Search Results (60,513)

Per- and polyfluoroalkyl substances (PFASs) have attracted global attention due to their persistence and biological toxicity, becoming critical emerging contaminants in river and lake environments worldwide. Building upon existing studies, this work aims to comprehensively understand the pollution patterns, environmental behaviors, and potential risks of PFASs in freshwater systems, thereby providing scientific evidence and technical support for precise pollution control, risk prevention, and the protection of aquatic ecosystems and human health. Based on publications from 2002 to 2025 indexed in the Web of Science (WoS), bibliometric analysis was used to explore the temporal evolution and research hotspots of PFASs, and to systematically review their input pathways, pollution characteristics, environmental behaviors, influencing factors, and ecological and health risks in river and lake environments. Results show that PFAS inputs originate from both direct and indirect pathways. Direct emissions mainly stem from industrial production, consumer product use, and waste disposal, while indirect emissions arise from precursor transformation, secondary releases from wastewater treatment plants (WWTPs), and long-range atmospheric transport (LRAT). Affected by source distribution, physicochemical properties, and environmental conditions, PFASs display pronounced spatial variability among environmental media. Their partitioning, degradation, and migration are jointly controlled by molecular properties, aquatic physicochemical conditions, and interactions with dissolved organic matter (DOM). Current risk assessments indicate that PFASs generally pose low risks in non-industrial areas, yet elevated ecological and health risks persist in industrial clusters and regions with intensive aqueous film-forming foam (AFFF) use. Quantitative evaluation of mixture toxicity and chronic low-dose exposure risks remains insufficient and warrants further investigation. This study reveals the complex, dynamic environmental behaviors of PFASs in river and lake systems. Considering the interactions between PFASs and coexisting components, future research should emphasize mechanisms, key influencing factors, and synergistic control strategies under multi-media co-pollution. Developing quantitative risk assessment frameworks capable of characterizing integrated mixture toxicity will provide a scientific basis for the precise identification and effective management of PFAS pollution in aquatic environments. Full article

Polar patterns and topological defects are ubiquitous in active matter. In this paper, we study a paradigmatic polar active dumbbell system through numerical simulations, to clarify how polar patterns and defects emerge and shape evolution. We focus on the interplay between these patterns and morphology, domain growth, irreversibility, and compressibility, tuned by dumbbell rigidity and interaction strength. Our results show that, when separated through MIPS, dumbbells with softer interactions can slide one relative to each other and compress more easily, producing blurred hexatic patterns, polarization patterns extended across entire hexatically varied domains, and stronger compression effects. Analysis of isolated domains reveals the consistent presence of inward-pointing topological defects that drive cluster compression and generate non-trivial density profiles, whose magnitude and extension are ruled by the rigidity of the pairwise potential. Investigation of entropy production reveals instead that clusters hosting an aster/spiral defect are characterized by a flat/increasing entropy profile mirroring the underlying polarization structure, thus suggesting an alternative avenue to distinguish topological defects on thermodynamical grounds. Overall, our study highlights how interaction strength and defect–compression interplay affect cluster evolution in particle-based active models, and also provides connections with recent studies of continuum polar active field models. Full article

This study evaluates the cosmetic degradation of polyethylene (PE) and polypropylene (PP) automotive components under four exposure scenarios—no exposure, outdoor exposure with and without glass shielding, and accelerated UV chamber weathering (ASTM G154)—through the evolution of visible (VIS) reflectance. Thirty-two samples (16 PE, 16 PP) were monitored over five time points; surface reflectance was recorded at 21 wavelengths and summarized into seven VIS bands, and hardness (Shore D) was measured pre/post-exposure. Repeated-measures univariate and multivariate analyses consistently revealed significant effects of Condition, Time, and their interaction on reflectance, with initial-reflectance adjustment improving inference stability across bands. PE exhibited more gradual and coherent reflectance decay, whereas PP showed greater band-to-band variability—most notably under UV chamber exposure. Additionally, hardness decreased in most exposed groups, aligning with optical changes. To place spectral trajectories in a kinetic context, a family of exponential models with small-sample information criterion selection was fitted, yielding $\eta \left(t\right)$—a dimensionless degradation efficiency summarizing spectral change. The contribution of this work is a multi-statistical framework—combining VIS-band-aware summaries with covariate-adjusted univariate/multivariate testing—that supports comparisons across materials and exposure conditions, underscoring the practical value of UV chamber protocols as surrogates for outdoor weathering. In sum, the study demonstrates the effectiveness of multivariate and covariate-adjusted models in quantifying optical degradation of polyolefins, offering pragmatic guidance for assessing mid- to long-term performance in automotive applications. Full article

