Search Results (35,210)

The formation and size evolution of gas-phase nanoparticles (NPs) in laser ablation inductively coupled plasma mass spectrometry critically influence aerosol transport, plasma ionization efficiency, and ultimately analytical accuracy. Nevertheless, burst-mode laser ablation, as an efficient and versatile strategy for controlling gas-phase NP size, remains insufficiently explored. Here, we combine experimental investigations and theoretical analysis to elucidate the mechanisms of gas-phase nanoparticle formation and size control by tuning the interpulse interval in burst-mode femtosecond (fs) laser ablation. The mean nanoparticle size exhibits a non-monotonic dependence on interpulse spacing, decreasing with a narrowing size distribution as the interval increases from 0 to 300 ps, and then increasing with distribution broadening at longer delays up to 1000 ps, closely correlating with ablation-crater depth. A characteristic transition at ~300 ps is identified, where both nanoparticle size and crater depth reach a minimum, revealing a critical timescale in pulse–plume–surface interactions. Simulations show that the interpulse interval governs the redistribution of laser energy between the surface and plume, driving a transition from surface-dominated ablation to plume-dominated absorption and partial recovery of surface coupling. This delay-dependent framework provides a unified explanation for nanoparticle formation, where particle size is determined by the competition between plume-mediated fragmentation and surface-driven material supply, and offers a basis for tailoring NP size distributions via temporal pulse shaping. Full article

Rheumatoid arthritis (RA) has traditionally been managed after the onset of clinically apparent synovitis; however, accumulating evidence indicates that disease-related immune abnormalities precede clinical diagnosis by several years. This preclinical phase is characterized by systemic autoimmunity, early musculoskeletal symptoms, and subclinical inflammation in genetically and environmentally susceptible individuals. In this review, we summarize current concepts regarding the pathogenesis, risk stratification, and therapeutic interception of preclinical RA. Particular attention is given to the mucosal origin hypothesis and to the roles of immunosenescence, peripheral helper T cells, and fibroblast-like synoviocytes in early disease evolution. Recent advances in clinical, serological, and imaging-based risk stratification have improved the identification of individuals at high risk of progression to clinical RA, and emerging intervention trials have shown that selected therapies may delay disease onset or reduce early inflammatory burden. Although complete prevention of RA has not yet been achieved, these findings support a paradigm shift from the treatment of established RA toward earlier, risk-adapted intervention before irreversible joint damage occurs. Future efforts should focus on refining predictive biomarkers, optimizing the timing and intensity of intervention, and establishing safe, individualized preventive strategies. Full article

Accurate diagnosis of PM and precise histologic subtyping are critical for optimal therapeutic decision-making, as treatment strategies—including chemotherapy, immunotherapy, or multimodality approaches—are largely subtype-dependent. Because of the several-decade latency between fiber inhalation and symptom onset, many cases are diagnosed at an advanced stage, when patients are already in poor clinical condition. As observed across multiple solid malignancies, earlier-stage diagnosis is associated with improved prognosis and expanded therapeutic options. However, the rarity of PM, the absence of validated screening strategies, and its nonspecific clinical and radiologic presentation—often mimicking both benign and metastatic pleural conditions, frequently result in diagnostic delay. Furthermore, the lack of pathognomonic histopathologic markers further complicates timely and definitive diagnosis. This review aims to delineate the epidemiologic, clinical, radiologic, and pathologic barriers that hinder accurate and early detection of PM. Current clinical evidence points to an urgent need to develop novel, validated biomarkers in PM, which will require a multidisciplinary approach. Full article

