Search Results (80,653)

While fiber-reinforced polymer (FRP) sheets effectively enhance the flexural strength of reinforced concrete (RC) slabs, excessive flexural strengthening can reduce ductility and lead to brittle failure. This study provides an overview of the failure limits for the end spans of continuous RC slabs, considering the relationship between moment and shear capacities. A design approach for maximizing the strength contribution and amount of carbon FRP (CFRP) while ensuring ductile failure in strengthened slabs was developed and refined based on ACI standard recommendations. The failure mode of the strengthened slab was validated through numerical analysis using Abaqus software by further investigating the stress distribution of flexural members. Analytical results indicated that a 0.15 mm thick CFRP layer could enhance the nominal failure load by 148% while preserving desirable ductile failure behavior, demonstrating the effectiveness and feasibility of the proposed approach. Full article

The cotton–melon aphid (Aphis gossypii Glover), a globally distributed polyphagous pest, primarily infests cucurbit crops and leads to significant reductions in both crop yield and quality. Overreliance on chemical insecticides has resulted in widespread resistance development, highlighting the urgent requirement for alternative control strategies. This study evaluates the potential of topical RNA interference (RNAi) for managing cotton–melon aphids. We first analyzed instar-specific expression profiles of four candidate RNAi target genes (ATPE, IAP, Cat, and ilvE), employed topical dsRNA delivery to silence these genes, and subsequently evaluated their effects on aphid mortality, growth rates, and reproductive capacity. Furthermore, we investigated the non-target effects of RNAi-treated aphids on the predator ladybird beetles Propylea japonica. The results indicate that topical dsRNA delivery successfully silenced the target genes, significantly impairing aphid development and fecundity while inducing mortality, with no adverse effects on the beneficial predator. This method provides a powerful tool for insect gene functional studies and a promising solution for RNAi-based pest management. Full article

The rapid development of Connected and Autonomous Vehicles (CAVs) presents challenges in managing mixed traffic flows. Previous studies have primarily focused on mixed traffic flow involving CAVs and Human-Driven Vehicles (HDVs), or on the combination of trucks and cars. However, these studies have not fully addressed the heterogeneous mixed traffic flow consisting of CAVs and HDVs, including trucks and cars, influenced by varying human driving styles. Therefore, this study investigates the influences of the market penetration rate (MPR) of CAVs, truck proportion, and driving style on operational characteristics in heterogeneous mixed traffic flow. A total of 1105 events were extracted from highD dataset to analyze four car-following types: car-following-car (CC), car-following-truck (CT), truck-following-car (TC), and truck-following-truck (TT). Principal Component Analysis (PCA) and clustering techniques were employed to categorize distinct driving styles, while the Intelligent Driver Model (IDM) was calibrated to represent the various car-following behaviors. Subsequently, microscopic simulations were conducted using the Simulation of Urban Mobility (SUMO) platform to evaluate the impact of CAVs on sustainable traffic operations, including road capacity, stability, safety, traffic oscillations, fuel consumption, and emissions under various traffic conditions. The results demonstrate that CAVs can significantly enhance road capacity, improve emissions, and stabilize traffic flow at high MPRs. For instance, when the MPR increases from 40% to 80%, the road capacity improves by approximately 25%, while stability enhances by approximately 33%. In contrast, higher truck proportions lead to reduced capacity, increased emissions, and decreased traffic flow stability. In addition, an increased proportion of mild drivers reduces capacity, raises emissions per kilometer, and improves stability and safety. However, a high proportion of mild human drivers (e.g., 100% mild drivers) may negatively impact traffic safety when CAVs are present. This study provides valuable insights into evaluating heterogeneous traffic flows and supports the development of future traffic management strategies for more sustainable transportation systems. Full article

This article delves into the problem of fuzzy adaptive event-triggered (ET) formation control for nonholonomic mobile robots (NMRs) subject to full-state constraints. Fuzzy logic systems (FLSs) are employed to identify the unknown nonlinear functions within the system. To guarantee that all system states remain within their constraint boundaries, barrier Lyapunov functions (BLFs) are meticulously constructed. Subsequently, within the framework of the backstepping control design algorithm, we propose a novel fuzzy adaptive ET formation controller. Our ET mechanism can achieve an overall resource-saving rate of 88.17% for the four robots. Rigorous theoretical analysis demonstrates that the designed strategy not only ensures the stability of the controlled NMRs but also enables the formation tracking errors to converge to a small neighborhood around zero. Notably, the BLFs-based control approach presented herein endows the system with the capacity to avoid collisions to a certain degree, enhancing the overall safety and reliability of the robot formation. Finally, a simulation example is provided. The results vividly illustrate the effectiveness and practicality of the proposed theory, validating its potential for real-world applications in the field of nonholonomic mobile robot formation control. Full article

