Search Results (21,088)

To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries. Full article

As an efficient clean energy technology, water electrolysis for hydrogen production has its efficiency limited by the sluggish oxygen evolution reaction (OER) kinetics, which drives the demand for the development of high-performance anode OER catalysts. This work constructs bimetallic (Al, Mn) co-doped nanoporous spinel CoFe₂O₄ (np-CFO) with a tunable structure and composition as an OER catalyst through a simple two-step dealloying strategy. The as-formed np-CFO (Al and Mn) features a hierarchical flaky configuration; that is, there are a large number of fine nanosheets attached to the surface of a regular micron-sized flake, which not only increases the number of active sites but also enhances mass transport efficiency. Consequently, the optimized catalyst exhibits a low OER overpotential of only 320 mV at a current density of 10 mA cm⁻², a minimal Tafel slope of 45.09 mV dec⁻¹, and exceptional durability. Even under industrial conditions (6 M KOH, 60 °C), it only needs 1.83 V to achieve a current density of 500 mA cm⁻² and can maintain good stability for approximately 100 h at this high current density. Theoretical simulations indicate that Al and Mn co-doping could indeed optimize the electronic structure of CFO and thus decrease the energy barrier of OER to 1.35 eV. This work offers a practical approach towards synthesizing efficient and stable OER catalysts. Full article

Biofilms are structured microbial communities that pose significant challenges to food safety and quality within the food-processing industry. Their formation on equipment and surfaces enables persistent contamination, microbial resistance, and recurring outbreaks of foodborne illness. This review provides a comprehensive synthesis of current knowledge on biofilm formation mechanisms, genetic regulation, and the unique behavior of multi-species biofilms. The review evaluates modern detection and monitoring technologies, including PCR, biosensors, and advanced microscopy, and compares their effectiveness in industrial contexts. Real-world outbreak data and a global economic impact analysis underscore the urgency for more effective regulatory frameworks and sanitation innovations. The findings highlight the critical need for integrated, proactive biofilm management approaches to safeguard food safety, reduce public health risks, and minimize economic losses across global food sectors. Full article

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

In this study, a novel direct laser beam turning (DLBT) approach is proposed for the precision machining of AISI 308L austenitic stainless steel, which eliminates the need for cutting tools and thereby eradicates tool wear and vibration-induced surface irregularities. A nanosecond-pulsed Nd:YAG fiber laser (λ = 1064 nm, spot size = 0.05 mm) was used, and Ø1.6 mm × 20 mm cylindrical rods were processed under ambient conditions without auxiliary cooling. The experimental framework systematically evaluated the influence of scanning speed, pulse frequency, and the number of laser passes on dimensional accuracy and material removal efficiency. The results indicate that a maximum diameter reduction of 0.271 mm was achieved at a scanning speed of 3200 mm/s and 50 kHz, whereas 0.195 mm was attained at 6400 mm/s and 200 kHz. A robust second-order polynomial correlation (R² = 0.99) was established between diameter reduction and the number of passes, revealing the high predictability of the process. Crucially, when the scanning speed was doubled, the effective fluence was halved, considerably influencing the ablation characteristics. Despite the low fluence, evidence of material evaporation at elevated frequencies due to the incubation effect underscores the complex photothermal dynamics governing the process. This work constitutes the first comprehensive quantification of pass-dependent diameter modulation in DLBT and introduces a transformative, noncontact micromachining strategy for hard-to-machine alloys. The demonstrated precision, repeatability, and thermal control position DLBT as a promising candidate for next-generation manufacturing of high-performance miniaturized components. Full article

The frequency-domain free-surface Green’s function method is widely used in solving ship hydrodynamic problems, with its core challenge lying in the computation of the Green’s function and its partial derivatives. This study analyzes the relationship between the free-surface Green’s function and its derivatives, proposing a machine learning-based recursive prediction method termed the pulsating source recursive prediction method. The accuracy and efficiency of this method under various parameter settings are investigated, and its application to the hydrodynamic calculations of container ship S175 and a bulk carrier is demonstrated. Results show that the predicted Green’s function achieves an accuracy of 3–6 decimals, with computational efficiency surpassing numerical methods and matching analytical approaches. The hydrodynamic results are reliable, confirming the method’s practical value. Full article