The WW domain-containing oxidoreductase (WWOX) gene, well-known as a tumor suppressor, also has a crucial role as a transcription factor in the developing brain. The bi-allelic loss of the WWOX gene causes a condition characterized by drug-resistant epilepsy, developmental delay, and neurological impairments, often resulting in mortality within the first year of life, known as WWOX-related epileptic encephalopathy (WOREE) syndrome (MIM: 616211). Whole Exome Sequencing (WES) analysis was performed on a female patient who died within three months of birth and was diagnosed with microcephaly, severe early-onset refractory seizures, and drug-resistant epileptic encephalopathy. WES revealed a 38 kb CNV deletion spanning WWOX exons 6–7, and a known frameshift variant in exon 8, impairing a highly clinically significant region of the encoded protein. Clinical and genetic features of reported WOREE patients with WWOX gene deletions similar to our patient were analyzed. Our case highlights the clinical heterogeneity of WWOX variants in WOREE syndrome and expands the spectrum of reported compound heterozygous deletions. Further research needs to elucidate WWOX pathophysiology and improve diagnostic and therapeutic strategies. Full article

The digital preservation and dissemination of historical and cultural heritage is a pivotal area at the intersection of digital humanities and geographic information science. To address the challenges of multi-source heterogeneity, limited dimensionality, and inadequate public engagement, this study designed and implemented an interactive visualization platform using modern Web technologies. Taking the Leshan Confucian Temple (religious heritage) and the former site of Wuhan University (educational heritage) as case studies, the platform integrates four types of heterogeneous data (geospatial coordinates, architectural attributes, visitor behavioral records, and multimedia imagery) into a unified spatiotemporal information model. Core technical implementations are built upon a lightweight front-end stack including the Gaode Map JavaScript API for geographic visualization, ECharts for dynamic statistical charting, and the Tailwind CSS framework for a fully responsive front-end interface. Key interactive features encompass linked map markers with contextual information windows, user-driven chart filtering, and paginated loading of cultural relic cards. Evaluation results demonstrate that the platform achieves cross-device response delay ≤3 s, supports spatially grounded, dynamic, and presentation of cultural heritage information, and attains a System Usability Scale (SUS) score of 82.5. This work offers a lightweight, scalable technical solution for advancing digital recording and public communication of historical and cultural heritage, while contributing to the theoretical discourse on spatial narrative and multi-source data integration in digital humanities. Full article

Despite the availability of clinical guidelines aimed at managing pregnancy complications, maternal deaths related to obstetric emergencies remain unacceptably high in South Africa, especially in rural provinces like Limpopo. These preventable deaths are often linked to delayed response to complications, poor adherence to protocols, and lack of essential resources. The study aimed to explore the experiences of health professionals regarding the implementation of maternal guidelines used to manage obstetric emergencies. The study adopted a qualitative, descriptive, and explorative design. Data were analysed thematically, and trustworthiness was maintained throughout the research process. Sixteen participants from four selected hospitals in a rural area of South Africa (Vhembe District, Limpopo Province) were purposively sampled and interviewed using semi-structured interviews; data were analysed thematically. The findings highlighted multiple critical barriers to guideline implementation, including shortages of printed clinical protocols, inconsistent patient follow-up, poor referral systems, infrastructure deficits, medication stock-outs, and negative staff attitudes. Most doctors and midwives working in maternity units lacked training on the Essential Steps in the Management of Obstetric Emergencies (ESMOE), resulting in insufficient knowledge and skills to manage obstetric emergencies. Therefore, there is an urgent need for comprehensive ESMOE training for all doctors and midwives in maternity units. Full article

