IFRS has a positive and significant influence on sustainability outcomes. Additionally, institutional ownership and board independence significantly moderate the adverse effects of earnings management, leading to improved sustainability performance. The findings suggest that managers should enhance the clarity and accountability of financial reporting by implementing robust internal systems aligned with IFRS, conducting regular compliance audits, and training finance staff on current disclosure standards. Full article

This article introduces new sufficient conditions ensuring the interior approximate controllability of semilinear thermoelastic plate equations subject to Dirichlet boundary conditions. The analysis is carried out by reformulating the system as an abstract evolution equation on a suitable Banach space. A key role is played by the compactness of the semigroup generated by the linear operator, which allows us to treat the nonlinear components effectively. To establish controllability, we apply Rothe’s fixed-point theorem, which provides the necessary framework for handling nonlinear perturbations. The results obtained contribute to the existing literature, since the controllability of the specific semilinear thermoelastic system considered here has not been previously investigated. Full article

This study investigates how energy consumption and foreign direct investment (FDI) influenced economic growth in BRICS+ countries from 1990 to 2021, using a two-step System GMM estimator to address endogeneity and dynamic effects. While the results show that both energy and FDI positively affected growth, disaggregated analysis revealed that renewable energy promoted growth, whereas non-renewables hindered it. Similarly, FDI directed toward gross fixed capital formation (FDI_GFCF) consistently boosted growth, unlike aggregate FDI. Financial development moderated these effects, amplifying the benefits of energy use but dampening FDI’s growth impact in more developed financial systems. The effects of energy and FDI remained stable before and after the Paris Agreement, supporting the robustness of the findings. These results underscore the importance of tailored energy and FDI strategies, financial sector reforms, and supportive policy environments to advance sustainable growth in BRICS+ economies. Full article

In China, most of the ancient wooden structure mortise and tenon buildings, under the long-term upper load, have columns with surface surfaces that have varying degrees of damage, which need to be repaired and strengthened urgently, but the theory related to CFRP, mortise size, and pre-damage simulation still needs to be deeply studied. To investigate the effects of CFRP reinforcement layers, cross-sectional area of concealed tenons as the projected area after installation, and tenon engagement length as the axial length after installation on the axial compressive mechanical properties of pre-damaged quad-segment spliced Pinus sylvestris var. mongolia composited wooden columns, axial compression failure tests were conducted on 10 specimens following pre-damage simulation and CFRP strengthening. The experimental program yielded comprehensive data, including observations, mechanical analyses, load-displacement curves, load-strain curves, ultimate load-bearing capacities, ductility coefficients, and stiffness values. The results demonstrate that with consistent tenon cross-sectional area and engagement length, increasing CFRP layers from 1 to 3 raises the ultimate bearing capacity from 472.3 kN to 620.3 kN and improves the ductility coefficient from 4.67 to 7.95, clearly indicating that CFRP reinforcement significantly enhances axial compressive performance while effectively mitigating brittle failure. When maintaining constant CFRP layers and tenon cross-sectional area, extending the tenon engagement length from 30 mm to 90 mm elevates the bearing capacity from 494.95 kN to 546.3 kN and boosts the ductility coefficient from 5.58 to 7.95. In contrast, with fixed CFRP layers and engagement length, expanding the tenon cross-sectional area from 360 mm² to 810 mm² produces only marginal bearing capacity improvement from 548.2 kN to 556.2 kN with ductility coefficients ranging between 4.67 and 5.56, conclusively revealing that tenon engagement length has substantially greater influence on mechanical properties than cross-sectional area. The optimal axial compressive performance configuration combines 3 CFRP layers, an 810 mm² tenon cross-section, and a 90 mm engagement length. Full article