Textile industries release dyes into wastewater, and when present above certain levels, these dyes pose serious risks because of their high toxicity. This study investigates the removal of Sunset Yellow (SY) and Methylene Violet (MV) dyes from wastewater using chitosan (CS) and polysilicate acid (pSi) in the structure of aluminum-based coagulants, resulting in hybrid formulations (CS@Al, Al/pSi, and CS@Al/pSi). Among the various treatment methods that have been applied for the removal of dyes, the coagulation/flocculation process was chosen in the present study, as it is a cheap and effective method. Coagulation performance was optimized for pH, coagulant dosage, temperature and mixing time. The Al/pSi coagulant achieved nearly complete SY removal (98.8%) at 25 mg/L dosage and pH 3.0. MV removal in single-dye solutions was limited, with Al/pSi achieving only 26.6% removal at pH 3.0. However, in mixed-dye systems (SY/MV), synergistic interactions increased MV removal up to 94.4% and SY removal to 100%. Hybrid CS@Al/pSi showed lower SY removal (36.4%) for SY at 50 mg/L but provided stable floc formation, particularly in mixtures of anionic and cationic dyes. Application to real textile wastewater confirmed the high efficiency of the optimized coagulants, particularly with Al/pSi_20,A and AlCl₃, indicating their potential for industrial wastewater treatment. SEM, EDS, XRD, and FTIR analyses revealed structural consolidation, increased surface area, and successful dye adsorption, explaining the high removal efficiency. Full article

The increased energy efficiency of electrified vehicles and their potential to reduce CO₂ emissions through the use of environmentally friendly materials are highlighted as reasons for the shift to electrified vehicles. Brief trends on the development of electric vehicles (EVs) have been discussed, presenting outstanding improvement towards the actualization of the green economy. The state of the art in lubrication has been thoroughly investigated as one of the factors influencing energy efficiency and the lifespan of machine components. As a result, many reports on the effectiveness of specific lubricants in electric vehicle applications have been developed. Good thermal and corrosion-resistant lubricants are necessary because of the emergence of several new tribological difficulties, especially in areas that interact with greater temperatures and currents. To avoid fluidity and frictional problems that may be experienced over its lifetime, a good viscosity level of lubricant was also mentioned as a crucial component in the formulation of EV lubricant. New lubricants are also necessary for the gearbox systems of electric vehicles. Furthermore, battery electric vehicles (BEVs) require a suitable cooling system for the batteries; thus, a compatible nano-fluid is recommended. Sustainable battery cooling options support global energy efficiency and carbon emission reduction while extending the life of EV batteries. The path for future advancements or the creation of the most useful and efficient EV lubricants is provided by this review study. Full article

Aerosol–cloud interaction remains one of the largest sources of uncertainty in weather and climate modeling. This study investigates the impacts of aerosols on the macro- and microphysical properties of different cloud types over East Asia, based on nine years of joint satellite observations from CloudSat, CALIPSO, and MODIS, combined with ERA5 reanalysis data. Results reveal pronounced cloud-type dependence in aerosol effects on cloud fraction, cloud top height, and cloud thickness. Aerosols enhance the development of convective clouds while suppressing the vertical extent of stable stratiform clouds. For ice-phase structures, ice cloud fraction and ice water path significantly increase with aerosol optical depth (AOD) in deep convective and high-level clouds, whereas mid- to low-level clouds exhibit reduced ice crystal effective radius and ice water content, indicating an “ice crystal suppression effect.” Even after controlling for 14 meteorological variables, partial correlations between AOD and cloud properties remain significant, suggesting a degree of aerosol influence independent of meteorological conditions. Humidity and wind speed at different altitudes are identified as key modulating factors. These findings highlight the importance of accounting for cloud-type differences, moisture conditions, and dynamic processes when assessing aerosol–cloud–climate interactions and provide observational insights to improve the parameterization of aerosol indirect effects in climate models. Full article

