Search Results (6,377)

Soil moisture is one of the key hydrologic components indicating the performance of landfill final covers. Conventional compacted clay (CC) covers and evapotranspiration (ET) covers often suffer from moisture-induced stresses, such as desiccation cracking and irreversible hydraulic conductivity. Engineered turf (EnT) cover systems have been introduced recently as an alternative; however, their field-scale moisture distribution behavior remains unexplored. This study investigates and compares the soil moisture distribution characteristics of EnT, ET, and CC landfill covers at a shallow depth using one year of field-monitored data in a humid subtropical region. Three full-scale test Sections (3 m × 3 m × 1.2 m) were constructed side by side and instrumented with moisture sensors at a depth of 0.3 m. Distributional characteristics of moisture were evaluated with descriptive statistics, goodness-of-fit tests such as Shapiro–Wilk (SW) and Anderson–Darling (AD), Gaussian probability density functions, Q–Q plots, and standard-normal transformations. Results revealed that Shapiro–Wilk (W = 0.75–0.92, p < 0.001) and Anderson–Darling $(A^2=1.63\times {10}^3\mathrm{to}6.31\times {10}^3,p<0.001)$ tests rejected normality for every cover, while Levene’s test showed unequal variances between EnT and the other covers $(F>5.4\times {10}^4,$$p<0.001)$ but equivalence between CC and ET (F = 0.23, p = 0.628). EnT cover exhibited the narrowest moisture envelope $(95\%\mathrm{range}=0.156\mathrm{to}0.240{\mathrm{m}}^3/{\mathrm{m}}^3;\mathrm{CV}=10.6\%)$, whereas ET and CC covers showed markedly broader distributions (CV = 38.6 % and 33.3 %, respectively). These findings demonstrated that EnT cover maintains a more stable shallow soil moisture profile under dynamic weather conditions. Full article

Laser Powder Bed Fusion (LPBF) has emerged as a leading additive manufacturing (AM) process for producing complex metal components. Despite its advantages, the inherent LPBF process complexity leads to challenges in achieving consistent quality and repeatability. To address these concerns, recent research efforts have focused on sensor fusion techniques for process monitoring, and on developing more elaborate control strategies. Sensor fusion combines information from multiple in situ sensors to provide more comprehensive insights into process characteristics such as melt pool behavior, spatter formation, and layer integrity. By leveraging multimodal data sources, sensor fusion enhances the detection and diagnosis of process anomalies in real-time. Closed-loop control systems may utilize this fused information to adjust key process parameters–such as laser power, focal depth, and scanning speed–to mitigate defect formation during the build process. This review focuses on the current state-of-the-art in sensor fusion monitoring and control strategies for LPBF. In terms of sensor fusion, recent advances extend beyond CNN-based approaches to include graph-based, attention, and transformer architectures. Among these, feature-level integration has shown the best balance between accuracy and computational cost. However, the limited volume of available experimental data, class-imbalance issues and lack of standardization still hinder further progress. In terms of control, a trend away from purely physics-based towards Machine Learning (ML)-assisted and hybrid strategies can be observed. These strategies show promise for more adaptive and effective quality enhancement. The biggest challenge is the broader validation on more complex part geometries and under realistic conditions using commercial LPBF systems. Full article

Standardized driving cycles such as the FTP-75 fail to represent traffic conditions in cities like Guayaquil, where high congestion and varied driving behaviors are not captured by external models. This study aimed to develop representative driving cycles for the city’s most congested urban routes, covering the north, south, center, and west zones. Using the direct method, real-world trips were conducted with an M1-category vehicle equipped with an OBDLINK MX+ device, allowing real-time data collection. Driving data were processed through OBDWIZ software Version 4.30.1 and statistically analyzed using Minitab. From pilot tests, the appropriate sample size was estimated, and normality tests were applied to determine the correct measures of central tendency. The final representative cycles were constructed using a weighting criteria method. The results provided quantified evidence of variations in average speed, idle time, and acceleration patterns across the routes, which were transformed into representative driving cycles. These cycles provide a more accurate basis for emission modeling, vehicle certification, and transport policy design in congested cities such as Guayaquil, and this is the applied impact that is highlighted in our contribution. Furthermore, the developed cycles provide a foundation for future research on emission modeling and the design of sustainable transport strategies in Latin American cities. Full article

