Search Results (217)

This research examines how influencer information spreads and is accepted by consumers, focusing on a Tunisian sample of social media users, and how these effects percolate into consumers’ perception of the quality of cosmetic products. Drawing on the Information Adoption Model (IAM), this study develops a conceptual framework adapted to the social media landscape, particularly the TikTok platform. To test this framework, we conducted a survey targeting 285 consumers using a non-random sampling frame, primarily through Facebook and Instagram. The findings suggest that consumers perceive influencer information as useful when they believe it is credible and of high quality. Interestingly, while high-quality information tends to lead to influencer information adoption, credibility alone does not guarantee adoption. Additionally, our study emphasizes the role of influencer information usefulness in driving its adoption. One notable discovery is the link between influencer information adoption and consumers’ perceptions of the quality of cosmetic products. However, this correlation does not hold equally for both genders, thus suggesting a moderation effect between gender and influencer information processing in this context. Full article

Intelligent transport systems are revolutionising all aspects of modern life, increasing the efficiency of commerce, modern living, and international travel. Intelligent transport systems are systems of systems comprised of cyber, physical, and social nodes. They represent unique opportunities but also have potential threats to system operation and correctness. The emergent behaviour in Complex Cyber–Physical–Social Systems (C-CPSSs), caused by events such as cyber-attacks and network outages, have the potential to have devastating effects to critical services across society. It is therefore imperative that the risk of cascading failure is minimised through the fortifying of these systems of systems to achieve resilient mission assurance. This work designs and implements a programmatic model to validate the value of cascading failure simulation and analysis, which is then tested against a C-CPSS intelligent transport system scenario. Results from the model and its implementations highlight the value in identifying both critical nodes and percolation of consequences during a cyber failure, in addition to the importance of including social nodes in models for accurate simulation results. Understanding the relationships between cyber, physical, and social nodes is key to understanding systems’ failures that occur because of or that involve cyber systems, in order to achieve cyber and system resilience. Full article

Conductive polymer composites (CPCs) are widely used in flexible electronics due to their tunable electrical properties and mechanical deformability. However, accurately predicting the evolution of conductive networks, particularly under compressive strain, remains a significant challenge. In this study, we developed a statistical mechanics model and an extended dynamic statistical mechanics model to quantitatively describe percolation behavior in CPCs. The static model incorporates filler geometry, aspect ratio (AR), and surface-to-volume ratio, and was validated using Monte Carlo simulations. Results show that the percolation threshold for spherical fillers was 0.11965, while significantly lower values of 0.00669 and 0.00203 were observed for plate- and rod-shaped fillers, respectively, confirming the enhanced connectivity of anisotropic particles. To capture strain-dependent behavior, a dynamic model was constructed using a Smoluchowski-type gain–loss framework. This model separates conductive network formation (gain) from network disconnection (loss) caused by filler alignment and Poisson-induced expansion. At high Poisson’s ratios (0.3 and 0.5), the model accurately predicted the reduction in connectivity, particularly for anisotropic fillers. Across all tested conditions, the model exhibited strong agreement with simulation data, with RMSE values ranging from 0.0004 to 0.0449. The results confirm that high AR fillers enhance conductivity under compression, while large Poisson’s ratios suppress network formation. These findings provide a reliable, physically grounded modeling framework for designing strain-sensitive devices such as flexible pressure sensors. Full article

