Search Results (979)

This study presents the Multi-dimensional Flood Vulnerability Index (M-FLOVI), calculated by using an index-based method specifically tailored to capture the impact of nature-based solutions (NbSs) on vulnerability. It aggregates five vulnerability dimensions (physical, economic, environmental, social and institutional) into a single index within a multi-level framework. Each dimension is calculated from a set of indicators that can be computed with moderate data demands. These calculations generally require information about buildings, infrastructure, land cover, population, protected areas and cultural heritage, which can partly be obtained from open-access data. M-FLOVI ranges between 0 and 1, and it can be readily mapped and combined with flood hazard to produce flood risk maps. This paper elaborates a step-by-step M-FLOVI calculation in the Tamnava River Basin, Serbia, where various NbSs were proposed. Under the baseline conditions, most of the study area exhibits either moderate (83.5%) or low vulnerability (15.8%). These NbSs decrease future vulnerability in 6.6 km² (1.34%) of the study area. Afforestation (0.59%) and retention ponds (0.42%) decrease environmental vulnerability, while flood plain restoration (0.33%), which is expected to create a protected bird habitat, increases environmental vulnerability. These results suggest that M-FLOVI can effectively capture NbSs’ impacts on future vulnerability to floods. Full article

Aronia melanocarpa puree is rich in anthocyanins and proanthocyanidins, but its pronounced tannin-derived astringency limits product acceptance. This study developed a non-removal astringency-modulation strategy using food-grade L-proline and evaluated its molecular basis, processing window, and quality effects. Ultraviolet–visible (UV–Vis) and Fourier-transform infrared (FT-IR) spectroscopic analyses suggested that L-proline altered the local microenvironment of procyanidin B2 (PC-B2) through hydrogen bonding, hydrophobic association, and molecular packing rearrangement, without evident disruption of the PC-B2 aromatic skeleton. In a PC-B2–bovine serum albumin model, an appropriate L-proline level reduced the protein precipitation rate from 45.3% to 31.2% and increased soluble phenolic retention, suggesting weakened polyphenol–protein precipitation. The strategy was then optimized in puree using machine learning-assisted multi-response analysis and Box–Behnken validation. The recommended condition was 150 mg/100 mL L-proline at 40 °C for 60 min, yielding a deastringency rate of 36.13%, with anthocyanin and vitamin C retention rates of 88.80% and 55.56%, respectively. The optimized treatment maintained red color, colloidal dispersion, and shear-thinning behavior; increased the anthocyanin digestion retention index from 50.0% to 87.4%; and improved overall sensory acceptance from 4.17 to 8.17. These findings support L-proline-mediated microenvironmental modulation as a mild processing approach for high-tannin cloudy berry products. Full article

NAD⁺ depletion is a defining feature of the aging cell, driven by a progressive decline in nicotinamide phosphoribosyltransferase (NAMPT) activity, the rate-limiting enzyme of the NAD⁺ salvage pathway. Pyrroloquinoline quinone (PQQ), a plant-derived redox-active quinone cofactor, elevates intracellular NAD⁺ by a mechanism that remains incompletely understood. We employed an integrated in silico approach combining molecular docking, density functional theory (DFT), and 100 ns molecular dynamics (MD) simulation to evaluate whether PQQ directly targets NAMPT. Docking against the NAMPT crystal structure (PDB: 7ENQ) yielded a binding free energy of −9.4 kcal/mol, with PQQ positioned in the allosteric activation site and forming hydrogen bonds at His191, Asp219, and Val242 together with π–π stacking at Tyr188, extending a known synthetic activator pharmacophore to a dietary ligand class. MM-GBSA analysis yielded binding free energy = −31.2 kcal/mol, confirming dominant electrostatic and van der Waals stabilization. In silico alanine mutagenesis of Tyr188 and Val242 reduced binding affinity to −7.2 and −7.0 kcal/mol respectively, with complete loss of allosteric-site contacts, validating the proposed mechanism computationally. DFT analysis revealed a HOMO–LUMO gap of 3.20 eV and electrophilicity index ω = 8.91 eV, consistent with non-covalent binding to nucleophilic residues. MD simulation confirmed retention of PQQ within the allosteric site over 100 ns. These data provide a structural and electronic framework for the NAD⁺-boosting activity of PQQ and a rationale for experimental validation. Full article