Multilevel active bridge converters are potential candidates for many modern high-power DC applications due to their ability to integrate multiple sources while minimizing weight and volume. Therefore, this paper deals with an analytical, simulation-based, and experimentally verified investigation of their circulating current behavior, power factor performance, and power loss characteristics. A high-frequency link analysis framework is developed to characterize voltage, current, and power transfer waveforms, providing insight into reactive power generation and its impact on overall efficiency. By introducing a modulation-based control approach, the proposed converters significantly reduce circulating currents and enhance the power factor, particularly under varying phase-shift conditions. Compared to quadruple active bridge topologies, the discussed multilevel architectures offer reduced transformer complexity and improved power quality, making them suitable for demanding applications such as electric vehicles and aerospace systems. Full article

This paper presents a detailed analysis of the thermal and flammability properties of polylactide- (PLA) and poly(ethylene terephthalate)- (PET) based polymer blends with biofillers, such as calcium lignosulfonate (CLS), lignosulfonamide (SA) and lignosulfonate modified with tannic acid (BMT) and gallic acid (BMG). Calorimetric studies revealed the presence of two glass transitions, one cold crystallization temperature, and two melting points, confirming the partial immiscibility of the PLA and PET phases. The additives had different effects on the temperatures and ranges of phase transformations—BMT restricted PLA chain mobility, while CLS acted as a nucleating agent that promoted crystallization. Thermogravimetric analyses (TGA) analyses showed that the additives significantly affected the thermal stability under oxidizing conditions, some (e.g., BMG) lowered the onset degradation temperature, while the others (BMT, SA) increased the residual char content. The additives also altered combustion behavior; particularly BMG that most effectively reduced flammability, promoted char formation, and extended combustion time. CLS reduced PET flammability more effectively than PLA, especially at higher PET content (e.g., 65% reduction in PET for 2:1/CLS). SA inhibited only PLA combustion, with strong effects at higher PLA content (up to 76% reduction for 2:1/SA). BMT mainly reduced PET flammability (48% reduction in 1:1/BMT), while BMG inhibited PET more strongly at lower PET content (76% reduction for 2:1/BMG). The effect of each additive also depended on the PLA:PET ratio in the blend. FTIR analysis of the char residues revealed functional groups associated with decomposition products of carboxylic acids and aromatic esters. Ultimately, only blends containing BMT and BMG met the requirements for flammability class FV-1, while SA met FV-2 classification. BMG was the most effective additive, offering enhanced thermal stability, ignition delay, and durable char formation, making it a promising bio- based flame retardant for sustainable polyester materials. Full article

This review emphasizes the latest developments in bioprinted scaffolds in tissue engineering, with a focus on their biomimetic applications. The accelerated pace of development of 3D bioprinting technologies has transformed the ability to fabricate scaffolds with the potential to replicate the structure and function of native tissues. Bioprinting methods such as inkjet, extrusion-based, laser-assisted, and digital light processing (DLP) approaches have the potential to fabricate complex, multi-material structures with high precision in geometry, material composition, and cellular microenvironments. Incorporating biomimetic design principles to replicate the mechanical and biological behaviors of native tissues has been of major research interest. Scaffold geometries that support cell adhesion, growth, and differentiation essential for tissue regeneration are mainly of particular interest. The review also deals with the development of bioink, with an emphasis on the utilization of natural, synthetic, and composite materials for enhanced scaffold stability, printability, and biocompatibility. Rheological characteristics, cell viability, and the utilization of stimuli-responsive bioinks are also discussed in detail. Their utilization in bone, cartilage, skin, neural, and cardiovascular tissue engineering demonstrates the versatility of bioprinted scaffolds. Despite the significant advancements, there are still challenges that include achieving efficient vascularization, long-term integration with host tissues, and scalability. The review concludes by underlining future trends such as 4D bioprinting, artificial intelligence-augmented scaffold design, and the regulatory and ethical implications involved in clinical translation. By considering these challenges in detail, this review provides insight into the future of bioprinted scaffolds in regenerative medicine. Full article

