Search Results (17,138)

Maple (Acer spp.) seeds are potential sources of fat-soluble nutrients and bioactive compounds, yet they remain comparatively understudied. This study compared six market-derived Acer seed types by quantifying phospholipids (PLs), fatty acids, carotenoids, and phytosterols, and by evaluating total phenolic content (TPC) and DPPH radical scavenging activity in methanolic extracts. Total phospholipid contents varied markedly among samples (17.94–295.87 mg/100 g), with phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylinositol (PI) as the predominant classes. Fatty acid profiles were dominated by oleic acid (C18:1) and linoleic acid (C18:2), and nervonic acid (NA; C24:1) was consistently detected in all samples at 0.17–1.88 g/100 g (4.55–7.89% of total fatty acids). β-Sitosterol ranged from 16.58 ± 1.41 to 37.46 ± 1.62 mg/100 g. Carotenoid composition varied among the tested samples, and Jeju red maple showed the highest provitamin A potential, including the exclusive detection of α-carotene and the highest retinol activity equivalent. Antioxidant indices also differed significantly among samples (TPC: 317.89–897.12 mg GAE/100 g; DPPH: 81.37–93.27%), but TPC was not consistently proportional to DPPH activity, suggesting contributions from non-phenolic constituents. Pearson correlation analysis further showed exploratory co-variation patterns among the measured variables across the tested samples. Overall, the tested market-derived Acer seed materials exhibited marked compositional diversity and antioxidant potential, supporting their further evaluation as candidate functional food, nutraceutical, and value-added plant lipid resources. Full article

The origin of life is commonly discussed within two competing conceptual frameworks: the metabolism-first and information-first hypotheses. While each emphasizes a different defining property of early life, modern biochemistry reveals a fundamental interdependence between metabolic processes and genetic information transfer, leading to a persistent chicken-and-egg problem. In this study, we investigate a prebiotically plausible reaction system that enables the concurrent formation of molecular precursors associated with both frameworks. Under simulated Hadean hydrothermal conditions, acetylene, ammonia, cyanide, and carbon monoxide were reacted in aqueous solution in the presence of transition metal sulfides. Using gas chromatography–mass spectrometry combined with stable isotope labeling, we demonstrate the simultaneous formation of the nucleobase uracil and the amino acids alanine and aspartic acid. Isotopic incorporation patterns allow reconstruction of the underlying reaction pathways and confirm the contribution of all starting materials to product formation. While amino acids are produced continuously over the observed period in significantly higher yields than uracil, uracil formation exhibits a pronounced time-dependent maximum after three days. Variations in pH, reaction time, and metal sulfide catalysts modulate product yields but do not prevent the parallel emergence of both molecular classes. These findings support a scenario in which proto-metabolic chemistry and molecular precursors of genetic information could have arisen simultaneously within a shared geochemical setting. The results provide experimental support for a coupled origin of metabolism and transcriptional building blocks, offering a potential resolution to the dichotomy between metabolism-first and information-first models of early life. Full article

Introduction: Drug side effects are a relevant problem for patient safety and public health, and traditional methods have limitations in capturing complex patterns between clinical and pharmacological variables. Objective: To evaluate machine learning models to probabilistically predict multiple side effects associated with drug use. Materials and methods: A cross-sectional computational study was carried out with data from 1000 medications that included clinical condition, dosage and duration of treatment. Random Forest, Decision Tree, Support Vector Classifier and KNN were trained and optimized using Grid Search and an 80:20 split for training and testing. Chi-square tests and Principal Component Analysis were applied to explore associations and overlap between categories. Results: Significant associations were found between side effects and clinical condition (p < 0.05) and the drug administered (p < 0.05). The PCA showed a high overlap between categories, which justified a probabilistic approach. Tree-based models showed better performance (accuracy ≈ 0.35). Conclusions: Prediction of side effects is a multifactorial and non-deterministic problem; probabilistic machine learning models allow for estimating several plausible adverse events and can support clinical decision-making and pharmacovigilance. Full article