Background/Objectives: Traumatic spine injury is a major cause of morbidity and mortality in low- and middle-income countries, yet detailed epidemiologic data from sub-Saharan Africa remain limited. We used a fracture registry to characterize injury patterns, care pathways, and short-term outcomes among patients presenting with traumatic spine injury at a tertiary referral center in Ethiopia. Methods: We performed a retrospective analysis of a prospectively maintained fracture registry at a tertiary referral hospital in Ethiopia from June 2023 to July 2025. Patients with traumatic spine injury were included. Variables included demographics, injury mechanism and context, injury region, AO morphology, neurologic status (ASIA), referral status, mode of transportation, time to presentation, treatment, and 30-day outcomes. Descriptive statistics were used to summarize the cohort. Bivariate associations were assessed using chi-square or Fisher’s exact tests, and crude odds ratios were calculated for prespecified 2 × 2 comparisons. Results: A total of 252 patients were included (mean age: 33.1 ± 13.6 years; 81.3% male). Falls (45.2%) and road traffic accidents (26.2%) were the most common mechanisms, and injuries most often occurred on farms (40.1%) and roads/streets (33.7%). The thoracolumbar (31.3%) and cervical (30.6%) regions were most frequently affected. Complete spinal cord injury (ASIA A) occurred in 36.5% of patients. Most patients were referred (88.5%), 62.7% presented >24 h after injury, and 65.5% were managed non-operatively. Referral status was strongly associated with delayed presentation (OR: 10.49, 95% CI: 3.84–28.64). Thirty-day mortality was 22.2%. Complete SCI (OR: 6.17, 95% CI: 3.23–11.90) and cervical/thoracic injuries (OR: 6.54, 95% CI: 3.12–13.70) were associated with higher mortality. Conclusions: Traumatic spine injury in this Ethiopian cohort disproportionately affected young adults and was marked by severe neurologic injury, delayed presentation, and high early mortality. Full article

Accurately forecasting the weighted mean temperature (Tm) is critical for converting the zenith wet delay (ZWD) into global navigation satellite system (GNSS)-based precipitable water vapor (PWV) for real-time sensing and forecasting applications. The forecast Vienna Mapping Function 1 (VMF1-FC) is a global forecast product developed by TU Wien based on numerical weather prediction models and can provide grid-wise Tm one day ahead. In this study, we evaluate the accuracy of VMF1-FC-forecasted Tm using observations from 319 global radiosonde (RS) sites during 2019–2021. The results indicate that VMF1-FC-forecasted Tm shows a relatively low RMSE but a relatively large bias (0.75 K) relative to the widely used Global Pressure and Temperature 3 (GPT3) model. To improve the accuracy of VMF1-FC-forecasted Tm, three refined models, XTm, LTm, and CTm, are developed using Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost), respectively, based on observations from 319 RS sites. The models use longitude, latitude, ellipsoidal height, floating day of year (fdoy), and VMF1-FC Tm as input features, and RS Tm as the target variable. Validation using RS data from 2022 that are not involved in model development shows that the refined models significantly reduce bias, with biases of 0 K, 0 K, and −0.03 K for XTm, LTm, and CTm, respectively. Benefiting from the effective reduction in bias, the root mean square error (RMSE) is correspondingly reduced. The RMSEs of XTm, LTm, and CTm are 1.45 K, 1.45 K, and 1.46 K, respectively, achieving improvements of 18.50%/64.93%, 18.44%/64.91%, and 18.11%/64.76% compared with the VMF1-FC and GPT3 models. In addition, three refined models demonstrate higher accuracy and improve stability across different latitude bands, ellipsoidal height ranges, and temporal scales. The refined models provide more accurate global-scale Tm and offer strong potential for GNSS meteorological applications, particularly real-time GNSS-based PWV sensing and weather forecasting. Full article

Sea ice classification is of fundamental importance for polar monitoring and global climate research. Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a frontier technology in polar remote sensing due to its high spatiotemporal resolution and cost-effectiveness. Based on BeiDou System Reflectometry (BDS-R) data acquired from the Fengyun-3E (FY-3E) satellite, this study introduces a classification approach that integrates multi-dimensional sea ice information. A comprehensive feature set was constructed by integrating the Spectral Entropy (SE) of the Normalized Integrated Delay Waveform (NIDW) First-order Differential Curve to characterize the oscillatory complexity of the trailing edge power decay process as a scattering dynamic property, the Root Mean Square height (RMS) to characterize the attenuation magnitude of scattering intensity arising from surface roughness and related factors as a scattering intensity attenuation property, and salinity (S) and L-band brightness temperature (TB) data from SMOS to describe dielectric and radiative properties. These novel features are combined with traditional GNSS-R features. After selecting the optimal feature set via an ablation study, the features were used to train a Random Forest (RF) classifier for sea ice classification. Validated against Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea ice type products, the proposed method yielded an overall accuracy of 93.86% and a Kappa coefficient of 0.8061. The integration of multi-dimensional features notably improved the identification of Multi-Year Ice (MYI), achieving a Recall of 85.11% and an F1-score of 84.43%. These results indicate that the proposed multi-dimensional feature set provides an effective solution for GNSS-R-based sea ice classification. Full article