Encapsulation serves as a critical strategy for the preservation of sensitive bioactive compounds, ensuring their stability and functionality within complex food matrices. Cellulose nanocrystals (CNCs) upcycled from by-products are being favoured as wall materials because they offer a sustainable yet powerful solution for maintaining compound stability. This study evaluated the encapsulation of fish oil (FO) within a nanocomposite matrix of garlic skin-derived cellulose nanocrystals (GCNCs) and soy protein isolate (SPI). The synergistic effects of FO loading and GCNC:SPI ratios on the microcapsules’ structural, physicochemical, and digestive properties were investigated. Higher FO loading significantly reduced the moisture content of the resulting microcapsule powders while increasing bulk and tapped densities by minimising internal porosity. Microstructural analysis showed irregularly shaped agglomerates. Higher FO loading also increased surface oil retention and inter-particle adhesion of the microcapsule powders; however, elevated SPI levels effectively counteracted these effects. Colour analysis further revealed that higher FO loading reduced powder lightness (L*) and increased yellowness (b*), while greater GCNC content positively influenced redness (a*). The formulation containing 10% FO, 3% GCNCs, and 7% SPI was identified as the optimal treatment. This ratio achieved the highest encapsulation efficiency (65.77% ± 1.10) and demonstrated superior flowability, characterised by the lowest Carr’s Index (20.65% ± 0.29) and Hausner Ratio (1.23 ± 0.05). Additionally, it maintained oxidative stability, with TBARS values (2.42 ± 0.08 mg MDA/kg oil) remaining consistently below the established 3 mg MDA/kg threshold. Fourier Transform Infrared Spectroscopy confirmed the successful entrapment of FO within the GCNC–SPI matrix. According to the in vitro digestion assays, the wall material provided a durable barrier in acidic media because the gastric release (28.04–55.28%) was significantly lower than the intestinal release (64.38–77.62%). The predominant fatty acids identified in both encapsulated and unencapsulated products were myristic acid (saturated fatty acid), elaidic acid (monounsaturated fatty acid), and docosadienoic acid (polyunsaturated fatty acid). Superior nutritional quality index (NQI) values in the encapsulated samples underscore the effectiveness of the wall material in providing a critical defence against fatty acid degradation and preserving overall oil quality. These findings suggest that the GCNC/SPI binary system is a highly effective delivery vehicle for protecting sensitive polyunsaturated fatty acids in functional food applications. Full article

Soil hydraulic hysteresis—the divergence between drying and wetting trajectories of the water retention curve—encodes quantitative information on soil structural organization that traditional modelling approaches do not explicitly capture. This study introduces the State Resilience Index (SRI), a dimensionless descriptor defined as the normalized area enclosed between the drying and wetting branches of a hysteresis loop and evaluates its interpretive value across five contrasting datasets from the published literature. The datasets encompass compaction gradients, repeated wetting–drying cycles, depth-resolved soil profiles, and water vapor sorption isotherms from soils differing in clay content and mineralogy. SRI values ranged from 0.023 to 0.333, responding consistently to the dominant structural drivers of hysteresis in each system. High values were associated with heterogeneous, structurally complex pore networks characteristic of productive soils; declining values reflected progressive loss of structural memory under compaction, repeated cycling, or mineralogical rigidity. A provisional interpretive framework is proposed, linking SRI ranges to soil structural quality and agronomic potential. The index is dimensionless, model-free, and applicable across measurement domains and forcing regimes, positioning it as a broadly transferable tool for the comparative assessment of soil hydraulic path asymmetry. Full article

