Search Results (118)

Background: In recent decades, dermatological diagnostics have undergone a profound transformation, driven by the integration of new technologies alongside traditional methods. Classic techniques such as the Tzanck smear, potassium hydroxide (KOH) preparation, and Wood’s lamp examination remain fundamental in everyday clinical practice due to their simplicity, speed, and accessibility. At the same time, the development of non-invasive imaging technologies and the application of artificial intelligence (AI) have opened new frontiers in the early detection and monitoring of both neoplastic and inflammatory skin diseases. Methods: This review aims to provide a comprehensive overview of how conventional and emerging diagnostic tools can be integrated into dermatologic practice. Results: We examined a broad spectrum of diagnostic methods currently used in dermatology, ranging from traditional techniques to advanced approaches such as digital dermoscopy, reflectance confocal microscopy (RCM), optical coherence tomography (OCT), line-field confocal OCT (LC-OCT), 3D total body imaging systems with AI integration, mobile applications, electrical impedance spectroscopy (EIS), and multispectral imaging. Each method is discussed in terms of diagnostic accuracy, clinical applications, and potential limitations. While traditional methods continue to play a crucial role—especially in resource-limited settings or for immediate bedside decision-making—modern tools significantly enhance diagnostic precision. Dermoscopy and its digital evolution have improved the accuracy of melanoma and basal cell carcinoma detection. RCM and LC-OCT allow near-histological visualization of skin structures, reducing the need for invasive procedures. AI-powered platforms support lesion tracking and risk stratification, though their routine implementation requires further clinical validation and regulatory oversight. Tools like EIS and multispectral imaging may offer additional value in diagnostically challenging cases. An effective diagnostic approach in dermatology should rely on a thoughtful combination of methods, selected based on clinical suspicion and guided by Bayesian reasoning. Conclusions: Rather than replacing traditional tools, advanced technologies should complement them—optimizing diagnostic accuracy, improving patient outcomes, and supporting more individualized, evidence-based care. Full article

Background: Mucopolysaccharidoses (MPSs) are rare lysosomal storage disorders characterized by multisystem involvement; notably, skeletal abnormalities known as dysostosis multiplex and varying degrees of central nervous system impairment. Accurate radiological evaluation is crucial for accurate diagnosis and effective planning. This study aims to describe the clinical and radiological features of patients with MPS managed at our tertiary care center. Methods: We retrospectively reviewed clinical and radiological data from eight patients with confirmed MPS treated at S. Orsola University Hospital (Bologna, Italy) since 2000. Imaging included conventional radiography, supplemented by MRI and CT. The findings were analyzed by MPS subtype and correlated with clinical evolution and therapeutic interventions. A literature review complemented the analysis. Results: The cohort included one patient with MPS I, two with MPS II, one with MPS III, and four with MPS IV. Common skeletal findings were vertebral deformities, hip dysplasia, and shortening of long bones. Patients with MPS IV showed the most severe bone involvement, including pronounced platyspondyly and odontoid hypoplasia. Follow-up imaging demonstrated progression of bone and CNS pathology despite enzyme replacement therapy (ERT). Conclusions: Our findings underscore the pivotal role of imaging in MPS management. Tailored radiological protocols and multidisciplinary care are crucial for optimizing diagnosis and monitoring disease progression. Full article

