Search Results (956)

Background: Papillary thyroid microcarcinoma (PTMC) is associated with certain features that carry an increased risk of local recurrence, underscoring the importance of preoperative risk assessment. This study investigated the clinicopathological factors associated with high-risk lymph node metastasis (HRLNM) and patient outcomes. HRLNM is defined as ≥5 metastatic lymph nodes and/or lateral neck metastasis. Methods: We conducted a retrospective review of 985 patients with PTMC who underwent thyroidectomy at the Kaohsiung Chang Gung Memorial Hospital from 2013 to 2022. Results: Among the 985 patients, 100 (10.2%) had lymph node metastasis (LNM), and 27% of these were classified as having HRLNM. Male sex (OR 3.61, p = 0.04) and extranodal extension (OR 3.76, p = 0.043) were independent predictors of HRLNM. Patients with LNM exhibited lower rates of excellent treatment response (75% vs. 87%, p = 0.001), higher recurrence rates (9.0% vs. 0.6%, p = 0.001), and an increased risk of distant metastasis (2.0% vs. 0%). Recurrence-free survival (RFS) was significantly shorter in patients with LNM (120.9 vs. 198.6 months, p < 0.001). Although HRLNM showed a trend toward reduced RFS (113.5 vs. 124.6 months, p = 0.177), its impact on long-term survival remains uncertain. Conclusions: Male sex and extranodal extension were significant risk factors for HRLNM in patients with PTMC. These findings highlight the need for individualized risk stratification to guide treatment strategies and improve patient outcomes. Full article

Effective in situ H₂S removal is essential for the utilization of small, remote natural gas wells, where centralized treatment is often unfeasible. This study presents an integrated environmental–economic assessment of two such processes, LO-CAT^® and triazine-based absorption, using a scenario-based framework. Environmental impacts were assessed via the Waste Reduction Algorithm (WAR), considering both Potential Environmental Impact (PEI) generation and output across eight categories, while economic performance was analyzed based on equipment, chemical, energy, environmental treatment, and labor costs. Results show that the triazine-based process offers superior environmental performance due to lower toxic emissions, whereas LO-CAT^® demonstrates better economic viability at higher gas flow rates and H₂S concentrations. An integrated assessment combining monetized environmental impacts with economic costs reveals that the triazine-based process becomes competitive only if environmental impacts are priced above specific thresholds. This study contributes a practical evaluation framework and scenario-based dataset that support sustainable process selection for decentralized sour gas treatment applications. Full article

The compound effects of extreme climate change and intensive urban development have led to more frequent urban inundation, highlighting the urgent need for the fine-scale evaluation of stormwater drainage system performance in high-density urban built-up areas. A typical basin, located in Shenzhen, was selected, and a pipe–river coupled SWMM was developed and calibrated via a genetic algorithm to simulate the storm drainage system. Design storm scenario analyses revealed that regional inundation occurred in the central area of the basin and the enclosed culvert sections of the midstream river, even under a 0.5-year recurrence period, while the downstream open river channels maintained a substantial drainage capacity under a 200-year rainfall event. To systematically identify bottleneck zones, two novel metrics, namely, the node cumulative inundation volume and the conduit cumulative inundation length, were proposed to quantify the local inundation severity and spatial interactions across the drainage network. Two critical bottleneck zones were selected, and strategic improvement via the cross-sectional expansion of pipes and river culverts significantly enhanced the drainage efficiency. This study provides a practical case study and transferable technical framework for integrating hydraulic modeling, spatial analytics, and targeted infrastructure upgrades to enhance the resilience of drainage systems in high-density urban environments, offering an actionable framework for sustainable urban stormwater drainage system management. Full article

In the face of escalating cyber threats to critical infrastructures, achieving robust cyber resilience has become paramount. This paper proposes an endogenous security-oriented framework for cyber resilience assessment, specifically tailored for critical infrastructures. Drawing on the principles of endogenous security, our framework integrates dynamic heterogeneous redundancy (DHR) and adaptive defense mechanisms to address both known and unknown threats. We model resilience across four key dimensions—Prevention, Destruction Resistance, Adaptive Recovery, and Evolutionary Learning—using a novel mathematical formulation that captures nonlinear interactions and temporal dynamics. The framework incorporates environmental threat entropy to dynamically adjust resilience scores, ensuring relevance in evolving attack landscapes. Through empirical validation on simulated critical infrastructure scenarios, we demonstrate the framework’s ability to quantify resilience trajectories and trigger timely defensive adaptations. Empiricalvalidation on a real-world critical infrastructure system yielded an overall resilience score of 82.75, revealing a critical imbalance between strong preventive capabilities (90/100) and weak Adaptive Recovery (66/100). Our approach offers a significant advancement over static risk assessment models by providing actionable metrics for strategic resilience investments. This work contributes to the field by bridging endogenous security theory with practical resilience engineering, paving the way for more robust protection of critical systems against sophisticated cyber threats. Full article

