Search Results (2,832)

This study aims to assess the energy efficiency of LED luminaires used in public road lighting by comparing manufacturer-declared photometric and electrical parameters with laboratory simulation results. The research also evaluates the performance of these luminaires across various road types and installation configurations to determine compliance with national and international standards. Eleven LED luminaires were tested using a rotating mirror goniophotometer in an ISO/IEC 17025-accredited laboratory. Simulations were conducted using Dialux Evo software across six road types (M1–M6) and three installation configurations (unilateral, bilateral, and staggered). Key parameters analyzed included brog (L_m), overall uniformity (U₀), longitudinal uniformity (U_l), luminous efficacy (lm/W), power factor, and total harmonic distortion (THD) in voltage and current. Discrepancies were found between manufacturer-declared and simulation results, especially in higher-class roads (M1–M3), where up to 28.57% of luminaires failed to meet the minimum luminance requirements when tested. The study highlights the importance of validating manufacturer specifications through accredited laboratory testing. Overall, LED technology improves energy efficiency in public lighting, and inconsistencies in the power factor and luminance performance suggest the need for stricter regulatory oversight and more rigorous quality control. Simulation tools like Dialux Evo prove essential for optimizing lighting designs tailored to specific road types and traffic conditions. Full article

In Proton Exchange Membrane Water Electrolysis (PEMWE), the two-phase flow distribution in the anode field significantly affects overall electrolysis performance. Based on visualized experimental data, in this paper, the reaction kinetics equations were theoretically revised, and a three-dimensional, two-phase, non-isothermal, multi-physics coupled model of the electrolysis was developed and experimentally validated. Four different configurations of rectangular turbulence promoters were designed within the anode serpentine flow field and compared with a conventional serpentine flow field (SFF) in terms of their multi-physics distribution characteristics. The results showed that, in the double-row rectangular block serpentine flow field (DRB SFF), the uniformity of liquid water saturation, temperature, and current density improved by 16.6%, 0.49% and 40.8%, respectively. The normal mass transfer coefficient increased by a factor of 6.3, and polarization performance improved by 6.98%. A cross-arranged turbulence promoter structure was further proposed. This design maintains effective turbulence while reducing flow resistance and pressure drop, thereby enhancing mass transfer efficiency and overall electrolysis performance through improved bubble fragmentation. Full article

In extreme scenarios, to prevent the leakage of jamming coordination information, the jammers must proactively terminate their communication functions and implement jamming resource scheduling via Non-Networked Cooperation. However, current research on this non-networked jamming approach is relatively limited. Furthermore, existing algorithms either rely on networked interactions or lack cognitive strategies for the surrounding communication countermeasure situation. For example, they fail to adapt to dynamic changes in electromagnetic noise and struggle to determine jamming effectiveness, leading to low jamming efficiency and severe energy waste in non-networked scenarios. To address this issue, this paper establishes a game process and corresponding algorithm for non-networked communication countermeasures and designs cognitive, cooperative, and scheduling strategies for individual jammers. Meanwhile, a novel performance metric called the “Overall Communication Suppression Ratio (OCSR)” is proposed. This metric quantifies the relationship between “sustained full-suppression duration” and “ operating duration of the jamming system,” overcoming the defect that traditional metrics cannot evaluate the dynamic jamming effectiveness in non-networked scenarios. Experimental results indicate that although the OCSR of the proposed Intelligent Concentric Circle Algorithm (ICCA) is significantly lower than that of the Full-Power Jamming Algorithm (FPJA), ICCA extends the operating duration of the jamming system by 4.8%. This achieves non-uniform power setting of jammers, enabling flexible and dynamic jamming in non-networked scenarios and retaining more battery capacity for jammers after overall jamming failure. Full article