This paper presents a comparative study examining the effects of carbon nanotubes (CNTs) and expanded graphite (EG) on the thermal, mechanical, morphological, electrical, and piezoresistive properties of poly(ethylene-co-methacrylic acid) (EMAA) nanocomposites. To this end, different amounts of carbonaceous fillers (EG and CNTs separately) were added to the EMAA thermoplastic matrix, and the relative electrical percolation thresholds (EPTs) were determined. The effect of filler concentration on thermo-oxidative degradation and the EMAA crystallinity was investigated via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. Dynamic mechanical analysis (DMA) demonstrated that both fillers enhance the Young’s and storage moduli, as well as the glass transition temperature, with a greater improvement for the bidimensional nanofiller, most likely due to the cumulative effect of more extensive EG-matrix interactions. In tensile tests, a very relevant difference was detected in the Gauge Factor (G.F.) and the elongation at break of the two typologies of nanocomposites. The G.F. of EMAA 10% CNT and EMAA 15% EG were found to be 0.5 ± 0.08 and 165 ± 14, respectively, while elongation at break was about 68% for EMAA 10% CNT and 8% for EMAA 15% EG. Emission Scanning Electron Microscopy (FESEM) and Tunneling Atomic Force Microscopy (TUNA) have contributed to explaining the differences between EG- and CNT-based nanocomposites from a morphological point of view, underlying the pivotal role of the filler aspect ratio and its structural features in determining different mechanical and piezoresistive performance. The comprehensive analysis of EMAA-EG and EMAA-CNT nanocomposites provides a guide for selecting the best self-sensing system for the specific application. More specifically, EMAA-CNT nanocomposites with high elongation at break and lower sensitivity to small strains are suitable for movement sensors in the soft robotic field, where high deformation has to be detected. On the other hand, the high sensitivity at a low strain of EMAA-EG systems makes them suitable for integrated sensors in more rigid composite structures, such as aeronautical and automotive components or wind turbines. Full article

The spread of per- and polyfluoroalkyl substances (PFAS) in the environment poses a severe threat to soil organisms, aquatic life, and human health. Many PFAS compounds are mobile and easily transported from soils to groundwater and further to surface waters. Leaching tests are valuable tools for assessing the site-specific leaching behaviour of contaminants. Here, we report the results of an evaluation of two standardized leaching tests for PFAS-contaminated soil materials: the batch test (ISO 21268-2:2019) using either demineralized water or 1 mM CaCl₂ as leachants (liquid-to-solid (L/S) ratio of 10) and the up-flow percolation test (ISO 21268-3:2019) using 1 mM CaCl₂ as leachant. One field-contaminated soil and three spiked (12 PFAS compounds) soils (aged 5 months) were included in the study. Desorption kinetics in the batch test were fast and equilibrium was obtained for all PFAS compounds within 24 h, the prescribed equilibration time. The same solubility was obtained for short-chain PFAS (PFBA, PFHxA, PFHpA, PFBS) in demineralized water and 1 mM CaCl₂, whereas significantly lower solubility was often observed for long-chain PFAS in CaCl₂ than in water, probably due to decreased charge repulsion between soil surfaces and PFAS compounds. In the up-flow percolation test, concentrations of short-chain PFAS in leachates decreased rapidly with increasing L/S, in contrast to long-chain PFAS, where concentrations decreased gradually or remained constant. Solid–solution partitioning coefficients (K_d), calculated from the data of the batch and percolation tests (1 mM CaCl₂), were generally in agreement, although differing by more than three orders of magnitude between different PFAS compounds. Uncertainties and pitfalls when calculating K_d values from leaching test data are also explored. Full article

This study investigates the application of carbon nanotube (CNT)-enhanced epoxy adhesives for localised Joule heating-based curing in composite bonding. The electrical, thermal, and mechanical properties of epoxy with 0.25–1 wt% CNT loadings were evaluated. A simple CNT alignment method using DC voltage showed improved electrical conductivity, greatly reducing the percolation threshold. Transient thermal analysis using finite element modelling of representative volume elements revealed that aligned CNTs led to increased localised temperatures near the CNT clusters. The model was validated with infrared thermal imaging analysis, which also showed similar non-linear heat distribution and more uniform heating under higher CNT loading. Additionally, power distribution mapping was evaluated through inverse modelling techniques, suggesting different conductivity zones and cluster distribution within the single-lap joint. The numerical and experimental results demonstrated that CNT alignment significantly enhanced localised conductivity, thereby improving curing efficiency at lower voltages. The lap shear test results showed a peak shear strength of 10.16 MPa at 0.5 wt% CNT loading, 9% higher than pure epoxy. Scanning electron microscopy analysis confirmed the formation of aligned CNT clusters, and how CNT loading affected the failure modes, transitioning from cohesive to void-rich fracture patterns at a higher wt%. These findings establish CNT-enhanced Joule heating as a viable and scalable alternative for efficient composite bonding in aerospace and structural applications. Full article