Two growth trials were conducted to evaluate the effects of solvent-extracted soybean meal (SBM), low-oligosaccharide soybean meal (LO-SBM), and enzyme-treated soybean meal (ET-SBM) on the growth performance, feed utilization, and gut microbiome of the Pacific white shrimp (Litopenaeus vannamei). Nine diets were tested, including a basal diet using solvent-extracted soybean meal as the main protein source. The solvent-extracted soybean meal was then replaced with LO-SBM or ET-SBM at 40%, 60%, 80%, and 100% on an isonitrogenous and isolipidic basis. In the 8-week outdoor green water trial, all growth metrics, FCR and apparent net protein retention (ANPR) showed no significant differences among diets (p > 0.05). However, there was a significant effect of LO-SBM on phosphorus retention. In the clear water trial, intermediate inclusion levels of LO-SBM (60–80%) slightly improved growth metrics and phosphorus retention (p < 0.05) without affecting protein utilization, while 100% LO-SBM did not provide additional benefits. Diets with ET-SBM showed similar performance; however, phosphorus retention was reduced. Diets did not affect whole-body composition (p > 0.05), except for phosphorus and moisture. Gut microbiota analysis revealed that shrimp fed 100% ET-SBM had notably higher alpha diversity (Shannon index = 5.45, observed species = 326.41) compared to those fed 100% LO-SBM (Shannon index = 4.59, observed species = 242.69), indicating improved microbial stability with ET-SBM. Nonetheless, there were no significant differences in beta diversity or taxonomic composition between treatments (p > 0.05). This study demonstrates that incorporating 60–80% LO-SBM into the diet improves shrimp growth and nutrient utilization. Additionally, ET-SBM may also support shrimp growth, nutrient efficiency, and microbial diversity, suggesting that both LO-SBM and ET-SBM can be beneficial for shrimp nutrition. Full article

Microplastic pollution is an emerging environmental concern in coastal ecosystems, particularly in developing regions. However, research remains compartmentalized, limiting an integrated understanding of microplastic distribution, transport dynamics, and ecological risks across interconnected environmental matrices. In this study, a multi-matrix assessment was conducted to evaluate microplastic abundance, characteristics, and associated ecological risks. A total of 93 microplastic particles were identified, with the mangrove site exhibiting the highest concentration (200 items/kg), while the seagrass bed and estuary showed the lowest concentration (3.33 items/kg). The dominant microplastic type was primarily fiber (55.91%), with most particles ranging from 0.1 to 1 mm, and polypropylene (66.67%) was the predominant polymer type, reflecting the widespread contribution from plastic packaging and fishing gear. Significant correlations were observed between microplastic abundance and contamination factor (CF), pollution load index (PLI), and potential ecological risk index (PERI), whereas the polymer hazard index (PHI) showed no significant relationship due to its dependence on polymer composition. Non-metric multidimensional scaling (NMDS) revealed distinct distribution patterns of microplastic shape and polymer type across matrices. Overall, microplastic distribution across environmental matrices is driven by heterogeneous sources and transport pathways, with mangrove sediments enhancing retention, underscoring the need to elucidate seaward and landward source contribution and coastal fluxes. Full article

Accurate prediction of missing or potential links is crucial for understanding complex network dynamics and supporting applications such as social recommendation and infrastructure planning. To effectively exploit both global and local structural information, this study proposes a spectral-adaptive fusion (SAF) algorithm. SAF first constructs a spectral embedding matrix by retaining a subset of spectral components, from which a row-column normalized matrix and a Gaussian kernel matrix are derived. These matrices are then adaptively fused to produce link scores, using a common-neighbor-based mechanism that dynamically balances their contributions, capturing both local and global network features while mitigating the influence of highly central nodes. Energy retention and spectral gap analyses set the truncated ratio to 5%, resulting in an average runtime reduction of 71.0% across eight datasets. Under the AUC index, SAF achieves an average relative improvement of 2.22% over advanced graph neural network methods and 10.65% over matrix factorization approaches. Importantly, even at low training ratios, SAF maintains AUPR values above 0.91 on four networks and exhibits stable performance on recall, confirming its robustness and effectiveness for link prediction. Full article