The Earth’s Radiation Budget (ERB) is a critical component for understanding the planet’s climate system, as it governs the balance between incoming solar energy and outgoing thermal radiation. Accurate monitoring of the ERB, combined with Ocean Heat Content (OHC) measurements, is essential to assess Earth’s Energy Imbalance (EEI) and its implications for global warming. This paper presents new results on the ERB based on data from the Uvsq-Sat and Inspire-Sat nanosatellite missions, which operated from 2021 to 2024. These satellites constitute the first European constellation demonstrator designed for broadband, Wide Field-Of-View (WFOV) measurements of the ERB. While WFOV instruments provide enhanced temporal and spatial coverage, they do not replace the need for Narrow Field-Of-View (NFOV) measurements, such as those provided by the established Clouds and the Earth’s Radiant Energy System (CERES) instruments. Instead, they are designed to complement them. By using data from both the WFOV constellation and CERES instruments to measure Reflected Solar Radiation (RSR) and Outgoing Longwave Radiation (OLR), we estimate the EEI and monitor its evolution. Our analysis reveals a generally good agreement between Uvsq-Sat and CERES data for EEI from 2021 through the end of 2024. Over this period, EEI derived from Uvsq-Sat averaged +0.87 ± 0.23 ${\mathrm{Wm}}^{-2}$, closely matching the recent CERES trend. Both datasets indicate a peak in EEI in mid-2023, followed by a decline throughout 2024, likely reflecting stabilizing feedbacks triggered by the 2023 El Niño event. Importantly, this short-term decline occurred within a sustained upward trend in EEI since 2013, as shown by CERES observations, with solar activity having a negligible impact. Comparisons with OHC measurements confirm ongoing ocean heat accumulation, consistent with the rising decadal trend in EEI. These insights underscore the importance of continuous, high-frequency observations to capture the complex and rapidly evolving processes influencing Earth’s energy balance. Demonstrations using nanosatellites at different local times illustrate the advantages of small satellite constellations for improved monitoring frequency and coverage, particularly for variables that change over short time scales, such as RSR, also known as Outgoing Shortwave Radiation (OSR). Full article

The sustainable development of higher education exhibits a strong and measurable association with the level of regional innovation capacity. Drawing on panel data covering 31 provincial-level administrative regions in China from 2010 to 2022, we construct evaluation frameworks for both higher education and regional innovation capacity using the entropy weight method. These are complemented by kernel density estimation, spatial autocorrelation analysis, Dagum Gini coefficient decomposition, and the Obstacle Degree Model. Together, these tools enable a comprehensive investigation into the spatiotemporal evolution and driving mechanisms of coupling coordination dynamics between the two systems. The results indicate the following: (1) Both higher education and regional innovation capacity indices exhibit steady growth, accompanied by a clear temporal gradient differentiation. (2) The coupling coordination degree shows an overall upward trend, with significant inter-regional disparities, notably “higher in the east and low in the west”. (3) The spatial distribution of the coupling coordination degree reveals positive spatial autocorrelation, with provinces exhibiting similar levels tending to form spatial clusters, most commonly of the low–low or high–high type. (4) The spatial heterogeneity is pronounced, with inter-regional differences driving overall imbalance. (5) Key obstacles hindering regional innovation include inadequate R&D investment, limited trade openness, and weak technological development. In higher education sectors, limitations stem from insufficient social service benefits and efficiency of flow. This study recommends promoting the synchronized advancement of higher education and regional innovation through region-specific development strategies, strengthening institutional infrastructure, and accurately identifying and addressing key barriers. These efforts are essential to fostering high-quality, coordinated regional development. Full article

This study investigates the convergence of blockchain, artificial intelligence (AI), near-field communication (NFC), and mobile technologies in electronic payment (e-payment) systems, proposing an innovative integrative framework to deconstruct the systemic innovations and transformative impacts driven by such technological synergy. Unlike prior research, which often focuses on single-technology adoption, this study uniquely adopts a cross-technology convergence perspective. To our knowledge, this is the first study to empirically map the multi-technology convergence landscape in e-payment using scientometric techniques. By employing bibliometric and thematic network analysis methods, the research maps the intellectual evolution and key research themes of technology convergence in e-payment systems. Findings reveal that while the integration of these technologies holds significant promise, improving transparency, scalability, and responsiveness, it also presents challenges, including interoperability barriers, privacy concerns, and regulatory complexity. Furthermore, this study highlights the potential for convergent technologies to unintentionally deepen the digital divide if not inclusively designed. The novelty of this study is threefold: (1) theoretical contribution—this study expands existing frameworks of technology adoption and digital governance by introducing an integrated perspective on cross-technology adoption and regulatory responsiveness; (2) practical relevance—it offers actionable, stakeholder-specific recommendations for policymakers, financial institutions, developers, and end-users; (3) methodological innovation—it leverages scientometric and topic modeling techniques to capture the macro-level trajectory of technology convergence, complementing traditional qualitative insights. In conclusion, this study advances the theoretical foundations of digital finance and provides forward-looking policy and managerial implications, paving the way for a more secure, inclusive, and innovation-driven digital payment ecosystem. Full article