This study investigates the effects of different carbon nanomaterials (CNMs), namely, carbon nanotubes (CNTs), carbon nanofibers (CNFs), graphene, and graphite nanoplatelets (GNP) on the mechanical, electrical, and fractural characteristics of cement composites. The electrical conductivity results indicated that CNT- and CNF-added composites exhibited percolation threshold ranges of 0.1% to 0.3% and 0.3% to 1.0%, respectively. Regarding the mechanical properties tests, the composite with a 1.0% CNF showed the best results. Furthermore, fractural characteristics results indicated that even additions of the smallest dosage, i.e., 0.1% of CNM, exhibited positive results. Overall, the study highlighted the potential of CNM-added cement composites. Full article

A new combined analysis of SEM-BSE and EDX images using Aphelion^TM software was proposed to describe the quantitative microstructure (quantity and neighborhood of sacrificial phases) of Al-Zn-Si-(Mg) coatings on steel. Three materials with different Al/Zn ratios and Mg content were analyzed. The quantitative microstructure allowed us to describe their corrosion behaviors in a chloride environment and understand their ranking for sacrificial protection of steel in accelerated corrosion tests. For the analyses, interdendritic Zn-rich or Mg-rich phases were expected to be more sacrificial to steel than Al-rich dendrites. Without Mg (AZ coating), Al-rich dendrites created a percolating network, but interdendritic phases did not, suggesting their sacrificial protection to steel to be very limited. Additionally, significant Zn gradients inside dendrites led to a premature coating consumption on the surface, creating new zones of naked steel. In the coatings with Mg (AZM), sacrificial interdendritic phases created a percolating network, which is expected to improve long-time sacrificial protection and contribute to a more uniform formation of Zn corrosion products. For Al content between 30 wt.% and 45 wt.%, a lowering of the Al/Zn ratio (L-AZM) increased the connectivity of the sacrificial interdendritic phases, which is expected to improve the long-term sacrificial effect. Accelerated corrosion tests of scratches in the steel coatings validated the hypotheses. Full article

This study explores the resistive switching (RS) behavior and conduction mechanisms of Ag/SF-Ag NP/Si memristors with varying Ag NP concentrations. I-V measurements confirm stable RS characteristics across 100 cycles, with consistent set and reset voltages. Increasing Ag NP concentration enhances conductive filament formation, leading to sharper switching transitions and a higher HRS/LRS ratio, w-hich increases from 43 (0 wt% Ag NP) to 4.6 × 10⁴ (10 wt% Ag NP). Log(I)-log(V) analysis reveals a conduction transition from Ohmic to Poole–Frenkel mechanisms, indicating improved charge percolation. Reliability tests show stable LRS values, while HRS exhibits greater variation at higher Ag NP concentrations. These results demonstrate that Ag NPs play a crucial role in optimizing memristor performance, improving switching characteristics, and enhancing reliability. The findings suggest that Ag/SF-Ag NP/Si memristors are promising for high-performance resistive memory and neuromorphic computing applications. Full article

Earthquake activity poses significant risks to both human survival and economic development. However, earthquake forecasting remains a challenge due to the complex, poorly understood interactions that drive seismic events. In this study, we construct an earthquake percolation model to examine the relationships between earthquakes and the underlying patterns and processes in Southern California. Our results demonstrate that the model can capture the spatiotemporal and magnitude characteristics of seismic activity. Through clustering analysis, we identify two distinct regimes: a continuous increase driven by earthquake clustering, and a discontinuous increase resulting from the merging of clusters dominated by large, distinct mega-earthquakes. Notably, in the continuous increase regime, we observe that clusters exhibit a broader spatiotemporal distribution, suggesting long-range and long-term correlations. Additionally, by varying the magnitude threshold, we explore the scaling behavior of earthquake percolation. The robustness of our findings is confirmed through comparison with multiple shuffling tests. Full article