Cutaneous leishmaniasis is a zoonotic disease caused by Leishmania parasites and leads to chronic, non-healing skin lesions. Although current drugs can control the disease, their use is limited by systemic side effects, low efficacy, and inadequate lesion penetration. Therefore, innovative local delivery systems are required to enhance drug penetration and reduce systemic toxicity. To address these challenges, silver nanoparticles (AgNPs) were synthesized using propolis extract through a green synthesis approach, and a tri-layer wound dressing composed of polyvinyl alcohol and gelatin containing synthesized AgNPs and Glucantime was fabricated by electrospinning. Characterization (SEM-EDX, FTIR, TGA) confirmed uniform morphology, chemical structure, and thermal stability; the wound dressing exhibited hydrophilicity, antioxidant activity, and biphasic release. Biological evaluations against Leishmania tropica demonstrated significant antiparasitic activity. Promastigote viability decreased from 76.3% in neat fibers to 31.6% in nanofibers containing AgNPs and 7.9% in tri-layer nanofibers containing both AgNPs and Glucantime. Similarly, the amastigote infection index dropped from 410 in controls to 250 in neat nanofibers, 204 in AgNPs-containing nanofibers, and 22 in tri-layer nanofibers containing AgNPs and Glucantime. The tri-layer nanofibers demonstrated enhanced antileishmanial activity over AgNPs-containing fibers, confirming synergistic efficacy. All nanofibers were biocompatible, supporting their use as a safe platform for cutaneous leishmaniasis treatment. Full article

Current saw- and pin-type lint-cleaning systems used by the ginning industry have challenges retaining lint quality. The objective of the research was to test a novel pneumatic fractionator for the lint cleaning of an Upland cotton variety that was both saw- and roller-ginned. The process variables tested were initial lint moisture content in the range of 5.5–15% w.b., line pressure in the range of 276–552 kPa, and residence time in the range of 15–45 s. Experiments were conducted based on a central composite design. Models based on response surface methodology (RSM) were developed for final lint moisture, total trash extracted during lint cleaning, and High-Volume Instrument (HVI) fiber quality. The RSM models adequately described the pneumatic fractionation process, as indicated by the coefficient of determination, predicted vs. observed plots, and residual values. The results indicated that the interactions among initial lint moisture content, residence time, and line pressure significantly affected lint quality. At the optimized pneumatic fractionator process conditions, the predicted lint quality attributes were better for both roller- and saw-ginned lint compared to lint cleaned with saw- and pin-type lint cleaners. The upper half mean length increased by 1 mm, the uniformity index was higher by 0.5–1 percentage points, the strength was 1–2 g/tex higher, and the short fiber content was reduced by more than one percentage point. Color grades were better for pneumatic fractionated lint compared to saw- and pin-type lint cleaning methods. Lint value was approximately 4 cents/kg higher for both saw- and roller-ginned pneumatic fractionated lint, compared to lint cleaned using saw- and pin-type lint cleaners. The novel pneumatic fractionator, when compared to industry-standard saw- and pin-type lint cleaners, effectively cleaned lint while retaining fiber quality and removing most of the motes and trash. Full article

Phosphorus is an essential resource for numerous industrial applications. However, its uneven global distribution makes Europe heavily dependent on imports. Recovering phosphorus from waste streams is therefore crucial for improving resource security. The FlashPhos project addresses this challenge by developing a process to recover phosphorus from sewage sludge, in which phosphorus-rich slag is produced in a flash reactor and subsequently reduced in a Submerged Arc Furnace (SAF). In this process, approximately 250 kg/h of sewage sludge is converted into slag, which is further processed in the SAF to recover about 8 kg/h of white phosphorus. This work focuses on the development of a computational model of the SAF, with particular emphasis on slag behaviour. Due to the extreme operating conditions, which severely limit experimental access, a numerically efficient three-dimensional CFD model was developed to investigate the internal flow of the three-phase, AC-powered SAF. The model accounts for multiphase interactions, dynamic bubble generation and energy sinks associated with the reduction reaction, and Joule heating. A temperature control loop adjusts electrode currents to reach and maintain a prescribed target temperature. To further reduce computational cost, a novel simulation approach is introduced, achieving a reduction in simulation time of up to 300%. This approach replaces the solution of the electric potential equation with time-averaged Joule-heating values obtained from a preceding simulation. The system requires transient simulation and reaches a pseudo-steady state after approximately 337 s. The results demonstrate effective slag mixing, with gas bubbles significantly enhancing flow velocities compared to natural convection alone, leading to maximum slag velocities of 0.9–1.0 m/s. The temperature field is largely uniform and closely matches the target temperature within ±2 K, indicating efficient mixing and control. A parameter study reveals a strong sensitivity of the flow behaviour to the slag viscosity, while electrode spacing shows no clear influence. Overall, the model provides a robust basis for further development and future coupling with the gas phase. Full article

