Search Results (402)

Background: African swine fever virus (ASFV) causes a fatal hemorrhagic disease in domestic pigs and wild boars. While live attenuated vaccines (LAVs) provide protection, their use raises safety concerns. Therefore, the aim of the present study was to identify viral B-cell antigens associated with protection and to test their potential using highly immunogenic vaccine delivery platforms. Methods: We employed a microarray of 169 ASFV proteins expressed in a cell-free prokaryotic system to identify immunodominant antigens using sera from immune pigs. Six structural proteins were selected and formulated into AP205 virus-like particles (VLPs). Additionally, replication-defective vesicular stomatitis virus (VSV)-based vaccine candidates expressing glycosylated CD2v and EP153R proteins were generated. Three groups of specific pathogen-free pigs were immunized with either VLP- or VSV-based vaccines and challenged with the virulent ASFV Georgia 2007 strain. Control groups included pigs immunized with the attenuated ASFV Estonia 2014 strain and a naïve group. Results: Most vaccine candidates induced detectable antibody responses against target ASFV proteins. However, neither VLP- nor VSV-based vaccines provided protection, as clinical scores, hematology, cytokine responses, and viremia levels were similar to those in the negative control group. In contrast, only the ASFV Estonia 2014 strain elicited a robust T-cell response and protective immunity. Conclusions: These findings highlight the challenges in identifying protective B-cell antigens of ASFV and emphasize the pivotal role of cellular immunity in mediating protection. Full article

Investigating the influence of landscape evolution on river eutrophication is critical for optimizing spatial patterns to improve water quality. Machine learning (ML) models can capture the complex relationship between landscape metrics and water quality, but their black-box property restricts the interpretability of the underlying mechanisms and makes it difficult to forecast future trends in water quality. To address this, we developed a novel framework that, for the first time, couples an interpretable ML model with the Patch-generating Land Use Simulation (PLUS) model for eutrophication index (EI) prediction. This approach elucidates the response of river eutrophication to landscape dynamics and forecasts future river EI trends. The random forest regression (RFR) model outperformed other algorithms in quantifying these relationships (R² = 0.934 for training, 0.711 for testing). SHAP analysis revealed that landscape metrics contributed 81.78% to the river EI, far exceeding climate factors (18.22%). Consequently, landscape evolution emerged as the dominant explanatory factor. Scenario simulations indicated that while the ecological protection (EP) scenario effectively mitigates river eutrophication, the urban development (UD) scenario significantly exacerbates it. Specifically, under the UD scenario, the average EI in urban sub-watersheds is projected to reach 60.78 by 2040, approaching heavy eutrophic levels. Our findings inform spatial optimization strategies for river eutrophication management and facilitate the design of targeted, localized water ecological protection policies in subtropical monsoonal basins. Full article

Lightweight concrete incorporating expanded polystyrene (EPS) remains an active area of research due to its potential to produce more sustainable resource-efficient construction materials. However, identifying the optimal mix design for EPS-infused concrete typically requires extensive experimental trials, resulting in significant time, cost, and material consumption. To address this challenge, this study proposes an artificial neural network (ANN) predictive model with 5-fold cross-validation to estimate compressive strength performance and to develop mix design recommendations based on actual and predicted results. A total of 55 experimental samples were prepared and grouped into 11 batches, with the EPS volume replacement levels ranging from 0% to 50% at 5% increments. Model performance was evaluated using mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), coefficient of determination (R²), and scatter index (SI), with graphical representations like predicted vs. actual plots, response plots, and residual plots, and the results were benchmarked against a multiple linear regression (MLR) model. Among the tested configurations, the 4-5-1 ANN model demonstrated the highest predictive accuracy. Furthermore, a Shapley (SHAP) analysis was conducted to interpret the model behavior and determine the relative importance of the input variables. The findings reveal that EPS content had the greatest influence on compressive strength prediction, followed by slump value, then gravel content, and finally concrete density. Full article