The development of more effective treatments for neurodegenerative disorders presents a significant challenge in modern medicine. Currently, scientists are focusing on discovering bioactive compounds from plant sources to prevent and treat neurodegenerative diseases. Fifteen flavonoids and saponins from C. foliosum Asch. and C. bonus-henricus L. were tested for their inhibitory activity on hMAO-A and hMAO-B. Five compounds (1 μM) exhibit a weak inhibitory effect on hMAO-A and show good inhibitory activity against the hMAO-B enzyme (30–35%), compared to the positive control selegiline (55%). These active compounds were examined on rat brain synaptosomes and mitochondria obtained by multiple differential centrifugations using a Percoll gradient. Their effects were also monitored on rat brain microsomes obtained by double differential centrifugation. The main parameters characterizing the functional–metabolic status of subcellular fractions are synaptosomal viability, GSH level, and MDA production. All tested compounds (50 μM) demonstrated significant neuroprotective and antioxidant activities across models of induced oxidative stress, including 6-OHDA, t-BuOOH, and Fe^2+/AA-induced lipid peroxidation. The plausible mechanisms of neuroprotection rely on MAO-B inhibition, the scavenging of ROS, stabilizing the cell membrane by reducing MDA production, and neutralizing free radicals by maintaining GSH levels. In addition, we developed and validated a UHPLC-HRMS method for identifying and simultaneously quantificatying flavonoids and saponins in the aerial parts of C. foliosum. Compounds 30-normedicagenic acid- HexA-Hex-TA 22f and medicagenic acid-HexA-Hex-TA 25f were considered new natural compounds. Full article

Vehicle washing facilities (VWFs) consume substantial amounts of potable water and produce wastewater containing pollutants such as hydrocarbons, detergents, and pathogens, presenting significant environmental and operational challenges. This study evaluates Nature-based Solutions (NbS) for wastewater treatment and recycling at a pilot facility in Girona, Spain, aiming to reduce potable water consumption and ensure safe reuse while minimizing environmental impact. Over a two-year period, three systems—a Vertical Flow Treatment Wetland (VFTW), Horizontal Flow Treatment Wetland (HFTW), and Infiltration-Percolation (IP) filter—were tested. Thirty-two parameters, including physicochemical (e.g., turbidity, nutrients, heavy metals, detergents) and microbiological indicators (e.g., E. coli, Legionella spp.), were monitored. VFTW and IP systems were the most effective, reducing turbidity below 5 NTU, COD to under 20 mg/L, and E. coli below 10 CFU/100 mL, meeting Spanish reuse standards. The HFTW effectively removed organic matter and nutrients but faced challenges such as clogging and reduced hydraulic performance, making it less suitable for carwash wastewater. Together, these systems enabled up to 60% water reuse, with final chlorination ensuring microbial safety, particularly against Legionella, while meeting Spanish reuse standards. This study highlights the potential of NbS as sustainable, low-energy solutions for wastewater recycling and pollution control in vehicle washing facilities. Full article

Porcine reproductive and respiratory syndrome (PRRS) is an endemic disease affecting the swine industry. The disease is caused by the PRRS virus (PRRSV). Despite extensive biosecurity and control measures, the persistence and seasonality of the virus have raised questions about the virus’s environmental dynamics during the fall season when the yearly epidemic onset begins and when crop harvesting and manure incorporation into the field occur. Therefore, this study aimed to assess the potential for PRRSV to percolate through different soil types, simulating conditions that could lead to groundwater contamination which could represent a risk of herd introduction. An experimental soil column model was used to mimic field conditions. Three PRRSV-2 strains were tested across thirteen Minnesota soils with different physical and chemical characteristics. The findings revealed that PRRSV can percolate through all soil types and that the amount of virus percolated decreases with increased amounts of soil. These results suggest that PRRSV can percolate through different soil types. Further investigations should be undertaken to determine the associated implications for swine health and biosecurity measures. Full article