Microencapsulation is a fundamental technology for protecting active compounds from environmental degradation by factors such as light, heat, and oxygen. This process significantly improves their stability, bioavailability, and shelf life by entrapping an active core within a protective matrix. Therefore, a thorough understanding of the physicochemical interactions between these components is essential for developing stable and efficient delivery systems. The composition of the microcapsule and the encapsulation method are key determinants of system stability and the retention of encapsulated materials. Recently, the application of computational tools to predict and optimize microencapsulation processes has emerged as a promising area of research. In this context, molecular dynamics (MD) simulation has become an indispensable computational technique. By solving Newton’s equations of motion, MD simulations enable a detailed study of the dynamic behavior of atoms and molecules in a simulated environment. For example, MD-based analyses have quantitatively demonstrated that optimizing polymer–core interaction energies can enhance encapsulation efficiency by over 20% and improve the thermal stability of active compounds. This approach provides invaluable insights into the molecular interactions between the core material and the matrix, ultimately facilitating the rational design of optimized microstructures for diverse applications, including pharmaceuticals, thereby opening new avenues for innovation in the field. Ultimately, the integration of computational modeling into microencapsulation research not only represents a methodological advancement but also pivotal opportunity to accelerate innovation, optimize processes, and develop more effective and sustainable therapeutic systems. Full article

Human rhinovirus 16 (HRV-16) is a major cause of common colds and can exacerbate asthma and COPD, yet no approved antiviral treatments exist. Heparin, a highly sulfated polysaccharide, is known to block viral infection of many viruses that require attachment to heparan sulfate proteoglycans (HSPGs). Here, we investigated whether heparin inhibits HRV-16 infection. HRV-16 uses ICAM-1 as its attachment receptor and lacks a confirmed HSPG-binding mechanism. Notably, heparin inhibited HRV-16 infection in vitro in a dose- and time-dependent manner. Pre-treatment of either cells or virus particles with unfractionated heparin significantly reduced HRV-16 RNA expression at 24 and 48 h post-infection. In contrast, low-molecular-weight heparins blocked infection of HRV-16 significantly less effectively compared to unfractionated heparins. Our findings suggest that the inhibitory effect of unfractionated heparin on HRV-16 infection is likely independent of specific HSPGs interactions and may be mediated by the size and highly negative charge of unfractionated heparin. Importantly, the ability of unfractionated heparin to block viruses that do not require HSPGs for attachment implies a broader antiviral potential as a prophylactic or therapeutic agent against a variety of respiratory viruses. Full article

Motility disorders, particularly gastroparesis, are prevalent complications following solid organ transplantation, significantly impacting quality of life, nutritional status, graft survival, and mortality. This comprehensive review synthesises evidence from PubMed, Scopus, and Embase databases on pathophysiology, clinical manifestations, diagnosis, management, and prognostic factors across transplant types. Mechanisms include vagal nerve injury (highest in lung transplants, prevalence 40–91%), immunosuppressive effects (e.g., tacrolimus accelerates motility; mycophenolate impairs it), surgical trauma, microbiome dysbiosis (reduced Firmicutes/Bacteroidetes ratio), and metabolic factors like post-transplant diabetes (OR 5.17 in kidney recipients). Pediatric and thoracic recipients face the highest risks, with lung transplant gastroparesis conferring a 2.7-fold increased mortality/retransplantation hazard (p < 0.05). Diagnosis relies on gastric emptying scintigraphy (gold standard, sensitivity 85–95%) and wireless motility capsules (100% sensitivity for delay), while management encompasses prokinetics (60–80% response), endoscopic G-POEM (85% success), gastric electrical stimulation (100% quality-of-life improvement in series), and nutritional support. Prognostic factors include younger age (better intervention response), aetiology (anatomical worse than metabolic), and early therapy success. Outcomes vary: lung recipients experience severe impacts on chronic allograft dysfunction (83% oesophageal motility abnormalities correlate with 66–67% rejection). Future directions emphasise microbiome therapies, AI predictive models (AUC 0.85), and wearables for continuous monitoring. Multidisciplinary approaches are essential to balance immunosuppression with GI management, addressing ethical dilemmas like drug interactions and access disparities. Ultimately, early screening and personalised interventions can mitigate complications, enhancing long-term transplant success. Full article