Background/Objectives: Tablet development requires simultaneous optimization of multiple quality attributes under limited experimental budgets, yet formulation–property relationships are highly nonlinear in mixture systems. To support pre-formulation decision-making prior to extensive tablet prototyping, this study proposes an AI framework that organizes formulation and process data together with raw-material property records into a reusable database, and enriches conventional composition/process features with physically motivated mixture descriptors derived from raw-material properties and formulation/process settings. Methods: Mixture-level scalar descriptors are constructed by composition-weighted aggregation of material properties, and particle size distribution (PSD) is incorporated via a compact set of summary statistics computed from composition-weighted mixture PSDs. Three feature sets are compared: (i) Materials + Processes (MP), (ii) MP with scalar Descriptors (MPD), and (iii) MPD with PSD summaries (MPDD). Five target properties are modeled: hardness, disintegration time, flow function, cohesion, and thickness. We train and evaluate Random Forest, Extra Trees Regressor, Lasso, Partial Least Squares, Support Vector Regression, and a multi-branch neural network that processes the three feature blocks separately and concatenates them for prediction. For interpolation assessment, repeated Train/Dev/Test splitting (5:3:2) across multiple random seeds is used, and the effect of feature augmentation is quantified by paired RMSE improvements with bootstrap confidence intervals and paired Wilcoxon signed-rank tests. To assess robustness under practical formulation updates, rolling-origin time-series splits are employed and Applicability Domain indicators are computed to characterize out-of-distribution coverage. Results: Across interpolation evaluations, mixture-descriptor augmentation (MPD/MPDD) improves hardness and disintegration time in most settings, whereas gains for flow function are smaller and cohesion/thickness show mixed effects under limited sample sizes. Conclusions: Under extrapolation-oriented evaluation, the descriptors can improve hardness but may degrade disintegration-time prediction under covariate shift, emphasizing the need for careful descriptor selection and dimensionality control when deploying pre-formulation predictors. Full article

Polymer-modified bituminous binders are widely used in road construction due to their enhanced mechanical performance; however, the effectiveness of these materials critically depends on the actual concentration of polymer modifiers, particularly styrene-butadiene-styrene (SBS). This study aims to develop and validate a rapid, reproducible Fourier Transform Infrared Spectroscopy—Attenuated Total Reflectance (FTIR-ATR) spectroscopy method for the quantitative determination of SBS content in polymer-modified bitumen (PMB). Since, to date, there is no clearly defined method for controlling the quantitative content of polymers in PMB, this creates difficulties in accepting the roadway into operation. Calibration PMB samples containing 1–4% SBS were prepared, tested for physical and mechanical properties, and analyzed spectroscopically to identify characteristic absorption bands at 966 cm⁻¹ and 699–760 cm⁻¹. A first-order calibration model was constructed to relate peak intensity to polymer concentration. The results demonstrate a clear linear correlation between SBS content and IR absorption features, confirming the suitability of FTIR as an instrumental method for routine laboratory control. Application of the model allowed determination of actual polymer mass fraction with high accuracy and reproducibility. The findings also showed that increased SBS levels improve softening point, elasticity, and low-temperature resistance, with 3–4% representing a performance-optimal range. Overall, the proposed FTIR-based approach provides an objective and efficient tool for quality control of polymer-modified binders and supports broader standardization efforts in the field. Full article

Education for Sustainable Development (ESD) plays a vital role in addressing global sustainability changes, and foreign language teaching may contribute to this process. Nevertheless, studies on the incorporation of Sustainable Development Goals (SDGs) in materials related to teaching Turkish as a Foreign Language (TTFL) are limited. This study examines the representation of the 17 SDGs in TTFL textbooks. A qualitative document analysis was conducted on the A1, B1, and C1 levels of the “Yeni İstanbul” textbook series across the social, economic, and environmental dimensions of sustainability. The findings indicate a hierarchical distribution of SDG-related content across proficiency levels. At the beginner (A1) level, the social dimension with emphasis on urban integration themes (78.09%) is dominant, while at the advanced (C1) level, the economic dimension becomes more prominent (43.17%). The most striking result is that the environmental dimension remains the weakest area at all levels (A1: 6.67%; B1: 9.95%; C1: 10.93%). Environmental issues primarily appear as contextual vocabulary rather than critical sustainability content. Although the textbooks support socio-economic integration, they show limited alignment with sustainability literacy goals. The findings highlight the need for a more comprehensive integration of environmental sustainability themes in foreign language curricula. Full article