The Complementary Relationship (CR) principle of evapotranspiration provides an efficient approach for estimating actual evapotranspiration (ET_a), owing to its simplified computation and effectiveness in utilizing meteorological factors. Accurate estimation of actual evapotranspiration (ET_a) is crucial for understanding surface energy and water cycles, especially in permafrost regions. This study aims to evaluate the applicability of two Complementary Relationship (CR)-based methods—Bouchet’s in 1963 and Brutsaert’s in 2015—for estimating ETa on the Qinghai–Tibetan Plateau (QTP), using observations from Eddy Covariance (EC) systems. The potential evapotranspiration (ET_p) was calculated using the Penman equation with two wind functions: the Rome wind function and the Monin–Obukhov Similarity Theory (MOST). The comparison revealed that Bouchet’s method underestimated ET_a during frozen soil periods and overestimated it during thawed periods. In contrast, Brutsaert’s method combined with the MOST yielded the lowest RMSE values (0.67–0.70 mm/day) and the highest correlation coefficients (r > 0.85), indicating superior performance. Sensitivity analysis showed that net radiation (Rn) had the strongest influence on ET_a, with a daily sensitivity coefficient of up to 1.35. This study highlights the improved accuracy and reliability of Brutsaert’s CR method in cold alpine environments, underscoring the importance of considering freeze–thaw dynamics in ET modeling. Future research should incorporate seasonal calibration of key parameters (e.g., ε) to further reduce uncertainty. Full article

This study describes and validates a novel method for assessing anterior crystalline lens curvature along vertical and horizontal meridians using radial measurements derived from Scheimpflug imaging. The aim was to evaluate whether pupil diameter (PD), anterior lens curvature, and anterior chamber depth (ACD) change during accommodation and whether these changes are age-dependent. A cross-sectional study was conducted on 104 right eyes from healthy participants aged 21–62 years. Sixteen radial images per eye were acquired using the Galilei Dual Scheimpflug Placido Disk Topographer under four accommodative demands (0, 1, 3, and 5 dioptres (D)). Custom software analysed lens curvature by calculating eccentricity in both meridians. Participants were analysed as a total group and by age subgroups. Accommodative amplitude and monocular accommodative facility were inversely correlated with age. Both PD and ACD significantly decreased with higher accommodative demands and age. Relative eccentricity decreased under accommodation, indicating increased lens curvature, especially in younger participants. Significant curvature changes were detected in the horizontal meridian only, although no statistically significant differences between meridians were found overall. The vertical meridian showed slightly higher eccentricity values, suggesting that it remained less curved. By enabling detailed, meridionally stratified in vivo assessment of anterior lens curvature, this novel method provides a valuable non-invasive approach for characterizing age-related biomechanical changes during accommodation. The resulting insights enhance our understanding of presbyopia progression, particularly regarding the spatial remodelling of the anterior lens surface. Full article

Given the environmental significance of the textile industry, especially the accumulation of nondegradable materials, there is extensive development of greener approaches to fabric waste management. Here, we investigated the biodegradation potential of three Streptomyces strains in model compost on polyamide (PA) and polyamide-elastane (PA-EA) as synthetic, and on cotton (CO) as natural textile materials. Weight change of the materials was followed, while Fourier-Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) were used to analyze surface changes of the materials upon biodegradation. The bioluminescence-based toxicity test employing Vibrio fischeri confirmed the ecological safety of the tested textiles. After 12 months, the increase of 10 and 16% weight loss, of PA-EA and PA, respectively, was observed in compost augmented with Streptomyces sp. BPS43. Additionally, a 14% increase in cotton degradation was recorded after 2 months in compost augmented with Streptomyces sp. NP10. Genome exploration of the strains was carried out for potential plastic-degrading enzymes. It highlighted BPS43 as the most versatile strain with specific amidases that show sequence identity to UMG-SP-1, UMG-SP-2, and UMG-SP-3 (polyurethane degrading enzymes identified from compost metagenome). Our results showcase the behavior of Streptomyces sp. BPS43 in the degradation of PA and PA-EA textiles in composting conditions, with enzymatic potential that could be further characterized and optimized for increased synthetic textile degradation. Full article