In this study the influence of the geological formation environment on the physicochemical properties of two natural sepiolites, as collected, was investigated. The samples analyzed were a lacustrine-derived sample from Tolsa, Spain (ST), and a hydrothermal-derived sample from La Adela, Argentine (SA). Comprehensive characterization was carried out using chemical analysis (XRF), X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and evaluations of hydrophobicity/hydrophilicity behavior. The results indicate that the ST sample exhibits a higher SiO₂/MgO ratio and contains amorphous silica impurities, while the SA sample shows a composition more closely aligned with the theoretical stoichiometry of sepiolite. Furthermore, the SA sample demonstrates greater crystallinity compared to the ST sample. Morphological analysis revealed that ST consists of compact, aggregated fibrous structures, while SA is composed of disaggregated, needle-like fibers with high aspect ratios and nanometric diameters. Both samples display predominantly hydrophilic behavior; however, only the SA sample exhibits suspended particles at the interface, suggesting a slightly higher hydrophobic character than ST sample. These findings highlight the significant impact of the geological formation environment on the structural and surface characteristics of sepiolite, which, in turn, influence its performance in applications involving dispersion, adsorption, and interfacial interactions. Full article

This study presents the development of a predictive system based on artificial neural networks (ANNs) and fuzzy logic to estimate losses in an agave liquor production and packaging plant. Currently, these losses are discharged into wastewater, generating not only finished product waste, but also greater environmental pollution and higher treatment costs. To address this, agave liquor waste is converted into methane biogas through anaerobic digestion and subsequently transformed into electrical energy. The system begins by collecting historical data from the production process, including production plans and shrinkage rates at each stage of the packaging line. These data are analyzed to identify behavioral patterns and correlations between process variables and losses, allowing a deeper understanding of the packaging process. Critical control points were identified throughout the production stages, and an ANN model was trained with historical data to predict losses. Outstanding results were achieved in the packaging and capping stage, where a significant impact on bottle loss was observed, with a 29% impact in the morning shift and a 35% impact in the afternoon shift. Fuzzy logic was used to manage the uncertainty and subjectivity associated with identifying the stages most susceptible to waste, translating qualitative assessments into quantitative metrics. Estimates allow for approximately 8% to 12% reductions by streamlining the process with this analysis obtained through the use of artificial intelligence tools. This integrated approach aims to optimize operational efficiency, reduce losses, minimize environmental impact, and promote sustainable practices within the agave liquor industry. Full article

The promise of sustainability of ecotourism relies on comprehending the psychological mechanism that converts experience into post-visit environmental concern. This research formulates and examines a model that connects three antecedents—Perceived Trip Quality (PTQ), Aesthetic/Spiritual Experience (ASE), and Environmental Concern (EC)—with Responsible Post-Visit Behavior (RPB) through two mediators: Tourist Satisfaction (SAT) and Personal Norms (PN). Structural equation modeling based on a quantitative, cross-sectional design examined survey responses from 585 Greek ecotourists. All three precursors meaningfully predicted RPB, directly and indirectly through SAT and PN, with partial mediation on all but the direct pathway. Mediation effects also named PN a stronger channel than SAT, particularly in converting affective and moral involvement into stable intentions. Multi-group tests for gender, age, education, environmental orientation, and previous ecotourism experience revealed significant differences; younger, inexperienced, and high-orientation tourists were more sensitive to normative and affective mechanisms. The research develops environmental and tourism psychology by combining value-based and experience-based routes to post-visit action. Practical recommendations are made to policymakers, educators, and operators to develop transformational, norm-activating experiences. Full article