Within a waste biorefinery framework, integrating agro-industrial by-products into the circular economy requires a detailed understanding of the thermochemical conversion behaviour of low-grade carbonaceous materials. This study evaluates the co-pyrolysis characteristics of Soma lignite (SL) and pectin-rich sugar beet pulp (SBP) as a sustainable route for upgrading these resources into clean energy carriers. Interactions between the two feedstocks were analysed by thermogravimetric measurements, triple-region kinetic modelling, and quantitative synergy indices at six mixing ratios, including the pure samples (100:0, 80:20, 60:40, 40:60, 20:80, and 0:100 wt% SL:SBP). The Reactivity Index ($R_{\mathrm{m}}$) increased from $0.97\times {10}^{-4}$ s${}^{-1}$K${}^{-1}$ for pure SL to $8.65\times {10}^{-4}$ s${}^{-1}$K${}^{-1}$ for the 20:80 blend, showing that SBP acts as a highly reactive biomass component that accelerates devolatilisation in the main pyrolysis region. Synergy analysis indicated a shift from inhibitory behaviour in coal-rich blends to slightly positive synergy in SBP-rich mixtures, with the onset of positive $\Delta TC$ around 60 wt% SBP under the present single-heating-rate, non-replicated TGA conditions. This tentative threshold-like behaviour suggests that a critical level of literature-supported, hypothesised hydrogen-donating biomass radicals may be required to overcome the structural resistance of the coal matrix. Within these experimental limitations, the apparent macro-kinetic deviations and first-order Arrhenius parameters suggest that SL/SBP co-pyrolysis follows a complex, non-additive pathway that should be further validated by multi-heating-rate and product characterisation studies in future work. The primary contribution of this work lies in proposing this distinct threshold-like biomass fraction at the macro-kinetic level that governs the transition from heat-transfer-limited antagonism to radical-influenced synergy in low-rank coal and pectin-rich biomass blends. Overall, the combined $\Delta TC$, $\Delta E$ and $R_{\mathrm{m}}$ descriptors provide useful macro-kinetic benchmarks for guiding the optimisation of thermochemical processes for low-grade carbonaceous resources. Full article

By examining historical recipes from the medieval treatise The Montpellier Liber Diversarum Arcium, the creation of bottle green and verdigris pigments involved various types of tempera, such as parchment glue and gum arabic. Malachite was also prepared. These references and paints were analysed using infrared spectroscopy and visible spectroscopy techniques, such as micro-Infrared Spectroscopy (microFTIR) and Fibre Optic Reflectance Spectroscopy, (FORS) over the 350–1000 nm range. This research provided new insights into the pigments used in monastic manuscripts and Books of Hours, supported by valuable data from the Soleil synchrotron. Producing historically accurate reproductions and applying spectroscopy to analyse them promotes sustainable cultural heritage preservation by maintaining ancient artefacts, detecting early signs of degradation, and enabling the development of compatible restoration materials. Full article

Pulsed polarization of Au|YSZ gas sensors is examined to clarify the mechanism of NO_x detection under dynamic operation and to disentangle catalytic surface effects from electrochemical relaxation. Using gold electrodes with substantially lower catalytic activity than platinum explicitly enables this mechanistic separation. During pulsed polarization, periodic voltage pulses are followed by self-discharge under open-circuit conditions, and the response is measured based on the self-discharge rate. NO₂ consistently accelerates the self-discharge from the beginning, whereas NO slows the relaxation predominantly at later times. CO and H₂ produce similar delaying effects, and C₃H₆ shows no measurable influence under the tested conditions. Decreasing ambient O₂ slows the discharge and amplifies the NO₂ effect, which indicates that oxygen supply and surface exchange at the triple-phase boundary are rate determining. A Pt-containing catalytic overlayer drives local NO/NO₂ interconversion toward equilibrium so that both gases yield to an accelerated self-discharge. These findings support a mechanistic picture in which NO₂ provides effective oxygen equivalents that accelerate discharge, whereas NO, CO, and H₂ consume oxygen and slow down discharge. Overall, this establishes a materials-based approach for distinguishing between NO and NO₂ and evaluating the underlying mechanism during pulsed polarization. Full article