Although cold atmospheric plasma (CAP) has shown promise in facilitating wound repair due to its non-thermal and non-invasive properties, its dynamic effects on cellular response and metabolic regulation remain poorly characterized, and the mechanism is still unclear. In this study, we developed a microfluidic experimental system that integrates a CAP treatment module with multiparametric in situ sensing capabilities, along with precise environmental control of temperature, humidity, and CO₂ concentration. A stratified microfluidic chip was engineered to co-culture HaCaT keratinocytes and HSF fibroblasts. CAP treatment was applied within this platform, and the dynamic processes of cell migration, proliferation, and multiple metabolic markers were simultaneously monitored. The experimental results show that the system can not only achieve real-time observation in the healing process under plasma intervention, but also find that the healing process is closely related to the concentration of NO₂⁻. In addition, the study also found that keratin KRT14, which is thought to be closely related to wound healing, decreased significantly in the process of plasma-induced healing. The platform provides high-resolution experimental tools to elucidate the biological effects of CAP and has the potential for parameter optimization, material evaluation, and personalized therapeutic development to advance plasma research and clinical translational applications. Full article

To examine how reaction media influence the copolymerization processes of acrylamide-based copolymers, [BMIM]Oac and water were utilized as the reaction media. Four copolymers P(AM-SSS) (H₂O), P(AM-UA) (H₂O), P(AM-SSS) (ILs), and P(AM-UA) (ILs) were synthesized using the soluble monomer sodium p-styrene sulfonate (SSS), the insoluble monomer 10-undecylenoic acid (UA), and acrylamide (AM). The properties of the copolymers were characterized using infrared spectroscopy and ¹H NMR, and the copolymerization rates of the monomers and the segment sequences of the copolymers were calculated. The results indicated that copolymerization of SSS in ionic liquids could reduce the length of the continuous units of AM in the copolymer’s molecular chain from 231.2866 to 91.1179, with a more uniform distribution within the molecular chain. The thermal stability and micro-morphology of the copolymers were tested using a synchronous thermal analyzer and scanning electron microscopy, and the resistance of the copolymer solutions to temperature, salt, and shear were evaluated. Comparisons revealed that the three-dimensional spatial structure formed by the copolymers in ionic liquids is robust and loose. When AM and SSS polymerize in [BMIM]Oac, the resulting copolymer exhibits a higher viscosity retention rate in temperature and shear resistance tests, with a thermal decomposition temperature reaching 260 °C. Conversely, when AM and UA polymerize in [BMIM]Oac, the copolymer demonstrates good salt resistance, maintaining a viscosity retention rate of 259.04% at a Na⁺ concentration of 200,000 mg/L. Therefore, the ionic liquid [BMIM]Oac can enhance the various application performances of copolymers formed by monomers with different solubilities and AM. Full article

Meat quality is influenced by factors such as age, breed, slaughter weight, and nutrition. This study investigated the growth performance, slaughter performance, and meat quality of ducks across different breeds and ages. Results indicated that at the same age, significant differences in body weight were observed among breeds (p < 0.05), with the weight ranking in descending order as follows: Cherry Valley ducks (C) > Wuqin 10 meat ducks (W) > Mianyang Partridge ducks (M) > Liancheng White ducks (L). A comparison of the same breed across different ages revealed that the pectoral muscle ratio tended to increase with age, whereas the leg muscle ratio showed the opposite trend; however, total meat production gradually rose. At all three growth stages, C ducks exhibited higher body weight and meat yield than the other breeds. W ducks demonstrated excellent meat quality traits and appropriate meat production, with indices such as shear force, water-holding capacity, and fat content all higher than those of the other breeds. L ducks and M ducks had relatively lower body weight and meat production compared to the other breeds, yet their shear force and water-holding capacity were superior to those of C ducks. The analysis of meat quality at different times showed that across all breeds, shear force, meat color, muscle fiber diameter, crude protein content, and fat content increased with age, while drip loss rate and muscle fiber density decreased. A comprehensive multi-index evaluation model for duck meat quality under different breeds was established, along with a four-factor principal component model (Z1, Z2, Z3, Z4). Using the comprehensive ranking equation K, the meat quality performance of different breeds at various ages, in descending order, was as follows: 63-day-old W > 90-day-old M > 63-day-old C > 90-day-old L > 63-day-old M > 90-day-old C > 63-day-old L > 90-day-old W > 42-day-old C > 42-day-old W. This study not only provides a theoretical basis for evaluating meat quality traits in different duck breeds but also offers insights for breed selection and age-related quality optimization. Full article