Effective thermal management is essential in metal additive manufacturing to ensure process stability and desirable material properties. Directed energy deposition using a laser beam and wire (DED-LB/w) enables the production of large, high-performance components but remains sensitive to adverse thermal effects during multi-layer deposition due to heat accumulation. While prior studies have investigated interlayer temperature control and substrate preheating in DED modalities, including laser-powder and arc-based systems, the influence of substrate preheating in DED-LB/w has not been thoroughly examined. This study employs substrate preheating to simulate heat accumulation and assess its effects on melt pool geometry, wire–melt pool interaction, and the microstructural evolution of Alloy 718. Experimental results demonstrate that increased substrate temperatures lead to a gradual expansion of the melt pool, with a notable transition occurring beyond 400 °C. Microstructural analysis reveals that elevated preheat temperatures promote coarser secondary dendrite arm spacing and the development of wider columnar grains. Moreover, Nb-rich secondary phases, including the Laves phase, exhibit increased size but relatively unchanged area fractions. Observations from electrical conductance measurements and coaxial visual imaging show that preheat temperature significantly affects the process dynamics and microstructural evolution, providing a basis for advanced process control strategies. Full article

Objectives: Meniscal integrity is crucial for knee joint stability and the prevention of osteoarthritis (OA) development. Recent studies suggested that mechanical overload and interleukin (IL)-17A may be important intertwined players in meniscal degeneration, but a direct impact of IL-17A on the meniscus has not been investigated. Therefore, the aim of this study was to analyze the effect of IL-17A on meniscal tissue with and without combined mechanical injury (MI). Methods: Meniscal explant disks (1 mm height, 3 mm diameter) were isolated from bovine menisci (preserving the native tibial superficial zone) and exposed to IL-17A [0–100 ng/mL] and/or MI (single compression, 50% strain, strain rate 1 mm/sec). After three days of incubation in a serum-free medium, the proteoglycan release (sGAG; DMMB assay), mRNA level of matrix-degrading enzymes (qRT-PCR), aggrecan degradation (NITEGE immunostaining), and cell death (histomorphometry of nuclear blebbing/apoptosis and condensed nuclei/unspecified cell death) were determined. Statistics: one- and two-way ANOVA with Tukey’s multiple comparisons or Kruskal–Wallis with post hoc testing. Results: IL-17A increased sGAG release in a dose-dependent significant manner. MI also induced the release of sGAG significantly, but the combination with IL-17A showed the highest levels. Both IL-17A and MI individually affected the mRNA levels for ADAMTS4 and MMP-13 slightly, but the combination of both particularly induced a significant increase in mRNA levels. Signals for the ADAMTS4-related aggrecan neoepitope NITEGE were elevated by IL-17A in superficial areas of the excised tissue and by MI in superficial and deeper areas. The combination of both stimuli intensified this signal further. MI increased the number of cells with condensed nuclei significantly and induced apoptosis in a small proportion of cells. IL-17A had no significant impact on the amount of condensed or apoptotic nuclei. Conclusions: Our findings emphasize an interaction between inflammatory cytokine IL-17A signaling and mechanical stress since IL-17A induced matrix degeneration in meniscal tissue, which intensified in combination with a trauma. The latter might create a post-traumatic environment that promotes meniscal degeneration and subsequently osteoarthritis progression. Full article

Metal particles and surface charge accumulation are considered the key factors that could trigger unexpected flashovers of insulators equipped in gas-insulated switchgear (GIS). In eco-friendly gases, the flashover properties and the synergistic effect of the surface charge and the metal particle on flashover remain unclear. This study investigates the flashover properties of down-scaled 252 kV GIS basin-type epoxy insulators with metal particles in C₄F₇N/CO₂ mixtures, with and without AC pre-charging. Tests considered various particle adherence locations and a particle-free control group. The results indicated that metal particles at the high-voltage (HV) electrode or middle area reduce flashover voltage, with the HV electrode and concave surface being most critical. Surface charges, induced by pre-charging and metal particle attachment, interact synergistically with the metal particle during the flashover process, increasing the flashover voltage and redirecting arcs away from them. Such findings enhance understanding of flashover mechanisms in eco-friendly gas-insulated systems and inform insulator design. Full article