This study investigates the evolutionary game dynamics of medical knowledge sharing (KS) among Chinese hospitals under government regulation, focusing on the strategic interactions between general hospitals, community health service centers, and governmental bodies. Leveraging evolutionary game theory, we construct a tripartite evolutionary game model incorporating replicator dynamics to characterize the strategic evolution of the involved parties. Our analysis examines the regulatory decisions of the government and the strategic choices of Chinese hospitals, considering critical factors such as KS costs, synergistic benefits, government incentives and penalties, and patient evaluations. The model is analyzed using replicator dynamic equations to derive evolutionary stable strategies (ESSs), complemented by numerical simulations for sensitivity analysis. Key findings reveal that the system’s equilibrium depends on the balance between KS benefits and costs, with government regulation and patient evaluations significantly influencing Chinese hospital behaviors. The results highlight that increasing government incentives and penalties, alongside enhancing patient feedback mechanisms, can effectively promote KS. However, excessive incentives may reduce willingness to regulate, suggesting the need for balanced policy design. This research provides novel theoretical insights and practical recommendations by (1) pioneering the application of a tripartite evolutionary game framework to model KS dynamics in China’s hierarchical healthcare system under government oversight, (2) explicitly integrating the dual influences of government regulation and patient evaluations on hospital strategies, and (3) revealing the non-linear effects of policy instruments. These contributions are crucial for optimizing Chinese medical resource allocation and fostering sustainable collaborative healthcare ecosystems. Full article

Chinese lacquer, a historically significant bio-based coating, has garnered increasing attention in sustainable materials research due to its outstanding corrosion resistance, thermal stability, and environmental friendliness. Its curing process relies on the laccase-catalyzed oxidation and polymerization of urushiol to form a dense lacquer film. However, the stringent temperature and humidity requirements (20–30 °C, 70–80% humidity) and a curing period that can extend over several weeks severely constrain its industrial application. Recent studies have significantly enhanced the curing efficiency through strategies such as pre-polymerization control, metal ion catalysis (e.g., Cu²⁺ reducing drying time to just one day), and nanomaterial modification (e.g., nano-Al₂O₃ increasing film hardness to 6H). Nevertheless, challenges remain, including the sensitivity of laccase activity to environmental fluctuations, the trade-off between accelerated curing and film performance, and issues related to toxic pigments and VOC emissions. Future developments should integrate enzyme engineering (e.g., directed evolution to broaden laccase tolerance), intelligent catalytic systems (e.g., photo-enzyme synergy), and green technologies (e.g., UV curing), complemented by multiscale modeling and circular design strategies, to drive the innovative applications of Chinese lacquer in high-end fields such as aerospace sealing and cultural heritage preservation. Full article

Organic soil pollution poses a persistent threat to environmental sustainability by disrupting nutrient cycling and ecosystem functioning. The biochar-activated persulfate (PS)-based advanced oxidation process (AOP) has emerged as a promising strategy for the sustainable remediation of organic-contaminated soils. This review provides a comprehensive overview of the recent progress in the PS-based degradation of organic pollutants, with a particular focus on the role of biochar as an efficient and environmental activator. This review further summarizes advancements in the design of modified biochars, including metal (Fe, Cu, Co, Mn, Zn, and La), non-metal (N, S, B, P), and functional group modifications, aimed at enhancing the PS activation efficiency while minimizing secondary environmental risks. Importantly, the overlooked contributions of soil microorganisms in PS/biochar systems are discussed, highlighting their potential to complement chemical oxidation and contribute to eco-compatible remediation pathways. This review emphasizes the sustainability-oriented evolution of PS/biochar technology, highlighting the importance of a cost-efficient implementation, ecological compatibility, and the rational engineering of smart, regenerable catalysts. These insights support the advancement of PS/biochar-based AOPs toward scalable, intelligent, and environmentally sustainable soil remediation. Full article