Surface and sub-surface atomic configurations are critical for catalysis as they host the active sites governing electrochemical processes. This study employs density functional theory (DFT) calculations and Monte Carlo simulations combined with the cluster-expansion approach to investigate atom distribution and Pt segregation in Pt-Fe alloys across varying Pt/Fe ratios. Our simulations reveal a strong tendency for Pt atoms to segregate to the surface layer while Fe atoms enrich the sub-surface region. Crucially, the calculations predict the stability of a periodic Pt₂Fe alloy surface model, characterized by specific defect structures, at low platinum content and low annealing temperatures. Electronic structure analysis indicates that forming this Pt₂Fe surface alloy lowers the d-band center of Pt atoms, weakening CO adsorption and thereby enhancing resistance to CO poisoning. Although defect-induced strains can modulate the d-band center, crystal orbital Hamilton population (COHP) analysis confirms that such strains generally strengthen Pt-CO interactions. Therefore, the theoretical design of Pt₂Fe alloy surfaces and controlling defect density are predicted to be effective strategies for enhancing catalyst resistance to CO poisoning. This work highlights the advantages of periodic Pt₂Fe surface models for anti-CO poisoning and provides computational guidance for designing efficient Pt-based electrocatalysts. Full article

Background/Objectives: Additive manufacturing (AM) technology has emerged as an innovative approach in dentistry. Recently, manufacturers have developed permanent resins engineered explicitly for the fabrication of definitive prostheses using AM techniques. This systematic review evaluated the mechanical and physical properties of 3D-printed permanent resins in comparison to milled resins and hybrid ceramics for the fabrication of indirect dental restorations. Methods: Three electronic databases—Scopus, Web of Science, and PubMed—were searched for English-language articles. Two independent researchers conducted study selection, data extraction, quality assessment, and the evaluation of the certainty of evidence. In vitro studies assessing the mechanical and physical properties of the permanent resins were included in this review. Results: A total of 1779 articles were identified through electronic databases. Following full-text screening and eligibility assessment, 13 studies published between 2023 and 2024 were included in this qualitative review. The investigated outcomes included physical properties (surface roughness, color changes, water sorption/solubility) and mechanical properties (flexural strength, elastic modulus, microhardness). Conclusions: Three-dimensionally printed permanent resins show promising potential for fabricating indirect dental restorations. However, the current evidence regarding their mechanical and physical properties remain limited and inconsistent, mainly due to variability in study methodologies. Full article

This study explores the potential of biodegradable Bioglass 45S5 formulations as a dual-function approach for preventing and treating Staphylococcus aureus infections in orthopaedic surgery while addressing the growing concern of antimicrobial resistance (AMR). The research focuses on the development and characterisation of antibiotic-loaded BG45S5 formulations, assessing parameters such as drug loading efficiency, release kinetics, antimicrobial efficacy, and dissolution behaviour. Key findings indicate that the F2l-BG45S5-T-T-1.5 and F2l-BG45S5-T-V-1.5 formulations demonstrated controlled antibiotic release for up to seven days, with size distributions of D(10): 7.11 ± 0.806 µm, 4.96 ± 0.007 µm; D(50): 25.34 ± 1.730 µm, 25.20.7 ± 0.425 µm; and D(90): 53.7 ± 7.95 µm, 56.10 ± 0.579 µm, respectively. These formulations facilitated hydroxyapatite formation on their surfaces, indicative of osteogenic potential. The antimicrobial assessments revealed zones of inhibition against methicillin-susceptible Staphylococcus aureus (MSSA, ATCC-6538) measuring 20.3 ± 1.44 mm and 24.6 ± 1.32 mm, while for methicillin-resistant Staphylococcus aureus (MRSA, ATCC-43300), the inhibition zones were 21.6 ± 1.89 mm and 22 ± 0.28 mm, respectively. Time-kill assay results showed complete bacterial eradication within eight hours. Additionally, biocompatibility testing via MTT assay confirmed cell viability of >75%. In conclusion, these findings highlight the promise of antibiotic-loaded BG45S5 as a multifunctional biomaterial capable of both combating bone infections and supporting bone regeneration. These promising results suggest that in vivo studies should be undertaken to expedite these materials into clinical applications. Full article