Heavy metal pollution poses a significant threat to industrial and agricultural ecosystems; however, thorough research on the coupled risks and migration mechanisms of heavy metals within soil-groundwater systems in arid-region industrial parks remains limited. This study systematically collected 312 surface soil samples and 239 groundwater samples from typical chemical industrial parks in Xinjiang, northwestern China. The pollution levels of six typical heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) were quantitatively evaluated utilizing the Single Pollution Index (P_i), Nemerow Pollution Index (P_N), and Potential Ecological Risk Index (RI) for soil and the improved Heavy Metal Contamination Index (HCI) for groundwater. Additionally, GIS mapping and the Positive Matrix Factorization (PMF) model were integrated to delineate spatial distributions and primary emission sources. The assessment results indicated overall moderate pollution risks for Cd, Cu, and Ni in the soil, and for Cd, Pb, Cr, and Ni in the groundwater. Notably, Cd emerged as the primary risk contributor across both media. The RI identified Cd as the element posing the highest soil toxicity risk (with a mean RI of 53.57), while the HCI revealed that specific industrial zones face severe contamination levels (HCI > 4500), predominantly driven by Cd and Pb. GIS analysis illustrated a distinct distance–decay diffusion pattern emanating from industrial point sources. Crucially, PMF source apportionment demonstrated divergent contamination pathways: surface soil heavy metals (e.g., Cr, Cu, Pb, Zn) were primarily governed by top-down local industrial emissions (52.5%), whereas groundwater contamination was largely dictated by regional groundwater flow carrying mixed agricultural and natural geogenic inputs (75%). Furthermore, Pearson correlation analysis revealed a prevalent weak or negative correlation between heavy metal concentrations in the two media, suggesting a spatial “decoupling” of their contamination pathways. This phenomenon is likely driven by a dynamic “retention-leaching” mechanism within the arid vadose zone, where alkaline pH and high clay content act as a hydrochemical barrier impeding vertical migration. These findings underscore that soil and groundwater in arid industrial regions should be managed as distinct hydrochemical systems, providing a robust scientific basis for targeted remediation and the sustainable redevelopment of industrial brownfields. Full article

Although coconut water is recognized for its desirable sensory appeal and nutritional composition, its broader industrial use is constrained by the rapid deterioration that occurs after extraction. In this study, crossflow microfiltration of coconut water with a silicon carbide membrane was optimized by investigating pressure and temperature through a face-centered design (FCD) and artificial neural network modeling coupled with a genetic algorithm (ANN–GA). Permeate flux and fouling index were used as process responses, and the optimized condition was further examined in terms of hydraulic resistance, fouling behavior, and retention of minerals and primary metabolites. Pressure and temperature affected the process differently: permeate flux showed marked nonlinear behavior, whereas fouling index was governed mainly by pressure. At the sample level, ANN described permeate flux more accurately than FCD (R² = 0.99 vs. 0.96), whereas FCD showed better grouped cross-validated predictivity across unseen pressure–temperature conditions (Q² = 0.85 vs. 0.57). For the fouling index, FCD outperformed ANN in both sample-level fit and grouped validation (R² = 0.95 vs. 0.60; Q² = 0.70 vs. 0.61). Both approaches converged on the same favorable operating window, and experimental validation at 60 kPa and 35 °C yielded 1085.23 ± 23.12 L h⁻¹ m⁻² and 83.56 ± 1.56%. During concentration mode, flux decline was severe but predominantly reversible, with high clean-water permeance recovery after chemical cleaning. Resistance partition and fouling modeling indicated that the main hydraulic limitation was associated with concentration polarization and external cake-layer buildup rather than irreversible membrane damage. The clarified fraction also preserved high transmission of major minerals and relevant primary metabolites, indicating that the selected condition combined high productivity, manageable fouling, and satisfactory nutritional retention. Full article