This study examines the impact of agribusiness corporations (large-scale agricultural enterprises) and family farms on the sustainable development of agriculture and rural areas in Ukraine, and considers implications for SDG-aligned agri-food value chains that rely on stable access to sustainably produced raw materials. The research applies a multi-criteria decision analysis framework integrating economic, environmental and social indicators at the regional level. Using min–max normalisation, scoring and ranking methods, composite indices of economic sustainability, environmental sustainability, and sustainable rural development were constructed for 20 selected Ukrainian regions, and an integral sustainability index was calculated. Spearman’s rank correlation was applied to identify relationships between sustainability indicators and the structural characteristics of agricultural production. The results reveal pronounced interregional differentiation and an overall predominance of economic over environmental sustainability. Regions with a higher share of family farming demonstrate stronger environmental sustainability and more balanced development patterns, whereas dominance of large-scale enterprises is associated with adverse environmental effects. At the same time, relationships between farm structure and sustainable rural development are weak and not statistically significant, suggesting that social sustainability outcomes depend on more complex and context-dependent mechanisms beyond production scale alone. The findings highlight structural trade-offs between economic efficiency and environmental sustainability and underline the importance of regionally differentiated policy instruments. Strengthening support for family farms is identified as a promising mechanism for improving environmental performance and enhancing upstream conditions for sustainability-oriented sourcing and agri-food value chains. Full article

Ice–snow tourism has become an important development strategy in northern China, but its contribution to urban-rural integration remains uneven. Taking Inner Mongolia as a comparative qualitative case, this study examines how ice-snow tourism can move beyond enclave-oriented development and support inclusive regional development. The analysis draws on policy and planning documents, official reports, media materials, and published secondary studies, and compares Hulunbuir and Tongliao through four common dimensions: space, economy, governance, and culture. On this basis, the paper develops a community-field perspective and connects it with an institution–space–human/land coupling lens. The findings show clear differences in developmental tendency rather than two pure types. Hulunbuir exhibits stronger event-led agglomeration, urban service concentration, and branding capacity, but weaker community benefit capture. Tongliao shows stronger village-level benefit retention, collective participation, and cultural subjectivity, but faces limits in scale linkage and resilience. The paper argues that ice-snow tourism should not be understood as a simple trade-off between efficiency and equity. Instead, a coordinated “pole-community-network” pathway is needed to connect regional growth poles, community-centered governance, and networked collaboration across urban and rural nodes. The study contributes to tourism-led regional development research by clarifying how the community field mediates spatial organization, benefit sharing, and local agency in cold-resource regions. Full article

Non-cohesive earth dams are widely distributed in natural and semi-engineering scenarios, and overtopping-induced breaches are their most catastrophic failure mode. Accurate prediction of the overtopping failure process and breach evolution is critical for risk assessment, emergency management, and dam design optimization. In this study, an improved 3D numerical method is developed to simulate the coupled hydrodynamic–erosion–breach evolution processes of non-cohesive earth dams. The model based on the finite volume method integrates three core modules: a hydrodynamic module based on the Reynolds-Averaged Navier–Stokes equations with the Volume of Fluid method for free surface tracking, a dam material erosion module considering particle entrainment and transport mechanisms of non-cohesive soils, and a breach development module coupling erosion and gravitational collapse. To validate the model, two levels of verification are conducted: first, a classic benchmark dam break case is employed to confirm the feasibility of the hydrodynamic and breach evolution algorithms; second, published flume experimental data of non-cohesive earth dam overtopping failures are adopted to evaluate the model accuracy in predicting breach hydrographs and spatiotemporal evolution of breach geometry. The results demonstrate that the proposed model accurately reproduces the key characteristics of overtopping failure with high fidelity. The predicted breach flow rates and flow depths are in excellent agreement with experimental observations, with relative errors less than 5% for both peak discharge and time to peak. Consequently, this study provides a reliable numerical tool for detailed simulation of non-cohesive earth dam breaches and offers scientific support for emergency management. Full article