This work presents a method to encapsulate plant extracts within a binary polysaccharide carrier and to characterize the physicochemical and rheological performance of the resulting biocomposites in the context of food use. Using a starch/psyllium matrix, extracts from Sambucus nigra (SN), Aronia melanocarpa (AM), and Echinacea purpurea (EP) were effectively protected and incorporated through a stepwise workflow encompassing matrix preparation, encapsulation, structural verification, and functional assessment. SEM revealed a porous network containing uniformly distributed, extract-loaded spherical structures (~800–1500 nm), while FTIR supported the presence of hydrogen bonding and hydrophobic interactions that contributed to system stability. The prepared nanoemulsions showed shear-thinning (pseudoplastic) behavior, indicating favorable processing characteristics, whereas most physicochemical and bioactivity measurements were performed on lyophilized composites. The dried materials preserved extract-specific color signatures (ΔE > 5) and exhibited distinct thermal responses: AM produced a pronounced plasticizing effect (Tg reduced by >20 °C), while the incorporation of extracts generally delayed thermal degradation, consistent with polyphenol–starch interactions. Phase-transition behavior was also altered, with melting peaks suppressed for SN and AM and melting temperatures lowered for EP. Surface analysis indicated increased hydrophobicity and a reduced polar component of surface free energy, suggesting improved moisture barrier potential. Antioxidant capacity closely tracked total phenolic content (r > 0.94), with caffeic acid contributing strongly, particularly in EP-based systems. Antimicrobial activity depended on extract type (broad-spectrum for EP, selective for SN, minimal for AM), and the comparatively higher sensitivity of Gram-negative bacteria points to improved phenolic availability and membrane interactions upon encapsulation. Collectively, these results highlight the starch/psyllium matrix as a flexible platform for stabilizing plant extracts while enabling tunable functional attributes for functional food applications. Full article

Plastic microfibers (PMFs) increasingly accumulate in wastewater treatment plants, impairing sludge dewatering and raising operational costs. This study combines a bibliometric analysis (2000–2025) with a critical review of the recent mechanistic literature to map the evolving research landscape on PMF–extracellular polymeric substance (EPS) interactions. The bibliometric trajectory (R² = 0.9786) underscores a paradigm shift towards a molecular understanding of the sludge matrix. Our synthesis of recent experimental studies reveals that PMF-induced interference is often driven by the selective adsorption of hydrophobic extracellular proteins, with one study reporting up to 32.5% sequestration. This has been linked to deteriorated dewatering, such as a 45% increase in capillary suction time (CST) under controlled conditions. Proteomic studies have identified more than 40 extracellular proteins with altered expression, directly linking PMFs to impaired sludge rheology. However, this review critically assesses the underlying evidence, highlighting significant methodological heterogeneity, a lack of standardized protocols, and a reliance on laboratory-scale models as key limitations that prevent broad generalization. By identifying these gaps, this work reframes the PMF–EPS research agenda, emphasizing the need for harmonized methods and multi-omics integration to transform mechanistic insights into robust biotechnological solutions for sustainable sludge management within a circular bioeconomy. Full article

Residential buildings in Erbil City are increasingly facing challenges due to climatic extremes, rapid urbanization, and inadequate insulation practices. This study investigates the effects of insulation material type and placement on the thermal performance of external walls in both newly constructed and refurbished houses under the hot semiarid climate (BSh). Using integrated environmental solutions virtual environment (IES-VE) simulations, various wall systems—concrete, brick, and lightweight block—were assessed with different insulation types (expanded polystyrene (EPS), extruded polystyrene (XPS), rock wool (RW), and mineral wool (MW)) applied either internally or externally. Field surveys combined with numerical simulations demonstrated that external insulation significantly enhances thermal mass without diminishing insulation effectiveness, leading to greater energy savings and improved indoor comfort. Among all configurations, externally applied XPS on concrete and lightweight block walls achieved the highest resistance values (R-values) and the greatest reductions in heating and cooling loads. The results indicate that prioritizing the placement of external insulation can support the development of more energy-efficient and climate-responsive housing policies in Erbil. This research offers evidence-based recommendations for optimizing building envelope design in similar climatic contexts. Full article

Granular materials subjected to complex stress histories exhibit pronounced path dependence, multi-scale heterogeneity and scale-invariant characteristics, especially when particle breakage leads to gradation evolution with fractal features. Discrete element simulations are performed on granular assemblies with prescribed idealized fractal gradations under constant stress ratio loading–turning paths, while maintaining identical solid volume and initial relative density. The results show that, for a given gradation, both the peak strength envelope and the critical state line exhibit high consistency and are effectively independent of the examined stress paths, which are supported by high R² values from regression. At the critical state, microstructural parameters together with energy measures consistently follow stable power–law relationships with mean effective stress. For different gradations, the critical stress ratio remains nearly unchanged, whereas peak strength increases with increasing fractal dimensions; although critical state points remain nearly collinear in the deviatoric stress (q) –mean effective stress (p) plane, the critical state line in void ratio (e)–p plane shifts downward as the particle size distribution becomes broader. The evolution of microstructural and energy-related power–law relationships with fractal dimension exhibits a clear saturation trend. This study demonstrates that, within the simulated framework, fractal gradation primarily governs the position of the critical state in e–p space without altering its fundamental path-independent nature, providing fundamental insights into the multi-scale mechanics of graded granular materials under complex loading. Full article