Wastewater surveillance has proven to be a cost-effective, non-invasive method for monitoring the spread and evolution of SARS-CoV-2, yet its value during today’s low-incidence phase is still being defined. Between August 2023 and July 2024, 42 composite wastewater samples were collected in Perugia, Italy and analyzed using RT-qPCR and whole-genome sequencing to identify circulating SARS-CoV-2 lineages. In parallel, clinical samples (respiratory tract samples) were collected and analyzed, allowing for direct comparisons to confirm the robustness of the wastewater findings. The sewage viral loads ranged from 8.9 × 10⁵ to 4.9 × 10⁷ genome copies inhabitant⁻¹ day⁻¹, outlining two modest community waves (September–December 2023 and May–July 2024). Sequencing resolved 403 Omicron lineages and revealed three successive subvariant phases: (i) XBB.* dominance (August–October 2023), when late-Omicron XBB subvariants (mainly EG.5.* and XBB.1.5) accounted for almost all genomes; (ii) a BA.2.86/JN surge (November 2023–March 2024), during which the BA.2.86 subvariant, driven mainly by its JN descendants (especially JN.1), rapidly displaced XBB.* and peaked at 89% in February 2024; and (iii) KP.* takeover (April–July 2024), with JN.1-derived KP subvariants rising steadily and KP.3 reaching 81% by July 2024, thereby becoming the dominant lineage. Comparisons of data from wastewater and clinical surveillance demonstrated how the former presented a much higher diversity of circulating viral lineages. Importantly, some subvariants (including BA.2.86*) were detected in wastewater weeks to months prior to clinical identification, and for longer periods. Taken together, the obtained data validated wastewater surveillance as an effective early warning system, especially during periods of low infection prevalence and/or limited molecular testing efforts. This methodology can thus complement clinical surveillance by offering valuable insights into viral dynamics at the community level and enhancing pandemic preparedness. Full article

To advance the optimization of engineering parameters in in-seam borehole predrainage technology, this study developed a comprehensive analytical framework integrating theoretical modeling, numerical simulation, and field validation. Taking Pingdingshan Tian’an Coal Mine No. 1 as a practical case study, we established a gas-bearing coal seam drainage model based on fluid–solid coupling theory. A multifactor optimization scheme was implemented using response surface methodology (RSM) complemented by an evaluation system focusing on the gas extraction efficiency coefficient (K). Numerical simulations through COMSOL Multiphysics 6.0 enabled detailed investigation of single-factor influences and multifactor coupling effects, ultimately identifying field-verified optimal parameters. Key discoveries include the following: (1) Spatiotemporal evolution patterns of gas drainage compliance zones showing stabilized interborehole pressure gradients and enhanced regional connectivity after 300-day extraction; (2) a parameter sensitivity hierarchy for K-value defined as drainage duration (primary) > borehole spacing > borehole diameter > extraction negative pressure; (3) an optimized configuration (4.5 m spacing, 113 mm diameter, 18 kPa pressure) achieving a 54.2% pressure reduction with a 0.98 efficiency coefficient. Field data demonstrated only 2.1% average deviation from model predictions, validating the methodology’s effectiveness for gas control parameter optimization in coal mining operations. Full article

Most bioplastics are based on polysaccharides, which are either synthesized from a variously sourced monomer or extracted from some biomass waste. In many cases, some lignocellulosic fibers are then added to the obtained bioplastics to form biocomposites and extend their range of applications beyond packaging films and generically easily biodegradable materials. Plant-extracted tannins, which, as such, might also be building blocks for bioplastics, do nonetheless represent a useful complement in their production when added to polysaccharide-based plastics and biocomposites, since they offer other functions, such as bioadhesion, coloration, and biocidal effect. The variety of species used for tannin extraction and condensation is becoming very wide and is also connected with the local availability of amounts of bio-waste from other productions, such as from the food system. This work tries to summarize the evolution and recent developments in tannin extraction and their increasing centrality in the production of polysaccharide-based plastics, adhesives, and natural fiber composites. Full article