In this study, the service behavior of an X65 oil and gas pipeline in seawater and production water environments was simulated by a corrosion experiment, and the influence of surface treatment (polishing and scratching) on its corrosion behavior was systematically analyzed. The corrosion resistance of the material was evaluated by means of scanning electron microscopy (SEM), an electrochemical test, and uniform corrosion rate calculations. The results show that the corrosion degree of X65 steel in an oilfield production water environment is significantly higher than that in a seawater environment. The uniform corrosion rate of the welding area is as high as 1.05 mm/y, which is more sensitive than that of the matrix material. The surface treatment has a significant effect on the corrosion behavior. The polishing treatment reduces the corrosion current density of the matrix material from 472.44 μA/cm² to 313.10 μA/cm², and the polarization resistance increases to 14.07 kΩ·cm², which effectively improves its corrosion resistance. The scratch treatment significantly reduces the corrosion resistance of the material, and the corrosion current density of the welding area at the scratch site is as high as 313.00 μA/cm², even more than that of the untreated matrix material. The study further points out that the scratches and welding areas generated during the pipeline cleaning process will significantly aggravate the tendency of local corrosion and pitting corrosion due to their microstructure heterogeneity. This study provides a clear theoretical basis and engineering guidance for the anti-corrosion design and maintenance of offshore oil and gas pipelines in complex water quality environments. Full article

Hilly and mountainous areas are important agricultural production regions globally. Their dramatic topography, dense fruit tree planting, and steep slopes severely restrict the application of traditional plant protection machinery. Pest and disease control has long relied on manual spraying, resulting in high labor intensity, low efficiency, and pesticide utilization rates of less than 30%. Plant protection UAVs, with their advantages of flexibility, high efficiency, and precise application, provide a feasible technical approach for plant protection operations in hilly and mountainous areas. However, steep slopes and dense orchard environments place higher demands on key technologies such as drone positioning and navigation, attitude control, trajectory planning, and terrain following. Achieving accurate identification and adaptive following of the undulating fruit tree canopy while maintaining a constant spraying distance to ensure uniform pesticide coverage has become a core technological bottleneck. This paper systematically reviews the key technologies and research progress of plant protection UAVs in hilly and mountainous operations, focusing on the principles, advantages, and limitations of core methods such as multi-sensor fusion positioning, intelligent SLAM navigation, nonlinear attitude control and intelligent control, three-dimensional trajectory planning, and multimodal terrain following. It also discusses the challenges currently faced by these technologies in practical applications. Finally, this paper discusses and envisions the future of plant protection UAVs in achieving intelligent, collaborative, and precise operations on steep slopes and in dense orchards, providing theoretical reference and technical support for promoting the mechanization and intelligentization of mountain agriculture. Full article

Shape-memory polymers (SMPs) are a class of smart materials capable of recovering their original shape from a programmed temporary shape in response to external stimuli such as heat, light, or magnetic fields. SMPs have attracted significant interest for biomedical devices and soft robotics due to their large recoverable strains, programmable mechanical and thermal properties, tunable activation temperatures, responsiveness to various stimuli, low density, and ease of processing via additive manufacturing techniques, as well as demonstrated biocompatibility and potential bioresorbability. This review summarises recent progress in the fundamentals, classification, activation mechanisms, and fabrication strategies of SMPs, focusing particularly on design principles that influence performance relevant to specific applications. Both thermally and non-thermally activated SMP systems are discussed, alongside methods for controlling activation temperatures, including plasticisation, copolymerisation, and modulation of cross-linking density. The use of functional nanofillers to enhance thermal and electrical conductivity, mechanical strength, and actuation efficiency is also considered. Current manufacturing techniques are critically evaluated in terms of resolution, material compatibility, scalability, and integration potential. Biodegradable SMPs are highlighted, with discussion of degradation behaviour, biocompatibility, and demonstrations in devices such as haemostatic foams, embolic implants, and bone scaffolds. However, despite their promising potential, the widespread application of SMPs faces several challenges, including non-uniform activation, the need to balance mechanical strength with shape recovery, and limited standardisation. Addressing these issues is critical for advancing SMPs from laboratory research to clinical and industrial applications. Full article