Biological soil crusts (BSCs) are critical ecological components in arid lands. Their formation and stability hinge on the assembly and interactive networks of cyanobacteria-led bacterial communities. Yet, how different functional cyanobacteria shape the underlying microbial structure and assembly rules is poorly understood. Here, we cultivated artificial algal crusts using two representative cyanobacteria: the nitrogen-fixing Leptolyngbya sp. and the non-nitrogen-fixing Microcoleus vaginatus (M. vaginatus CM01). A total of six treatments were established based on the presence or absence of spraying with in situ BSCs leachate: a control group without inoculation of algae or bacteria (soil, S); a treatment group sprayed only with bacterial suspension (soil + bacteria, SB); a treatment group sprayed only with M. vaginatus CM01 (soil + M. vaginatus CM01, SM); a treatment group co-inoculated with both BSCs leachate and M. vaginatus CM01 (soil + M. vaginatus CM01 + bacteria, SMB); a treatment group inoculated only with Leptolyngbya sp. CT01 (soil + Leptolyngbya sp. CT01, SL); and a treatment group co-inoculated with Leptolyngbya sp. CT01 and biocrust leachate (soil + Leptolyngbya sp. CT01 + bacteria, SLB). By integrating 16S rRNA gene sequencing, neutral community modeling (NCM), and structural equation modeling (SEM), we dissected differences in Cyano-BSCs development, bacterial community composition, co-occurrence networks, and assembly mechanisms. Inoculation with M. vaginatus CM01 (SM, SMB) superiorly promoted Cyano-BSCs development: the SM group achieved the highest coverage (23.33%), while the SMB group showed marked increases in organic matter (OM, 4.10 g·kg⁻¹) and chlorophyll a (Chla, 13.40 μg·g⁻¹), alongside a >5-fold rise in bacterial, cyanobacterial, and nitrogen-fixation gene abundances versus controls. The mechanism centers on extracellular polymeric substances (EPS) secreted by M. vaginatus, which homogenized the microenvironment, suppressed stochastic bacterial dispersal (NCM, SM: R² = 0.698), and enhanced deterministic selection. This process forged a highly cooperative network (89.74% positive links, average degree 34.71) that directionally enriched Cyanobacteria (relative abundance 40.40%). The Shannon index of Cyano-BSCs from the group (SMB) reached 7.72 ± 0.09, reflecting high microbial community diversity. SEM confirmed M. vaginatus directly regulated bacterial assembly (path coefficient = 0.59, p < 0.05) and indirectly improved the soil environment (path coefficient = 0.64, p < 0.05), establishing a “cyanobacteria-community-environment” feedback loop. Conversely, the Leptolyngbya sp. groups (SL, SLB), despite enriching nitrogen-fixing bacteria and fungi, exhibited low carbon fixation efficiency (notably 1.26 g·kg⁻¹ OM in SL) and lack of EPS; communities remained stochastic (NCM, SL: R² = 0.751) with no effective regulatory pathway—a pattern mirrored in S and SB groups. Our findings demonstrate that M. vaginatus acts as a core engineer of biological soil Cyano-BSCs formation via an “EPS-mediated habitat filtering—functional group enrichment—cooperative network assembly” cascade, enforcing deterministic community construction. Leptolyngbya sp., with limited niche-constructing ability, fails to exert comparable control. This work provides a targeted framework for the artificial restoration of Cyano-BSCs in arid zones. Full article

The paper presents an analysis of the status and development trends of Polish Waste-to-Energy (WtE) installations in the context of improving the level of energy recovery measured by the R1 indicator of the Waste Framework Directive (R1 is a regulatory indicator of the R1/D10 classification, not the thermodynamic efficiency of the installation). Based on the standardised annual operating energy balances of six mature municipal waste incineration plants from 2020 to 2024 and partial data for 2025, electricity and heat production, auxiliary media consumption and waste fuel parameters were compared, and R1 was calculated in the Ep, Ef, Ew and Ei systems. The R1 values were then compared with heat collection conditions and modernisation implementations (integration with the heating network, exhaust gas condensation, advanced control/predictive algorithms), treating the ‘before/after’ comparisons as an observational assessment, without inferring strict causality. The average R1 for the facilities studied in 2020–2024 was 0.864, with the highest values recorded for installations in Kraków (R1 = 1.123 in 2024). The results indicate that a high and growing R1 is primarily associated with cogeneration and stable heat management in district heating systems, and that upgrades aimed at additional heat recovery and process stabilisation can further support this trend, in line with the ‘energy efficiency first’ principle. A novelty of the study is the standardised, long-term benchmarking of full-scale data for six installations using a uniform R1 methodology. Full article