Traditional numerical models have been widely employed to simulate the transport of multispecies reactive contaminants in groundwater systems; however, their high computational cost limits their applicability in real-time or large-scale scenarios. Recent advances in artificial intelligence (AI) offer promising alternatives, particularly data-driven machine learning techniques, for accelerating such simulations. This study presents the development of a surrogate model based on artificial neural networks (ANNs) to simulate the transport and decay of interacting multispecies contaminants in groundwater. High-fidelity training datasets are generated through finite difference-based reactive transport simulations across a wide range of environmental and geochemical conditions. The ANN model is trained to learn the complex nonlinear relationships governing the multispecies transport and transformation processes. Model validation reveals that the ANN surrogate accurately reproduces the spatial–temporal concentration profiles of both original and degradation species, capturing key dynamic behaviors with high precision. Notably, the ANN model achieves up to a 100-fold reduction in computational time compared to traditional analytical or semi-analytical solutions. These results highlight the ANN’s potential as an efficient and accurate surrogate modeling tool for groundwater contamination assessment, offering a valuable advancement for decision-making in environmental risk analysis and remediation planning. Full article

Responding to the challenges of global climate change and domestic air pollution, Taiwan revised its energy policy in recent years, introducing an energy transition strategy focused on low-carbon and clean energy. However, if photovoltaic installations are not properly sited, they may have negative impacts on the local environment. Previous research on renewable energy has primarily focused on policy evaluation, with limited attention given to case studies that examine the suitability of site selection for PV system installations. Thus, this study incorporates the Fuzzy Delphi Method (FDM) and the Analytic Hierarchy Process (AHP) to explore the criteria for evaluating site suitability for ground-mounted PV systems. This study considers existing sites with completed ground-mounted PV systems in Tainan City as case study subjects. The results indicate that the most important factor, as prioritized by experts, is the distance from Class I environmentally sensitive areas, followed by the duration of insolation, proximity to the electrical grid, and distance from residential areas. The evaluation model developed in this study provides a valuable reference for future site selection of ground-mounted PV systems. Establishing dedicated PV energy parks also may offer a viable solution to mitigate disputes related to the deployment of ground-mounted PV systems. Full article

Accurate prediction of soil lead (Pb) content in small sample scenarios is often limited by data scarcity and variability in soil properties, with traditional spectral modeling methods yielding suboptimal precision. To address this, we propose a transfer learning-based framework integrated with SHAP analysis for predicting soil Pb content in the Gejiu mining area, Yunnan. Using pH data from the European LUCAS soil database as the source domain, spectral features were extracted via a 1D-ResNet model and transferred to the target domain (130 soil samples from Gejiu) for Pb prediction. SHAP analysis was applied to clarify the role of spectral characteristics in cross-component transfer learning, uncovering shared and adaptive features between pH and Pb predictions. The transfer learning model (ResNet-pH-Pb) significantly outperformed direct modeling methods (PLS-Pb, SVM-Pb, and ResNet-Pb), with an R² of 0.77, demonstrating superior accuracy. SHAP analysis showed that the model retained key pH-related wavelengths (550–750 nm and 1600–1700 nm) while optimizing Pb-related wavelengths (e.g., 919 nm and 959 nm). This study offers a novel approach for soil heavy metal prediction under small sample constraints and provides a theoretical basis for understanding spectral prediction mechanisms through interpretability analysis. Full article

In this study, we explored the development and characterization of fungus-immobilized foamed bacterial cellulose (FBC) scaffolds using Pleurotus ostreatus and Aspergillus oryzae. FBC, a porous biomaterial with high structural integrity and resistance to enzymatic degradation, served as a three-dimensional matrix for fungal cultivation. The results indicated effective fungal immobilization, with the 1% A. oryzae-immobilized FBC group (FBC/1A) achieving the highest production yield. The water content (97%) and swelling behavior (95.9%) analyses revealed that P. ostreatus-immobilized FBC maintained high hydration levels and rehydration capacities, whereas A. oryzae immobilization led to slightly reduced water retention. Morphological assessments via SEM confirmed the presence of fungal-derived fibers integrated with native cellulose structures, suggesting successful immobilization. A thermogravimetric analysis demonstrated enhanced thermal stability in fungus-immobilized FBC, particularly in the A. oryzae group, while FTIR spectra suggested possible structural alterations induced by fungal activity. Collectively, these findings support the potential of fungal-immobilized FBC as a robust, biodegradable material with promising applications in biotechnology and sustainable material development. Full article