In soft soil areas, cement–soil mixing piles are widely employed as a building foundation treatment measure, and their construction parameters directly influence pile uniformity and the stability of foundation reinforcement. However, visual and quantitative methods to verify on-site improvement effects are currently lacking. This study aimed to improve the mixing uniformity between jet media and soil layers and proposed a quantitative evaluation method based on numerical simulation and image recognition. Taking the silty soil in the Nansha area in Guangdong Province, China, as the research object, combined with flow tests and discrete element simulations, an experimental simulation based on a linear model of adhesive rolling resistance was established. First, the entire process of the wet water spraying soil mixing method and visualizing particle behavior was simulated. Based on the Danckwerts mixing index, image recognition technology was applied to quantify the uniformity of cement–soil mixing at different rotational speeds. The simulation results revealed that increasing the rotational speed within a certain range (0–100 r/min) significantly improved the uniformity of cement–soil mixing by 33.3%. However, increasing the rotational speed still further (100–200 r/min) resulted in only a 15.8% improvement. Furthermore, excessive rotational speed caused a significant loss of cement within the designed diameter of the pile. Second, based on the cement retention rate inside the pile, a speed balance range suitable for the working conditions of this study was obtained. A good balance was achieved between the effective cement content inside the pile and the uniformity of cement–soil mixing, further ensuring the consolidation effect of the cement–soil pile. Full article

Background/Objectives: The obesity epidemic coexists with the phenomenon of “hidden hunger” (Type B malnutrition)—a micronutrient deficiency amidst a caloric excess. Traditional dietary assessment methods often distort the actual picture by ignoring technological losses during cooking, which necessitates the use of digital tools. Methods: A cross-sectional study (N = 3267) was conducted using the digital platform “NIAP”. The analysis was based on valid 3–7-day dietary records with algorithmic accounting for nutrient retention factors during thermal processing. The nutrient profiles of individuals with a normal body mass index (BMI) and obesity (BMI ≥ 30 kg/m²) were compared. Results: The epidemiology of intake shortfalls was highly prevalent and pronounced: 99.9% of the cohort had ≥1 inadequacy (with a mean negative deviation of −77.3% for vitamin D and −59.2% for Omega-3), and 61.5% exhibited ≥10 simultaneous multiple intake shortfalls. These inadequacy rates remained robust in a sensitivity analysis excluding under-reporters. The obesity group consumed significantly more energy, saturated fatty acids, added sugars, cholesterol, and sodium, but demonstrated a lower relative macronutrient intake (g/kg of body weight). Absolute fiber intake did not differ between the groups, indicating a decrease in its density per 1000 kcal in the diet of individuals with obesity; the intake of Omega-3 polyunsaturated fatty acids (PUFAs) showed a downward trend. The Na:K ratio was significantly higher in the obesity group (1.19 vs. 1.04, p < 0.001). Correlation analysis confirmed an inverse relationship between BMI and the overall nutrient density of the diet. Conclusions: A high-energy diet does not compensate for systemic micronutrient inadequacy among the evaluated cohort. Obesity is associated with a dietary imbalance favoring “empty calories” and pro-inflammatory components against a background of severe multiple dietary inadequacies. The integration of algorithmic dietary assessment that accounts for cooking losses is critical for objective diagnosis and personalized nutritional intervention. Full article

Soil water availability, salinity dynamics, and nitrate transport are key factors controlling agricultural sustainability in arid environments characterized by limited water resources and high evaporative demand. This study evaluated the combined effects of soil texture, nitrate–nitrogen application, and sawdust mulching on soil water retention, evaporation losses, salinity redistribution, and nitrate movement in loamy sand and sandy clay loam soils under controlled greenhouse conditions. Results showed that soil texture was the dominant control on hydrochemical behavior, with sandy clay loam exhibiting higher water retention and lower drainage than loamy sand. Sawdust mulching significantly improved soil water conservation by reducing evaporation and stabilizing moisture distribution, while the 4 cm mulch treatment achieved the highest overall CSI performance. Evaporation strongly governed salinity accumulation in surface layers, whereas mulching reduced salt build-up and promoted a more uniform salinity profile. Nitrate transport closely followed water fluxes, resulting in higher leaching in loamy sand and greater retention in sandy clay loam. Increasing nitrogen application enhanced nitrate mobility and leaching in both soils. A Composite Sustainability Index (CSI) was developed to integrate soil water conservation, evaporation reduction, salinity control, and nitrate retention into a unified metric. Sensitivity analysis demonstrated that treatment rankings were largely unaffected by alternative weighting schemes, confirming the robustness of the CSI framework. The CSI identified mulch application, particularly the 4 cm mulch treatment, as the most effective management option based on overall sustainability performance. The CSI framework provides an integrated decision-support tool for evaluating coupled water–salt–nitrate interactions and improving water use efficiency and salinity management in arid agricultural systems. This study offers a novel integrated CSI-based framework for simultaneously quantifying hydrological and hydrochemical soil responses under mulch management in arid environments. Full article