Expanded polystyrene (EPS) concrete, with excellent properties such as light weight, thermal insulation, and soundproofing, is widely applied in construction engineering. However, its complex heterogeneous internal structure makes it difficult to quickly and accurately assess compressive strength. Existing testing methods struggle to meet the real-time demands of on-site quality control in terms of both operational efficiency and accuracy. To address this, the present study proposes a method for predicting the compressive strength of EPS concrete based on image processing and Deep Convolutional Neural Networks (DCNN). By constructing a dataset consisting of 5600 preprocessed concrete slice images and addressing the issue of parameter redundancy in fully connected layers, the Broad Learning System (BLS) was employed to reconstruct and optimize the network architecture, thereby improving computational efficiency and enhancing prediction accuracy. The experimental results indicate that after introducing the BLS and related training optimization mechanisms, the training time was reduced by approximately 15%. Among all models, the BLS-Xception model performed the best, requiring only 1.9 s per training image. The coefficient of determination (R²) on the test set reached 0.95, representing an 18.7% improvement over traditional models. The study also indicates that the appropriate incorporation of coal ash, silica fume, and mineral powder significantly enhances the compressive strength of EPS concrete, with smaller EPS particles contributing more substantially to strength improvement. The model demonstrates excellent accuracy and reliability in predictions, providing an effective method for the rapid, non-destructive evaluation of the compressive strength of EPS concrete on construction sites. Full article

This study investigated the diversity and functional potential of lactic acid bacteria isolated from traditional lamb rennet, cheese, and whey collected from seven artisanal sheep farms in southern Romania. A total of 31 samples were analyzed, yielding 118 Gram-positive, catalase-negative isolates. Following dereplication by rep-PCR and 16S rRNA gene sequencing, 63 unique strains were identified across nine genera, with Lactiplantibacillus, Lactococcus, and Leuconostoc being the most prevalent. Strain distribution varied by sample type and manufacturer, with rennet and whey showing greater species diversity than cheese. Technological characterization showed strain-dependent differences in acidification and growth in cow’s and goat’s milk. Genetic screening revealed a high prevalence of functional genes such as ribA, gad, and α-amy, while genes associated with bacteriocin (nisA, pln) and folate (folK) production were less common. Most strains carried multiple functional genes, indicating a genetic potential for diverse functional traits. Antibacterial activity assays demonstrated that nearly all strains inhibited at least three indicator pathogens, with ten strains, particularly Lactiplantibacillus plantarum and Lactococcus lactis strains, exhibiting strong inhibitory effects. Bacteriocin production was confirmed for three Lact. lactis strains. Exopolysaccharide (EPS) production was confirmed in two strains, with yields varying by growth medium and sucrose supplementation. Overall, the results underscore the rich microbial diversity and promising biotechnological potential of LAB from traditional Romanian dairy ecosystems, supporting their use in food fermentation and functional product development. Full article

To address the growing problem of electromagnetic pollution, the development of intelligent, multifunctional electromagnetic shielding materials is essential. The objective of this work is to fabricate an intelligent, low-reflection and high-absorption electromagnetic shielding composite via direct ink writing. In this study, epoxy resin (EP) was employed as the matrix, with nickel powder (Ni), multi-walled carbon nanotubes (MWCNTs), and silver powder (Ag) serving as functional fillers. Direct-ink printing enabled the fabrication of uniformly structured composites and layered gradient-structured composites. By precisely varying the filler content through layer-by-layer printing, the gradient-structured composite exhibited an increasing electrical conductivity gradient and a decreasing magnetic permeability gradient along the direction of electromagnetic wave incidence. Comprehensive characterization of microstructure, electrical, magnetic, and dielectric properties, and electromagnetic shielding effectiveness revealed that the uniformly structured composites exhibited higher total shielding effectiveness (SE_T) and reflection coefficient (R) with increased electrical conductivity. The layered gradient-structured composite achieved an electrical conductivity of 5.44 S/m and an SE_T of 17.74 dB, with the R value reduced to 0.53. Compared to the highly conductive homogeneous composite used in the bottom layer (R = 0.87), this represents a reduction in reflectivity of approximately 39.1%, thereby mitigating secondary pollution from excessive reflection. Under a DC voltage of 200 V, all composites recovered their original shape within 63 s, with shape fixity (R_f) and recovery (R_r) ratios exceeding 92%. This strong shape memory capability supports conformal coating on complex devices and facilitates material recycling, offering a practical foundation for next-generation multifunctional electromagnetic shielding materials. Full article