Using solid waste as supplementary cementitious materials (SCMs) is an effective strategy for promoting low-carbon construction development. However, single or binary systems often exhibit mismatched reaction kinetics, thereby limiting their performance at high cement replacement rates. This study focuses on a novel low-carbon concrete designed based on reaction sequence coordination, containing recycled brick powder (RBP), ground granulated blast-furnace slag (GGBS), and self-combusting coal gangue (SCCG). The effects of RBP, GGBS, and SCCG on the hydration process and microstructure of the novel low-carbon concrete with different replacement levels have been studied by testing compressive strength, workability, and durability and observing microstructural changes. The results showed that an optimized ternary composition with an RBP:GGBS:SCCG ratio of 4:3:1 achieves a cement replacement level of 30% while exhibiting a 28-day compressive strength of 38.26 MPa, representing a 14.2% increase compared with plain cement mortar. Microstructural analyses indicate that this enhanced performance results from a time-dependent reaction sequence, in which GGBS contributes predominantly at early ages by supplying calcium, whereas RBP and SCCG mainly participate through delayed pozzolanic reactions and pore refinement at later ages. Consequently, the optimized ternary mortar exhibits a water absorption of 11.12% and a 27.2% reduction in electrical flux. This study aims to provide practical strategies for enhancing the performance of low-carbon cementitious materials through a reaction sequence coordination design approach, thereby improving the utilization efficiency of solid waste in the production of low-carbon building materials. Full article

Pulque is a traditional Mexican beverage produced through the fermentation of agave sap (aguamiel). Its primary sensory properties are attributed to the fermentative activity of Saccharomyces cerevisiae, Leuconostoc mesenteroides, and Zymomonas mobilis. However, the overproliferation of these microorganisms results in an extremely short shelf life, which hinders its commercialization. Tomatillo accrescent calyx extract (TACE) shows potential as a food preservative due to its high physalin content. Therefore, this study aimed to evaluate the effect of adding microencapsulated TACE on the shelf life and organoleptic properties of pulque. The extract demonstrated effective antimicrobial activity against L. mesenteroides, Z. mobilis, and S. cerevisiae, successfully delaying further fermentation. Additionally, the addition of TACE prevented an excessive increase in acidity, maintaining values suitable for consumption for up to 15 days, in accordance with regulatory standards, while the viscosity and alcohol content were not negatively affected. These findings suggest that TACE has significant potential for preserving both the microbiological and sensory quality of pulque. Full article

The natural gas hydrate production riser is the main passage for offshore hydrate production and transport. Its safe operation directly affects the production process. However, current hydrate production methods cannot avoid hydrate decomposition and formation inside the pipe. Hydrate phase change causes internal multiphase flow. Together with the external ocean current, it leads to more complex nonlinear vibration of the riser. Based on China’s gas hydrate trial production in the Shenhu area of the South China Sea, this study establishes a dynamic model of a production riser. The model considers hydrate phase change inside the pipe and vortex-induced vibration. It is solved using the Newmark-β method, and its validity is confirmed by CFD simulations. The results show that, under the combined action of ocean currents and internal multiphase flow, the riser exhibits a clear multi-frequency response in vortex-induced vibration. Its spatial trajectory is highly irregular. Specifically, hydrate phase change increases internal gas content and gas slippage, elevating fluid velocity. This reduces the riser’s structural stiffness and effective tension, altering the VIV response. In addition, lower top tension and higher slurry density, flow rate, and outlet backpressure delay hydrate decomposition. These factors also reduce the effective tension along the riser and increase its in-line deformation. Full article