Polyurea, a novel spray-applied composite polymer, is of high application importance for rapid roadway support in coal mines. The current study investigates the dynamic process and mechanisms governing the impact and spreading of polyurea droplets on rough surfaces through experimental and theoretical approaches. The key novelty lies in revealing how spontaneously varying viscosity couples with surface microstructure to produce novel scaling laws distinct from classical Newtonian behavior. The droplet impact and wetting process can be divided into three stages. In the pinning stage, droplet behavior is dominated by kinetic energy, leading to inertia-driven spreading in which the contact line radius increases quite slowly with time. In the penetration stage, the apparent three-phase contact line (TPCL) is pinned by surface microstructures, while the real TPCL evolves with time following a temporal scaling law t^3/2. In the spreading stage, surface roughness becomes decisive. On low-roughness substrates, limited pinning allows the real and apparent TPCLs to spread synchronously, with TPCL evolution governed by surface tension and viscous forces, following a t^1/8 scaling law. As roughness increases, pinning effects strengthen, causing divergence: the real TPCL is driven by surface tension and viscous dissipation between microstructures, whereas the apparent TPCL is additionally influenced by pinning and reaction-induced viscosity, scaling as t^1/24. This t^1/24 scaling for the apparent contact line on relatively high-roughness surfaces represents a significant deviation from established scaling relations. Experiments on rock-like substrates confirm these mechanisms for polyurea droplets. These findings provide theoretical and engineering guidance for optimizing spray-coating parameters in coal mines, with the goal of improving coating uniformity and interfacial adhesion. Full article

Background: Hyperbaric oxygen therapy (HBOT) is considered a potential adjunctive modality to enhance tissue regeneration in oral and maxillofacial surgery. By increasing tissue oxygen availability, HBOT may support bone and soft-tissue repair under hypoxic and chronically inflamed conditions. Aim: This narrative review evaluates current experimental and clinical evidence regarding HBOT in high-risk dental indications, including osteoradionecrosis (ORN), medication-related osteonecrosis of the jaw (MRONJ), chronic osteomyelitis, poorly healing postoperative wounds, and procedures in patients with systemic comorbidities. Methods: A structured search of PubMed, Web of Science, and the Cochrane Library identified 123 relevant English-language publications (from 1 January 2000–September 2025) addressing HBOT mechanisms and clinical applications in oral and maxillofacial surgery, including clinical trials, observational studies, preclinical models, and systematic reviews. Results: Available evidence suggests that HBOT may improve healing outcomes and reduce complication rates in early-stage ORN and MRONJ when used as an adjunct to surgery and systemic therapy. However, findings in implantology—particularly in irradiated or diabetic patients—and in periodontal therapy remain limited, heterogeneous, and methodologically inconsistent. Conclusions: HBOT may be considered in selected clinical scenarios, particularly where healing is impaired by hypoxia or systemic disease. Nevertheless, current evidence remains insufficient to support routine use. Standardized, high-quality studies with clearly defined endpoints and uniform therapeutic protocols are needed to determine its clinical effectiveness and optimal indications. Full article

The electrochemical reduction of CO₂ to ethanol represents a sustainable alternative to recycle CO₂ into a value-added product, yet achieving high selectivity and efficiency remains a challenge. This work explores Cu-based catalysts supported on SiO₂ and ZrO₂, with and without ZnO doping, for ethanol production in a continuous flow-cell system. Gas diffusion electrodes are fabricated using commercial catalysts with varying Cu loadings (5–10%) and ZnO contents (2–3.5%). Comprehensive characterization by XPS confirms the presence of Cu²⁺ and Zn²⁺ species, while SEM reveals that ZnO incorporation improves surface uniformity and aggregate distribution compared to undoped samples. Electrochemical tests demonstrate that 10% Cu on SiO₂ achieves a Faradaic efficiency of 96% for ethanol at −3 mA cm⁻², outperforming both doped catalysts and previously reported materials. However, efficiency declines at higher current densities, indicating a trade-off between selectivity and productivity. ZnO doping enhances C₂⁺ product formation but does not surpass the undoped catalyst in ethanol selectivity. These results underline the importance of catalyst composition, support interactions, and operating conditions, and point to further optimization of electrode architecture and cell configuration to sustain high ethanol yields under industrially relevant conditions. Full article