Background: Mapping the local etiology and susceptibility of common pathogens causing complicated urinary tract infection (cUTI) is important for promoting evidence-based antimicrobial prescribing. Evaluating the prevalence of extended-spectrum beta-lactamase (ESBL), AmpC beta-lactamase (AmpC), and carbapenemase-producing Enterobacterales (CPEs) is equally important as it informs treatment guidelines and empiric management. Whole genome sequencing (WGS) enhances antimicrobial resistance (AMR) surveillance by complementing phenotypic antimicrobial susceptibility testing, offering deeper insights into resistance mechanisms, transmissions, and evolutions. Integrating it into routine AMR monitoring can significantly improve global efforts to combat antimicrobial resistance. Methods: Antimicrobial susceptibility profiles of isolates from cUTI were collected from patients presenting with Sultan Qaboos University Hospital, Muscat and Suhar Hospital, Suhar, Oman. Automated systems as well as manual methods were used for detection of ESBL, AmpC, and CPE. ESBLs, AmpC β-lactamases, and CPEs were further detected by manual methods: double-disk synergy test for ESBL; disk approximation assay and D69C AmpC detection set for AmpC, and mCIM and KPC/IMP/NDM/VIM/OXA-48 Combo test kit for CPE. WGS was carried out in 11 FOX-resistant E. coli and (22 carbapenem-resistant K. pneumoniae) isolates with varying susceptibilities to identify circulating clades, AMR genes, and plasmids. Bioinformatic analysis was performed using online tools. Results: The susceptibility patterns of E. coli from cUTI were as follows: nitrofurantoin (96%), fosfomycin (100%), fluoroquinolones (44%), aminoglycosides (93%), piperacillin-tazobactam (95%), and carbapenems (98%). In comparison, susceptibility rates of K. pneumoniae were far lower: nitrofurantoin (38%), fosfomycin (89%), aminoglycosides (82%), piperacillin-tazobactam (72%), and carbapenems (83%). K. pneumoniae, however, was more susceptible to fluoroquinolones at 47% in comparison to E. coli. The prevalence of ESBL among E. coli and K. pneumoniae was 37.2% and CRE was 6.2% while the estimated prevalence of AmpC was 5.4%. It was observed that E. coli was the predominant ESBL and AmpC producer, while K. pneumoniae was the major carbapenem-resistant Enterobacterales (CREs) producer. No predominant multi-locus sequence typing (MLST) lineage was observed in AmpC-producing E. coli with nine E. coli MLST lineages being identified from eleven isolates: ST-10, ST-69, ST-77, ST-131, ST-156, ST-167, ST-361, ST-1125, and ST-2520. On the other hand, a less diverse MLST spectrum (ST-2096, ST-231, ST-147, ST-1770, and ST-111) was observed in the CRE K. pneumoniae. Among the five MLST lineages, ST-2096 (twelve isolates) and ST-147 (seven isolates) predominated. WGS revealed that DHA-1 was the predominant plasmid-mediated AmpC gene in E. coli, while OXA-232 and NDM-5 were the most common carbapenemase genes in K. pneumoniae. All E. coli DHA-1-positive isolates co-harbored the quinolone resistance gene qnrB4 and the sulfonamide resistance gene sul1 while no aminoglycoside resistance genes were detected. The majority of CPE CRE K. pneumoniae carried other β-lactamase genes, such as blaCTX-M-15, blaSHV, and blaTEM; all co-harbored the quinolone resistance gene OqxAB; and 77% carried the aminoglycoside resistance gene armA. Conclusions: Our results suggest that fosfomycin is an excellent empiric choice for treating complicated cystitis caused by both E. coli and K. pneumoniae, while nitrofurantoin is an appropriate choice for E. coli cystitis but not for K. pneumoniae. Aminoglycosides and piperacillin-tazobactam are excellent intravenous alternatives that spare carbapenems. DHA-1 was the predominant AmpC in E. coli, while OXA-232 and NDM-5 were the predominant carbapenemases in K. pneumoniae. In AmpC-producing E. coli, no MLST predominated, suggesting a significant flux in E. coli with lack of stable clades in this region. In contrast, ST-2096 and ST-147 predominated in CRE Klebsiella pneumoniae, suggesting a stable circulation of these in Oman. WGS profiling provides a deeper understanding of the genetic basis of resistance and enhances surveillance and offers comprehensive insights into pathogen evolution and transmission patterns. Full article