This study develops a novel dual-layer chitosan (CS)/pectin film incorporating grape skin anthocyanin extract (GSAE) and lignin to address critical limitations in cherry preservation. Unlike traditional methods that leave harmful residues, this bilayer design separately integrates functional components: GSAE for targeted antioxidant/antibacterial action and lignin for ultraviolet (UV) blocking. This targeted incorporation enables synergistic performance unattainable with single-layer or conventional approaches. The films, fabricated with lignin concentrations from 1% to 15% (w/v), demonstrated excellent mechanical integrity (assessed with structural characterization), optimized gas barrier performance, and effective UV attenuation (achieved via lignin incorporation). Antibacterial analyses confirmed substantial inhibition against Staphylococcus aureus and Escherichia coli. Crucially, cherry preservation tests showed that the 15% lignin film (PG/CL15%) reduced weight loss, preserved firmness, and extended shelf life by 8 days—a significant quantitative improvement over uncoated fruit. Structural characterization (TGA, FT-IR, and XRD) verified successful GSAE/lignin embedding via hydrogen bonding. Beyond cherries, this dual-layer, bio-based design offers a promising template for the active packaging of other perishable produce sensitive to oxidation, microbial spoilage, and UV degradation, which enhances its industrial relevance. Full article

Silicon oxynitride (SiO_xN_y, hereafter denoted as SiON) thin films represent an intermediate phase between silicon dioxide (SiO₂) and silicon nitride (Si₃N₄). Through systematic compositional ratio adjustments, the refractive index can be precisely tuned across a wide range from 1.45 to 2.3. However, the underlying mechanism governing the influence of elemental composition on film structural quality remains insufficiently understood. To address this knowledge gap, we systematically investigate the effects of key industrial plasma-enhanced chemical vapor deposition (PECVD) parameters—including precursor gas selection and flow rate ratios—on SiON film properties. Our experimental measurements reveal that stoichiometric SiO_xN_y (x = y) achieves a minimum surface roughness of 0.18 nm. As oxygen content decreases and nitrogen content increases, progressive replacement of Si-O bonds by Si-N bonds correlates with increased structural defect density within the film matrix. Capacitance–voltage (C-V) characterization demonstrates a corresponding enhancement in device capacitance following these compositional modifications. Recent studies confirm that controlled modulation of film stoichiometry enables precise tailoring of dielectric properties and capacitive behavior, as demonstrated in SiON-based power electronics, thereby advancing applications in related fields. Full article

Embedded system networks are widely deployed across various domains and often perform mission-critical tasks, making it essential for all nodes within the system to be trustworthy. Traditionally, each node is equipped with a discrete Trusted Platform Module (dTPM) to ensure network-wide trustworthiness. However, this study proposes a cost-effective system architecture that deploys software-based TPMs (SWTPMs) on the majority of nodes, while reserving dTPMs for a few central nodes to maintain overall system integrity. The proposed architecture employs IBMACS for system integrity reporting. In addition, a database-based anomaly detection (AD) agent is developed to identify and isolate untrusted nodes. A traffic anomaly detection agent is also introduced to monitor communication between servers and clients, ensuring that traffic patterns remain normal. Finally, a custom measurement kernel is implemented, along with an activation agent, to enforce a measured boot process for custom applications during startup. This architecture is designed to safeguard mission-critical embedded systems from malicious threats while reducing deployment costs. Full article

Atopic dermatitis (AD) is a common chronic skin disease affecting both children and adults. Currently lacking a clinical cure, AD presents significant physical and emotional challenges for patients and their families, substantially impacting their quality of life. This underscores significant unmet needs in AD management and highlights the necessity for developing effective therapeutic applications. Recently, several chlorine-containing active substances with promising pharmacological activity have been discovered in soft corals cultivated through coral farming. Among these, brianolide, isolated from the soft coral Briareum stechei, has shown promising potential. This study investigated brianolide’s regulatory effects on the inflammatory response in atopic dermatitis and its underlying mechanisms. Using an in vitro human keratinocyte cell line (HaCaT) stimulated with tumor necrosis factor-α (TNF-α)/interferon-γ (IFN-γ) to mimic AD inflammation, brianolide was found to inhibit cytokine and chemokine expression via the mitogen-activated protein kinase (MAPK) and nuclear factor kappa-light-chain-enhancer of activated B cell (NFκB)-signaling pathways. In an in vivo animal model of 2,4-Dinitrochlorobenzene (DNCB)-induced AD, brianolide demonstrated anti-inflammatory effects, reducing transepidermal water loss (TEWL), ear thickness, erythema, and epidermal blood flow. These findings provide new insights into brianolide’s activity against AD-related inflammation, elucidate potential mechanisms, and contribute to understanding the pharmacological potential of natural coral products for AD treatment. Full article