Background/Objectives: Retention of healthcare professionals in the workforce, their employment, and the improvement of working conditions largely depend on identifying the factors that influence their departure and their health. The study was conducted during the period from January to June 2021. This study aimed to examine the association between specific work-related stressors and work ability. The initial hypothesis was that general and specific occupational stressors negatively associate with work ability among healthcare professionals in emergency medical intervention teams. Methods: The study was designed as a cross-sectional comparative study. It was conducted among nurses and physicians in pre-hospital emergency medical services, employed full-time in intervention teams, while the control group consisted of employees from dispatch and call-receiving units. The study was conducted on the 840 participants, representing 43.3% of all healthcare professionals employed in pre-hospital emergency medical services in the Republic of Croatia. In addition to questions on participants’ personal characteristics, the following instruments were used: 1. a validated Questionnaire on Workplace Stressors among hospital healthcare professionals; and 2. the international standardized Work Ability Index (WAI) questionnaire for assessing work ability. Participants completed the questionnaires in paper form. Results: On average, the participants demonstrated lower levels of stress compared to reference values, both for overall stress and for individual stress factors, while their work ability, assessed using the Work Ability Index (WAI), ranged from very good to excellent. The control group showed higher levels of stress across all factors and lower work ability. However, the control group was older on average, generally had lower levels of education, and consisted more often of women—personal characteristics that may influence the examined variables. Lower stress levels and better work ability were associated with job satisfaction, ambition, and the fact that participants were working in their desired profession. Frequent sick leave (absenteeism) was highly correlating with both higher stress levels and poorer work ability. Conclusions: Greater job satisfaction and higher motivation have a positive impact on stress levels and employees’ work ability. The study results can serve as a starting point for institutional management in designing feasible decisions aimed at improving satisfaction, health, the work environment, and the work ability of emergency medical service personnel, as well as making these institutions more attractive for recruitment and retention of employees both in their positions and within the profession. Full article

Objectives: Local positioning systems (LPSs) used in indoor team sports generate a large number of external load variables, often exceeding practical monitoring capacity. The redundancy and overlap among these variables make it difficult to identify the most informative metrics for performance analysis and load management. This study aimed to reduce the dimensionality of external load variables derived from LPS data and to identify data-driven external-load observation profiles using principal component analysis and clustering techniques. Methods: A total of 188 observations from indoor team sports (basketball, handball, and futsal) were analyzed. Continuous external load variables were standardized and subjected to principal component analysis (PCA), with component retention based on a ≥90% cumulative explained variance threshold. K-means clustering was applied in both the full standardized feature space and the PCA-reduced space. The optimal number of clusters was determined using silhouette analysis and the elbow method. Agreement between clustering solutions was assessed using Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). Cluster characteristics were further examined using descriptive statistics and variable separation analysis. Results: The first two principal components explained 53.7% of the total variance, representing high-intensity external load and neuromuscular load dimensions, while 12 components were required to exceed 90% cumulative explained variance. Clustering analysis consistently identified three moderately separated clusters in both the full and PCA-reduced spaces. The PCA-based solution demonstrated improved separation (silhouette = 0.362) compared to the full-space solution (silhouette = 0.319). Agreement between clustering approaches was high (ARI = 0.981; NMI = 0.971), indicating that dimensionality reduction largely preserved the main clustering structure within the analyzed dataset. The most discriminative variables included jump load, acceleration load, metabolic power, and anaerobic activity distance. Conclusions: A large set of external load variables can be reduced into interpretable latent dimensions that support exploratory external-load profile identification. The combination of PCA and clustering provides an exploratory and structure-preserving framework for summarizing complex external-load datasets and identifying latent load dimensions. These findings may assist future monitoring strategies; however, the practical utility of the identified profiles requires prospective validation before implementation in training-load management. Full article