The Kindlin family of scaffold proteins plays key roles in integrin-mediated processes. Kindlin-1 and -2, encoded by the FERMT1 and FERMT2 genes, respectively, are expressed in the epidermis. Kindlin-1 plays protective roles against the development of cutaneous squamous cell carcinomas (cSCCs) in epidermal keratinocytes. However, the role of Kindlin-2 in transformed epidermal keratinocytes has remained virtually unexplored. In this study, we used siRNA approaches to generate Kindlin-2-depleted cells in three isogenic transformed keratinocyte lines. PM1, MET1, and MET4 cells model, respectively, a precancerous lesion, a primary cSCC, and a metastatic lesion of the latter. MET1 cells express both Kindlin-1 and -2. However, Kindlin-1 was not detectable in PM1 and MET4 cells. FERMT2 silencing in PM1 and MET4, but not in MET1 cells, reduced proliferation and the ability to adhere to culture surfaces and spreading. Furthermore, Kindlin-2-depleted PM1 and MET4, but not MET1 cells, exhibited decreased numbers of focal adhesions, as well as an altered F-actin and microtubule cytoskeletal organization. Significantly, FERMT2 silencing reduced the directional migration in all three cell types. These findings are consistent with the concept that, in the absence of other Kindlin orthologues, Kindlin-2 plays a prominent role in the modulation of the proliferation, spreading, focal adhesion assembly, and motility of transformed keratinocytes, as exemplified by PM1 and MET4 cells. Full article

This study investigates the foundational causes of unsustainability that obstruct efforts to address global challenges such as climate change, environmental degradation, water crises, and public health deterioration. Using qualitative research with in-depth expert interviews from education, environmental studies, and business, it finds that these global challenges, while visible on the surface, are deeply rooted in worldviews that shape human behavior, societal structures, and policies. Building on this insight, the thematic analysis manifests three interrelated systemic paradigms as the fundamental drivers of unsustainability: a crisis of wholeness, reflected in fragmented identities and collective disorientation; a disconnection from nature, shaped by human-centered perspectives; and the influence of dominant political-economic systems which prioritize growth logics over ecological and social concerns. These paradigms underlie both structural and cognitive barriers to systemic transformation, which influence the design and implementation of education for sustainability. By clarifying a body of knowledge and systemic paradigms regarding unsustainability, this paper calls for transformative education that promotes a holistic, value-based approach, eco-empathy, and critical thinking, aiming to equip future generations with the tools to challenge and transform unsustainable systems. Full article

Accelerated industrialization and surging energy demands have led to continuously rising atmospheric CO₂ concentrations. Developing sustainable methods to reduce atmospheric CO₂ levels is crucial for achieving carbon neutrality. Concurrently, the rapid development of new energy vehicles has driven a significant increase in demand for lithium-ion batteries (LIBs), which are now approaching an end-of-life peak. Efficient recycling of valuable metals from spent LIBs represents a critical challenge. This study employs conventional hydrometallurgical processing to recover valuable metals from spent LIBs. Subsequently, Ni-doped Co₃O₄ (Ni:Co₃O₄) supported on the natural mineral attapulgite (ATP) was synthesized via a sol–gel method. The incorporation of a small amount of Ni into the Co₃O₄ lattice generates oxygen vacancies, inducing a localized surface plasmon resonance (LSPR) effect, which significantly enhances charge carrier transport and separation efficiency. During the photocatalytic reduction of CO₂, the primary product CO generated by the Ni:Co₃O₄/ATP composite achieved a high production rate of 30.1 μmol·g⁻¹·h⁻¹. Furthermore, the composite maintains robust catalytic activity even after five consecutive reaction cycles. Full article