Deep reinforcement learning (DRL) for autonomous mobile robot navigation faces several inherent limitations. The stochastic nature of actions generated by DRL policies can undermine performance consistency, while inefficient exploration frequently delays the learning process or prevents the discovery of optimal solutions. This research aims to enhance the robustness of path planning by addressing these challenges. To achieve this goal, we propose a hybrid approach that integrates the flexible decision-making capabilities of deep reinforcement learning with the stability of traditional path planning. The proposed model adopts the Twin Delayed Deep Deterministic Policy Gradient (TD3) network as its base. Notably, we pre-process LiDAR point cloud data to extract only essential features for the state representation, thereby preventing performance degradation from high-dimensional inputs and improving computational efficiency. Our model optimizes the learning process through two core strategies. First, it prioritizes experience data generated during training based on negative rewards, guiding the model to learn more frequently from critical failures rather than redundant successes. Second, it dynamically compares the action proposed by the TD3 network with a goal-oriented action from a classical path-planning algorithm in real time. By selecting the action with the higher estimated value, the model guides the policy toward a stable and effective trajectory from the earliest stages of training. To validate the efficacy of our approach, we conducted simulation-based experiments comparing the performance of the proposed model with existing reinforcement learning networks. To ensure statistical significance and mitigate the impact of random initialization, all reported results are averaged over 10 independent runs with different random seeds. The results quantitatively demonstrate that our model achieves significantly higher and more stable reward values, confirming a robust improvement in the path-planning process. Full article

Polyester resin biocomposites containing biochar have attracted attention for improving mechanical strength and thermal stability while promoting sustainability. The pyrolysis temperature of biochar and its proportion in the polymer matrix are key factors affecting biocomposite performance. This study examined how biochar pyrolysis temperatures (400, 600, 800 °C) and incorporation levels (10, 20, 30 wt.%) influence the physical, chemical, mechanical, flammability, and morphological properties of polyester-based biocomposites. The samples were analyzed for density, water absorption, FTIR, XRD, flexural and tensile strength, ignition time, structural degradation, volumetric loss, and SEM microstructure. Biocomposites with 30 wt.% biochar produced at 800 °C showed the best mechanical properties, with a flexural strength of 95.3 MPa and an elastic modulus of 4417.4 MPa, representing increases of 14.5% and 45.7%, respectively, over the control. FTIR and XRD results revealed decreased aliphatic groups and increased aromaticity at higher pyrolysis temperatures, improving interactions between the matrix and biochar. These biocomposites also demonstrated enhanced thermal stability, with an ignition time of approximately 963 s, delayed structural degradation, and reduced volumetric loss (~19.3%). Overall, pyrolysis temperature and biochar content significantly influence the structural, mechanical, and thermal properties of polyester biocomposites, showing that biochar serves as a sustainable, performance-enhancing component in thermoset polymer matrices. Full article

The skin represents the largest organ in the body and functions to protect internal tissues from damage and infection. When wounds in small animals do not receive proper management, they may progress to chronic conditions, resulting in pain, delayed healing, and impaired well-being. Although conventional treatment mainly includes the use of topical antimicrobial agents and anti-inflammatory drugs, integrative veterinary medicine has been considered a promising complementary approach to enhance tissue repair. In this context, this study aimed to review non-conventional therapies applied to wound management in small animals, focusing on ozone therapy, light therapy that stimulates cellular activity, herbal medicine, and apitherapy, especially propolis. Overall, the analyzed studies indicate that ozone may contribute to microbial control and modulation of the immune response; light therapy may stimulate cellular activity and collagen production, promoting healing; medicinal plants present antioxidant and anti-inflammatory effects; and propolis demonstrates antimicrobial and regenerative properties. Thus, when responsibly applied and supported by scientific evidence, these approaches may complement conventional therapy, broaden clinical possibilities, and contribute to improved recovery and quality of life in animals. Full article