The synergistic dilemma of upstream actors in the agro-ecological product supply chain restricts the transformation of ecological value, and traditional research focuses on the “production-supply” dichotomy, neglecting the driving role of the innovation service system. This study innovatively proposes a theoretical framework of “industry-supply-innovation tri-system synergy”, constructs a dynamic evolutionary game model with “free-riding” behavior, quantifies the effects of synergistic cost sharing coefficients (θ), benefit distribution ratios (γ), and policy regulation variables on the evolution of the main body’s strategy, and reveals the key laws through Matlab simulation. The results show that: (1) the participation of an innovation service system can significantly improve the speed of cooperation convergence; (2) the initial willingness to cooperate and the fairness of benefit distribution dominate the evolution path, and the probability of the system converging to “active cooperation” increases significantly when θ > 0.5; (3) the policy needs to be complemented with the market, and the government optimizes the distribution of the benefits of innovation services to improve the efficiency of the supply chain. The government can optimize the distribution of benefits from innovation services to promote the efficiency of the supply chain. Accordingly, we propose a “market-policy” dual-wheel control strategy to promote the deep integration of multiple supply chain actors with the innovation service system as a link. Full article

Addressing the critical seismic vulnerabilities of reinforced concrete (RC) beam-column joints remains an imperative research priority in earthquake engineering. This study presents an experimental and analytical investigation into the seismic performance enhancement of non-ductile RC frames using an innovative all-steel Tube-in-Tube Buckling-Restrained Brace (TnT BRB) system. Shake table tests were performed on one-third scale RC frame specimens, including a baseline structure representing conventional substandard design and a counterpart retrofitted with the proposed TnT BRBs. Experimental results revealed that the unretrofitted specimen experienced pronounced brittle shear failures, excessive lateral deformations, and significant degradation of beam-column joints under cyclic seismic loading. In contrast, the TnT BRB-retrofitted specimen exhibited substantially improved seismic behavior, characterized by enhanced energy dissipation, controlled inter-story drifts, and preserved joint integrity. Advanced fiber-based finite element modeling complemented the experimental efforts, accurately capturing critical nonlinear phenomena such as hysteretic energy dissipation, stiffness degradation, and localized damage evolution within the structural components. Despite inherent modeling limitations regarding bond-slip effects and micro-level cracking, strong correlation between numerical and experimental results affirmed the efficacy of the TnT BRB retrofit solution. This integrated experimental-analytical approach offers a robust, cost-effective pathway for upgrading seismically deficient RC structures in earthquake-prone regions. Full article

This paper provides a detailed review of the evolution and development of corrugated wings, a biomimetic concept that is very effective under low Reynolds number flights. We will highlight, through reviewing experimental and numerical studies, the emphasis on its aerodynamic performance for lift enhancement, flow separation delay, and drag reduction in the aerodynamics of corrugated wings. Furthermore, we focus on topics such as fluid–structure interaction and aeroacoustics, presenting the possibility of morphing wing technologies in tandem and its effects on an angle of attack at various flight modes. This review outlines durability issues, materials selection, and experimental testing complemented by numerical models while determining the importance of interdisciplinary developments within corrugated wing aerodynamics using potential AI-assisted design. Our review envisions the application of aerodynamics of corrugated wings in the development of UAVs, MAVs, and future advanced aviation systems by integrating the principles from biology to engineering. Full article