This study aims to address the poor extensibility, brittleness, and limited hydration stability of pure sodium alginate (SA) hydrogels, which hinder their use in flexible, skin-adherent applications such as facial masks, by developing bio-based composites incorporating five representative functional additives: xanthan gum, guar gum, hydroxyethyl cellulose (HEC), poly(ethylene glycol)-240/hexamethylene diisocyanate copolymer bis-decyl tetradeceth-20 ether (GT-700), and Laponite^® XLG. Composite hydrogels were prepared by blending 1.5 wt% SA with 0.3 wt% of each additive in aqueous humectant solution, followed by ionic crosslinking using 3% (w/w) CaCl₂ solution. Physicochemical characterization included rotational viscometry, uniaxial tensile testing, ATR-FTIR spectroscopy, swelling ratio analysis, and pH measurement. Among them, the SA/XLG composite exhibited the most favorable performance, showing the highest viscosity, shear-thickening behavior, and markedly enhanced extensibility with an elongation at break of 14.8% (compared to 2.5% for neat SA). It also demonstrated a mean swelling ratio of 0.24 g/g and complete dissolution in water within one year. ATR-FTIR confirmed distinct non-covalent interactions between SA and XLG without covalent modification. The hydrogel also demonstrated excellent conformability to complex 3D surfaces, consistent hydration retention under centrifugal stress (+23.6% mass gain), and complete biodegradability in aqueous environments. Although its moderately alkaline pH (8.96) may require buffering for dermatological compatibility, its mechanical resilience and environmental responsiveness support its application as a sustainable, single-use skin-contact material. Notably, the SA/XLG composite hydrogel demonstrated compatibility with personalized fabrication strategies integrating 3D scanning and additive manufacturing, wherein facial topography is digitized and transformed into anatomically matched molds—highlighting its potential for customized cosmetic and biomedical applications. Full article

Background: Insect-derived proteins constitute an underutilized biological resource requiring urgent exploration to address global food protein shortages. However, their widespread application is hindered by the allergenic potential, particularly phospholipase A2 (PLA2), a highly immunoreactive allergen prevalent in edible insects such as ants and honeybees. Objective: This study systematically investigated the molecular mechanism underlying quercetin-mediated reduction in PLA2 allergenicity, aiming to establish a novel strategy for developing hypoallergenic insect protein resources. Methods and Results: Through integrated computational and experimental approaches, we identified quercetin’s dual non-covalent and covalent binding capabilities with PLA2. Molecular docking revealed robust interactions (the binding energy of −6.49 kcal/mol) within the catalytic pocket. Meanwhile, mass spectrometry specifically identified Cys37 as the covalent modification site, which can bind to quercetin and increase the gyration radius (Rg) of PLA2 within 75–125 ns. Molecular dynamics simulations illustrated quercetin-induced conformational changes affecting critical antigenic epitopes. Murine experiments further confirmed that quercetin-modified PLA2 exhibited significantly reduced IgE reactivity and allergic responses compared to native PLA2, as demonstrated by assessments of anaphylactic behavior, histopathological changes, and measurements of serum IgE antibody and biogenic amine levels. Conclusions: Collectively, these findings provide a transformative approach to safely utilize insect-derived proteins for sustainable nutrition solutions. Full article

3D bioprinting has emerged as a key tool in tissue engineering by facilitating the creation of customized scaffolds with properties tailored to specific needs. Among the design parameters, porosity stands out as a determining factor, as it directly influences critical mechanical and biological properties such as nutrient diffusion, cell adhesion and structural integrity. This review comprehensively analyses the state of the art in scaffold design, emphasizing how porosity-related parameters such as pore size, geometry, distribution and interconnectivity affect cellular behavior and mechanical performance. It also addresses advances in manufacturing methods, such as additive manufacturing and computer-aided design (CAD), which allow the development of scaffolds with hierarchical structures and controlled porosity. In addition, the use of computational modelling, in particular finite element analysis (FEA), as an essential predictive tool to optimize the design of scaffolds under physiological conditions is highlighted. This narrative review analyzed 112 core articles retrieved primarily from Scopus (2014–2025) to provide a comprehensive and up-to-date synthesis. Despite recent progress, significant challenges persist, including the lack of standardized methodologies for characterizing and comparing porosity parameters across different studies. This review identifies these gaps and suggests future research directions, such as the development of unified characterization and classification systems and the enhancement of nanoscale resolution in bioprinting technologies. By integrating structural design with biological functionality, this review underscores the transformative potential of porosity research applied to 3D bioprinting, positioning it as a key strategy to meet current clinical needs in tissue engineering. Full article