Biomimetics in dental restorative materials has gradually shifted from simply copying the appearance of natural teeth to better understanding how those tissues actually behave. Instead of focusing only on aesthetics, there is now more attention on how enamel and dentin function in real conditions, how they respond to stress, interact with their surroundings, and change over time. Because of this, newer materials are no longer just passive fillers; they are being designed to reflect aspects of natural tooth structure, composition, and behavior within the oral environment. This review brings together key ideas in this area, recent developments, and the challenges that remain. One issue that often comes up is how terms like bioinspired, biomimetic, and bioactive are used. They are sometimes treated as if they mean the same thing, but in practice, they point to different goals or levels of complexity in material design. For instance, some studies focus on creating more organized composite structures or mimicking natural mineralization processes, while others focus on antibacterial surfaces or peptide-based approaches that may support remineralization. There is also growing interest in materials that respond to environmental changes, such as shifts in pH or the early stages of wear. Even with promising laboratory results, these materials are not yet widely used in everyday clinical practice. Several issues continue to slow their adoption, including unclear terminology, limited availability of testing models that reflect real oral conditions, and a lack of long-term clinical data. Part of the challenge lies in the lack of consistent terminology, which can make it harder to compare findings across studies. Manufacturing challenges also remain, particularly when scaling up more complex systems. Moving forward, progress will depend on closer collaboration across disciplines, including materials science, oral biology, microbiology, and digital manufacturing. Such efforts will be important for developing restorative materials that behave more like natural tissues and perform reliably over time inside the mouth. Full article

Municipal solid waste incineration bottom ash (MSWIBA) represents both a resource opportunity and an environmental challenge in waste-to-energy systems. This comprehensive review examines MSWIBA’s physicochemical properties, heavy metal behavior, and applications in construction materials, alongside metal recovery techniques and risk mitigation strategies. The research introduces an integrated management framework combining property assessment with coordinated stream processing to reconcile resource recovery with environmental safety. Future studies should focus on advanced analytical methods, hybrid processes, long-term immobilization mechanisms, and life cycle assessment. These innovations aim to transform MSWIBA into a sustainable resource, supporting circular economy principles and low-carbon development. Full article

Background: Severe burn injuries are associated with prolonged consequent wound healing, substantial symptoms burden, and delayed, sometimes incomplete, functional recovery. Photobiomodulation using Multiwave Locked System (MLS) LASER therapy has been proposed as an adjunctive intervention to support tissue repair and thereby improve rehabilitation outcomes, but related clinical evidence in burn populations remains limited. Materials and Methods: This comparative study included 65 patients with severe burn injuries, of whom 35 were prospectively treated with adjunctive MLS LASER therapy, in addition to standard care, and 30 retrospectively identified patients, who received standard care alone, served as controls. The primary outcome was the time until complete epithelialization, while secondary outcomes included: reduction in wound surface, pain intensity, pruritus severity, scar quality, and functional improvements. Assessments were performed at baseline and after a standardized follow-up period of up to 20 days. Results: Patients treated with MLS LASER therapy achieved complete epithelialization significantly earlier than controls (median 40 vs. 73 days, p < 0.001) and demonstrated greater wound area reduction (median 434 vs. 137 cm², p = 0.0012). In multivariable analyses adjusted for burn extent, burn depth, age, and diabetes mellitus, considered as factors worsening evolution, MLS LASER therapy remained independently associated with shorter time to epithelialization and greater reduction in wound dimension. Significant improvements favoring the MLS group were also observed regarding pain, pruritus, scar quality, and functional outcomes, all assessed using specific evaluation tools (p < 0.001). Conclusions: Adjunctive MLS LASER therapy appears to be associated with improved wound healing dynamics and enhanced rehabilitation outcomes in patients with severe burn injuries. These findings should be interpreted with caution given the study limitations, including the non-randomized design and relatively small sample size. MLS LASER therapy may represent a promising adjunctive option in the conservative management of burn injuries; however, further prospective randomized studies are required to confirm these results and to define optimal treatment protocols. Full article