This paper explores the development of 3D-printed self-sensing Ultra-High Performance Concrete (UHPC) by incorporating graphite (G) powder, milled carbon microfiber (MCMF), and chopped carbon microfiber (CCMF) as additives into the UHPC matrix to enhance piezoresistive properties while maintaining workability for 3D printing. Percolation curves were established to identify optimal filler inclusion levels, and a series of compressive tests, including quasi-static cyclic, dynamic cyclic, and monotonic compressive loading, were conducted to evaluate the piezoresistive and mechanical performance of 29 different mix designs. It was found that incorporating G powder improved the conductivity of the UHPC but decreased compressive strength for both mold-cast and 3D-printed specimens. However, incorporating either MCMF or CCMF into the UHPC resulted in the maximum 9.8% and 19.2% increase in compressive strength and Young’s modulus, respectively, compared to the plain UHPC. The hybrid combination of MCMF and CCMF showed particularly effective in enhancing sensing performance, achieving strain linearity over 600 $\mu \epsilon$. The best-preforming specimens (3G250M250CCMF) were fabricated using 3 wt% of G, 0.25 wt% of MCMF, and 0.25 wt% of CCMF, yielding a maximum strain gauge factor of 540, a resolution of 68 $\mu \epsilon$, and an accuracy of 4.5 $\mu \epsilon$ under axial compression. The 3D-printed version of the best-performing specimens exhibited slightly diminished piezoresistive and mechanical behaviors compared to their mold-cast counterparts, yielding a maximum strain gauge factor of 410, a resolution of 99 $\mu \epsilon$, and an accuracy of 8.6 $\mu \epsilon$. Full article

The aim of this study was to determine the frequency–temperature dependence of the AC conductivity and relaxation times in humid electrical pressboard used in the insulation of power transformers, impregnated with the innovative NYTRO^® BIO 300X bio-oil produced from plant raw materials. Tests were carried out for a composite of cellulose–bio-oil–water nanodroplets with a moisture content of 0.6% by weight to 5% by weight in the frequency range from 10⁻⁴ Hz to 5·10³ Hz. The measurement temperatures ranged from 20 °C to 70 °C. The current conductivity in percolation channels in cellulose–bio insulating oil–water nanodroplets nanocomposites was analyzed. In such nanocomposites, DC conduction takes place via electron tunneling between the potential wells formed by the water nanodroplets. It was found that the value of the percolation channel resistance is lowest in the case of a regular arrangement of the nanodroplets. As disorder increases, characterized by an increase in the standard deviation value, the percolation channel resistance increases. It was found that the experimental values of the activation energy of the conductivity and the relaxation time of the composite of cellulose–bio-oil–water nanodroplets are the same within the limits of uncertainty and do not depend on the moisture content. The value of the generalized activation energy is ΔE ≈ (1.026 ± 0.0160) eV and is constant over the frequency and temperature ranges investigated. This study shows that in the lowest frequency region, the conductivity value does not depend on frequency. As the frequency increases further, the relaxation time decreases; so, the effect of moisture on the conductivity value decreases. The dependence of the DC conductivity on the moisture content was determined. For low moisture contents, the DC conductivity is practically constant. With a further increase in water content, there is a sharp increase in DC conductivity. Such curves are characteristic of the dependence of the DC conductivity of composites and nanocomposites on the content of the conducting phase. A percolation threshold value of x_c ≈ (1.4 ± 0.3)% by weight was determined from the intersection of flat and steeply sloping sections. The frequency dependence of the values of the relative relaxation times was determined for composites with moisture contents from 0.6% by weight to 5% by weight for a measurement temperature of 60 °C. The highest relative values of the relaxation time τ_ref occur for direct current and for the lowest frequencies close to 10⁻⁴ Hz. As the frequency increases further, the relaxation time decreases. The derivatives d(logτ_ref)/d(logf) were calculated, from the analysis of which it was determined that there are three stages of relaxation time decrease in the nanocomposites studied. The first occurs in the frequency region from 10⁻⁴ Hz to about 3·10⁻¹ Hz, and the second from about 3·10⁻¹ Hz to about 1.5·10¹ Hz. The beginning of the third stage is at a frequency of about 1.5·10¹ Hz. The end of this stage is above the upper range of the Frequency Domain Spectroscopy (FDS) meter, which is 5·10³ Hz. It has been established that the nanodroplets are in the cellulose and not in the bio-oil. The occurrence of three stages on the frequency dependence of the relaxation time can be explained when the fibrous structure of the cellulose is taken into account. Nanodroplets, found in micelles, microfibrils and in the fibers of which cellulose is composed, can have varying distances between nanodroplets, determined by the dimensions of these cellulose components. Full article