The green transformation of agricultural systems is crucial for environmental protection and food security, yet smallholder-dominated systems face immense structural barriers. This study investigates whether agricultural socialized services (ASSs)—an emerging institutional innovation—can serve as a catalyst for this transition. Using household survey data from the China Land Economy Survey (CLES), this study examines the direct impact and mediating pathways of ASSs on farmers’ adoption of green production behaviors. We also reveal the heterogeneity effects of household operating scale. The results show the following: (1) Agricultural socialized services positively impact farmers’ adoption of green production behaviors, which can contribute to advancing sustainable agricultural development. (2) ASSs do not simply increase the quantity of machines. Instead, they facilitate a shift from costly asset ownership to efficient mechanization-as-a-service. (3) Furthermore, a heterogeneity analysis reveals that the positive impacts of ASSs are heterogenous at different levels. ASSs more significantly influence farmers’ adoption of green practices for small-scale farms (operating at a size less than 4.8 mu). It provides robust empirical evidence that ASSs can effectively “decouple” green modernization from large-scale farmers to overcome structural barriers. These findings help to provide policy implications for promoting ASSs and sustainable agriculture production. Full article

The extraction of lithium from clay-type lithium ores has attracted significant attention, but the leaching behavior of associated elements, such as Rb, K, and Sr, remains less explored. This study quantitatively investigated the leaching behaviors and mechanisms of Li, Rb, K, Sr, and Mg in clay-type lithium ore through water leaching and roasting–water leaching processes. The results show that during direct water leaching, the leaching efficiency of K ranged between 10% and 13%, while Li and Sr exhibited lower extraction rates, requiring prolonged high-temperature leaching. Rb dissolution was minimal, and the leaching efficiency of Mg was significantly affected by temperature. In contrast, roasting–water leaching significantly enhanced the leaching efficiency, achieving extraction rates of 90.65% for Li, 92.91% for Rb, 75.85% for K, and 36.99% for Sr. However, Mg leaching was suppressed to below 1%. Roasting disrupted the original silicate and carbonate lattices, generating new phases that altered the ore’s microstructure into aggregated dense phases and needle-like porous phases upon water leaching, thereby facilitating the release of Li, Rb, K, and Sr. A research finding was that the new phase generated by magnesium inhibited its leaching, which indirectly enhanced subsequent Li, Rb, K, and Sr extraction and separation. These findings provide a quantitative foundation for optimizing multi-element co-extraction from clay-type lithium ores. Full article

Ependymomas are a heterogeneous group of central nervous system tumors originating from ependymal cells, exhibiting significant variability in clinical behavior, prognosis, and treatment response based on anatomical location and molecular profile. Historically, diagnosis and grading relied on histopathological features, often failing to predict outcomes accurately across tumor subtypes. With the integration of molecular and epigenetic profiling, the classification and management of ependymomas have undergone a significant transformation, culminating in the updated 2021 World Health Organization Classification of Tumors of the Central Nervous System. This molecularly driven system emphasizes the relevance of DNA methylation patterns and fusion oncogenes, offering a more biologically accurate stratification of disease. These insights enhanced diagnostic accuracy and informed prognostic assessments, paving the way for new targeted therapies. Although conventional treatment primarily consists of surgical resection and radiotherapy, emerging preclinical and early-phase clinical studies suggest a potential for molecularly guided interventions targeting specific oncogenic pathways. Despite these advances, effective targeted therapies remain limited, highlighting the need for further research and molecular stratification in clinical trial design. Additionally, the practical implementation of molecular diagnostics in standard-of-care settings is challenged by cost, accessibility, and institutional variability, which may impede equitable integration. This review summarizes the evolution of ependymoma classification, current molecular subtypes, gaps in clinical application and their implications for personalized therapy and future clinical research. Full article