Coastal shipping plays a critical role in meeting maritime decarbonization targets under the International Maritime Organization’s (IMO) Carbon Intensity Indicator (CII) and the European Union Emissions Trading System (EU ETS); however, operators currently lack robust tools to forecast route-specific carbon intensity and evaluate the causal benefits of fuel switching. This study developed a distribution-free causal forecasting framework for voyage-level Carbon Dioxide (CO₂) intensity using an enriched panel of 1440 real-world voyages across four Nigerian coastal routes (2022–2024). We employed a physics-informed monotonic Light Gradient Boosting Machine (LightGBM) model trained under a strict leave-one-route-out (LORO) protocol, integrated with split-conformal prediction for uncertainty quantification and Causal Forests for estimating heterogeneous treatment effects. The model predicted emission intensity on completely unseen corridors with a Mean Absolute Error (MAE) of 40.7 kg CO₂/nm, while 90% conformal prediction intervals achieved 100% empirical coverage. While the global average effect of switching from heavy fuel oil to diesel was negligible (≈−0.07 kg CO₂/nm), Causal Forests revealed significant heterogeneity, with effects ranging from −74 g to +29 g CO₂/nm depending on route conditions. Economically, targeted diesel use becomes viable only when carbon prices exceed ~100 USD/tCO₂. These findings demonstrate that effective coastal decarbonization requires moving beyond static baselines to uncertainty-aware planning and targeted, route-specific fuel strategies rather than uniform fleet-wide policies. Full article

CO₂ laser processing has emerged as an efficient dry-finishing technique capable of inducing controlled chemical and morphological transformations in cotton and denim textiles. The strong mid-infrared absorption of cellulose enables localised photothermal heating, leading to selective dye decomposition, surface oxidation, and micro-scale ablation while largely preserving the bulk fabric structure. These laser-driven mechanisms modify colour, surface chemistry, and topography in a predictable, parameter-dependent manner. Low-fluence conditions predominantly produce uniform fading through fragmentation and oxidation of indigo dye; in comparison, moderate thermal loads promote the formation of carbonyl and carboxyl groups that increase surface energy and enhance wettability. Higher fluence regimes generate micro-textured regions with increased roughness and anchoring capacity, enabling improved adhesion of dyes, coatings, and nanoparticles. Compared with conventional wet processes, CO₂ laser treatment eliminates chemical effluents, strongly reduces water consumption and supports digitally controlled, Industry 4.0-compatible manufacturing workflows. Despite its advantages, challenges remain in standardising processing parameters, quantifying oxidation depth, modelling thermal behaviour, and assessing the long-term stability of functionalised surfaces under real usage conditions. In this review, we consolidate current knowledge on the mechanistic pathways, processing windows, and functional potential of CO₂ laser-modified cotton substrates. By integrating findings from recent studies and identifying critical research gaps, the review supports the development of predictable, scalable, and sustainable laser-based cotton textile processing technologies. Full article

New-generation geostationary meteorological satellite radiometric imagers widely employ multi-column redundant long-linear-array detectors, for which the Best Detector Selection (BDS) strategy is crucial for enhancing the quality of remote sensing data. Addressing the limitation of current BDS methods that often rely on a single metric and thus fail to fully exploit the detector’s comprehensive performance, this paper proposes a detector evaluation method based on a modified Z-score. This method systematically categorizes detector metrics into three types: positive, negative, and uniformity. It introduces, for the first time, spectral response deviation (SRD) as an effective quantitative measure for the Spectral Response Function (SRF) and employs a robust normalization strategy using the Interquartile Range (IQR) instead of standard deviation, enabling multi-dimensional detector evaluation and selection. Validation using laboratory data from the FY-4C/AGRI long-wave infrared band demonstrates that, compared to traditional single-metric optimization strategies, the best detectors selected by our method show significant improvement across multiple performance indicators, markedly enhancing both data quality and overall system performance. The proposed method features low computational complexity and strong adaptability, supporting on-orbit real-time detector optimization and dynamic updates, thereby providing reliable technical support for high-quality processing of remote sensing data from geostationary meteorological satellites. Full article