Microwave-assisted heating (MWH) has established itself as a transformative and energy-efficient paradigm for advanced materials processing. This review provides a comprehensive overview of the advances achieved at the CNR-SCITEC laboratories in Genoa. In this context, a customized microwave platform has been strategically employed for the synthesis, sintering, foaming, and melting of diverse inorganic, organic, and hybrid systems. The spectrum of materials investigated includes superconducting magnesium diboride (MgB₂), hydroxyapatite-based scaffolds, polyethylene components obtained via microwave-assisted rotational molding, cork-based sound-adsorbing composites, recycled expanded polystyrene (rEPS) panels, and polyvinylidene fluoride (PVDF) piezoelectric films. Across the case studies, MWH demonstrated a superior capacity for reducing energy consumption and processing times while maintaining—or even enhancing—the target functional properties. Furthermore, this work evaluates the technological maturity and emerging market opportunities of microwave-based processing, positioning it as a key and sustainable platform for next-generation materials development. Full article

This study aimed to investigate the effects of r-type exopolysaccharides (EPSs) produced by the symbiotic bacteria Rhizobium tropici on soil aggregate formation and stability in loess sandy soil and to elucidate the independent and synergistic roles of EPSs in soil structure development. Experiments were conducted under both sterile and non-sterile soil conditions to distinguish the direct effects of EPSs from their interactions with indigenous soil microorganisms. Soil samples were treated with varying concentrations of EPSs and compared with untreated controls after undergoing a simulated weathering process. Aggregates were classified into four size fractions: <53 μm, 53–250 μm, 250–2000 μm, and 2000–5000 μm. Aggregate distribution and soil stability indicators, including the percentage of water-stable aggregates larger than 0.25 mm, mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (D), were analyzed. EPS application significantly promoted the formation of larger soil aggregates (>53 μm), with approximately 80% increases in the number of aggregates in the 53–250 μm and 2000–5000 μm fractions compared to the control. Soil stability was markedly enhanced, with a 41.7% increase in >0.25 mm water-stable aggregates, a 36.4% rise in MWD, and a 0.3% increase in GMD. The D decreased by 1.2% under 0.2‰ EPS treatment, indicating a more ordered soil structure. EPSs play a key role in promoting soil aggregate formation and enhancing soil stability. While microbial presence has a limited short-term effect on aggregation, the synergistic interaction between microorganisms and EPSs over time significantly enhances soil stability. This study provides new insights into understanding the independent and synergistic roles of EPSs in soil structure formation. Full article

Artificial cyanobacterial crusts (ACCs) are a potentially effective biological strategy for combating desertification. However, while functional microorganisms influence ACCs formation efficiency, research on their role is limited, and their underlying promotion mechanisms remain unclear. Here, we investigated the effects of three functional synthetic microbial communities (SynComs), each dominated by microorganisms specialized in exopolysaccharide (EPS) production (3 strains), siderophore production (3 strains), or nitrogen fixation (4 strains), on ACCs formation following inoculation with Microcoleus vaginatus. This study was carried out in a controlled laboratory setting with a 12 h light/dark cycle and a light intensity of 2400–2700 lux. Following a 24-day cultivation period, EPS-producing or nitrogen-fixing SynComs significantly increased the chlorophyll-a content by 16.0–16.3%. Except for the nitrogen-fixing bacteria treatment, other SynComs enhanced the soil organic matter content of ACCs by 9.1% to 27.3%. The content of EPS was significantly improved by all three SynComs by 14.1~19.2%. Urease activity rose by 6.7% when siderophore-producing bacteria were added. The impacts of SynComs on ammonium nitrogen (NH₄⁺-N) showed different temporal dynamics: nitrogen-fixing SynComs significantly increased NH₄⁺-N early (≤10 days), while EPS-producing and siderophore-producing SynComs enhanced accumulation later (17–24 days). SynComs inoculation markedly accelerated cyanobacterial and general microbial colonization and growth. In comparison to day 0, the 16S rRNA gene copy number of ACCs increased by 24.1% and 43.0%, respectively, in the EPS-producing and nitrogen-fixing SynComs. Additionally, correlation analysis showed that SynComs transformed the weak correlations in the control into a strong positive correlation between NH₄⁺-N and both Chl-a and microbial biomass. Our findings demonstrate SynComs, particularly the EPS-producing or nitrogen-fixing SynComs, enhance ACCs formation through elucidated mechanisms, providing a theoretical basis for optimizing ACCs-based desertification control strategies. Full article