This study investigates the adsorption behavior of natural sepiolite for the removal of cadmium (Cd²⁺), copper (Cu²⁺), and nickel (Ni²⁺) ions from aqueous solutions under batch conditions. The sepiolite was extensively characterized prior to adsorption experiments. Mineralogical analysis confirmed the presence of crystalline sepiolite, while DTG-TGA revealed thermal stability with distinct weight loss linked to surface and structural water. BET analysis indicated a high surface area of 194 m²/g and a mesoporous structure favorable for adsorption. Batch experiments evaluated the effects of contact time, pH, adsorbent dosage, and initial metal concentration. Adsorption was highly pH-dependent, with maximum removal near-neutral pH values. Higher adsorbent dosages reduced in a lower adsorption capacity per unit mass, primarily because the fixed amount of solute was distributed over a larger number of available sites, leading to unsaturation of the adsorbent surface and possible particle agglomeration. Isotherm modeling revealed that the Langmuir model provided the best fit, indicating monolayer adsorption with maximum adsorption capacities of 15.95 mg/g for Cd(II), 37.31 mg/g for Cu(II), and 17.83 mg/g for Ni(II). Langmuir constants indicated favorable interactions. Kinetics showed rapid adsorption within the first hour, reaching equilibrium at 240 min through surface adsorption and intraparticle diffusion. Cu(II) exhibited the fastest uptake, while Ni(II) adsorbed more slowly, suggesting differences in diffusion rates among the metal ions. Desorption using 0.1 N HCl achieved over 80% efficiency for all metals, confirming sepiolite reusability. Overall, raw sepiolite is an effective, low-cost adsorbent for removing potentially toxic elements from water. Full article

Background/Objectives: Photobiomodulation (PBM) is a non-invasive, low-level laser treatment shown to improve insulin resistance, glucose metabolism, and obesity-related inflammation. This study examined whether PBM could acutely enhance mitochondrial efficiency and energy metabolism in women with obesity. Methods: In a randomized, crossover within-subject design, 16 women with obesity (43 ± 5 years; BMI: 36 ± 4 kg/m²) and 16 sedentary normal-weight women (43 ± 5 years; BMI: 22.7 ± 2 kg/m²) underwent PBM (front and back exposure; red light, 633–660 nm; NIR, 850–940 nm) and a sham stimulation (SHAM), as a control, for 12 min. Resting energy expenditure (REE) was assessed via indirect calorimetry before and after exposure. Secondary measures included skin autofluorescence, heart rate, blood pressure, profile of mood states, rate of perceived exertion (RPE), and flexibility. Diet and physical activity were controlled. Results: A 2 × 2 × 2 ANOVA revealed a significant group × time interaction (F_3,60 = 3.054, p = 0.03) and a main effect of time (F_1,60 = 10.88, p = 0.001). Women with obesity showed a significant increase in REE post-PBM compared to pre-PBM (+9.3%, 1624 ± 314 vs. 1486 ± 327 kcal/day; p < 0.001), with no change in the respiratory exchange ratio. Additionally, RPE decreased and flexibility improved in both groups following PBM. Front and back skin temperatures increased significantly post-PBM, with greater changes observed in the back versus the front. Conclusions: These preliminary findings indicate that PBM acutely enhances energy utilization efficiency in women with obesity, increasing resting energy expenditure without modifying substrate oxidation. PBM may represent a promising non-invasive adjunctive strategy for improving the metabolic health of obese individuals. Full article

As high-energy-consumption underground public space, subway stations are responsible for a particularly significant proportion of air-conditioning energy use, especially during the cooling season, making the investigation of cooling-load characteristics highly important. However, the determination of independent influencing factors in different situations has not yet reached a consensus, and the role of interaction effects is lacking, which hinders the development of energy-saving strategies. For this purpose, this study proposes a sensitivity analysis framework based on 10 typical influencing factors from thermal parameters, meteorological parameters, internal heat disturbances, and indoor environmental setpoints. An input set was generated by integrating equal-step parameter discretization and Saltelli quasi-MonteCarlo sampling. A database containing 11,264 samples was constructed through an EnergyPlus–Python co-simulation method. Based on the Sobol global sensitivity analysis, the key influencing factors of subway station cooling load were identified and quantified, and the impact of these 10 factors was systematically analyzed. Results show that occupant density (S_i^T = 0.5605) and fresh air volume (S_i^T = 0.4546) are the dominant factors, contributing more than 50% of the load variance. In contrast, the characteristics of an underground structure significantly weaken the influence of the building-envelope heat transfer coefficient (S_i^T = 0.1482) and soil temperature (S_i^T = 0.0884). Furthermore, five groups of strong interaction effects were identified in this study, including occupant density–fresh air volume (S_ij = 0.1094), revealing a nonlinear load response mechanism driven by multi-parameter coupling. This research provides a theoretical foundation and quantitative tool for the refined design and optimized dynamic coupled operation of underground transportation hubs. Full article