The adoption of land cover standards is essential for resolving inconsistencies in global, regional, and national land cover datasets. This study examines the challenges associated with integrating existing datasets, including variations in land cover class definitions, classification methodologies, limited interoperability, and reduced comparability across scales. Focusing on Ghana as a case study, this research aims to develop a land cover legend and land cover map aligned with International Organization for Standardization (ISO) 19144-2 standards, evaluate the effectiveness of improving land cover classification and accuracy of data, and finally, assess the challenges and opportunities for the adoption of land cover standards. This study uses a multi-sensor remote sensing approach, integrating Sentinel-1 and Sentinel-2 optical imagery with ancillary data (elevation, slope, and aspect), to produce a national land cover dataset for 2023. Using the random forest (RF) algorithm, the land cover map was developed based on a land cover legend derived from the West African land cover reference system (WALCRS). The study also collaborates with national and international organizations to ensure the dataset meets global reporting standards for Sustainable Development Goals (SDGs), including those for land degradation neutrality. Using a survey form, stakeholders in the land cover domain were engaged globally (world), regionally (Africa), and nationally (Ghana), to assess the challenges to and opportunities for the adoption of land cover standards. The key findings reveal a diverse range of land cover types across Ghana, with cultivated rainfed areas (28.3%), closed/open forest areas (19.6%), and savanna areas (15.9%) being the most dominant classes. The classification achieved an overall accuracy of 90%, showing the robustness of the RF model for land cover mapping in a heterogeneous landscape such as Ghana. This study identified a limited familiarity with land cover standards, lack of documentation, cost implication, and complexity of standards as challenges to the adoption of land cover standards. Despite the challenges, this study highlights opportunities for adopting land cover standards, including improved data accuracy, support for decision-making, and enhanced capacity for monitoring sustainable land cover changes. The findings highlight the importance of integrating land cover standards to meet international reporting requirements and contribute to effective environmental monitoring and sustainable development initiatives. Full article

The epidermis acts as the body’s primary defense, relying on components like lipids, HA and GSH for skin barrier function, hydration and resistance to oxidative stress. However, limitations in the topical application of these biomolecules call for novel approaches. This study investigates the efficacy of Pro-GHL, a blend of free fatty acids, acetylglucosamine and GSH amino acid precursors (GAPs), designed to replenish skin lipids, HA and GSH through de novo biosynthesis. Using primary human keratinocytes, Pro-GHL demonstrated superior antioxidant and anti-inflammatory capacities compared to each individual component under the challenge of UVB or blue light. In 3D skin equivalent models (EpiKutis^®), Pro-GHL enhanced skin barrier function. In addition, Pro-GHL prevented the development of pigmentation in pigmented 3D skin equivalent models (MelaKutis^®) subjected to UVB irradiation or Benzo[a]pyrene exposure. Together, these results highlight Pro-GHL’s potential as a novel, effective and comprehensive skincare approach to fortify the skin’s defense system from within and prevent the accumulation of tissue damage in response to extrinsic stressors. Full article

Hard carbon (HC) is considered to be a highly promising anode material for sodium-ion batteries. However, the synthesis conditions and pore structure regulation are still challenging for high-capacity sodium-ion storage. In this study, HCs using polyethylene glycol terephthalate (PET) as a carbon resource and ZnO as a nanopore template were synthesized and systematically investigated. By optimizing the additive amount of zinc gluconate, the starting material for ZnO, PET-derived HCs with a proper mesoporous structure were obtained. The as-prepared hard carbon demonstrated a high reversible capacity of 389.42 mAh·g⁻¹ at 20 mA·g⁻¹, with the plateau capacity accounting for 68%. After 75 cycles, the discharge capacity stabilized at 367.73 mAh·g⁻¹ with a retention ratio of 89.4%. The rate performance test indicated that a proper mesopore structure helped to improve the sodium-ion diffusion coefficient, effectively enhancing the charge–storage kinetics. This work provides a promising strategy for converting PET into valuable carbon materials for application in the field of renewable energy technology. Full article

Ecological carrying capacity (ECC) is a crucial indicator for assessing sustainable development capabilities. However, mountain ecosystems possess unique complexities due to their diverse topography, high biodiversity, and fragile ecological environments. Addressing the current shortcomings in mountain ECC assessments, this paper proposes a novel hybrid evaluation framework that integrates improved ecological footprint (EF) and ecosystem service value (ESV) approaches with spatial econometric models. This framework allows for a more comprehensive understanding of the dynamic changes and driving factors of the mountain ecological carrying capacity index (ECCI), using Pingbian County as a case study. The results indicate the following: (1) Land use changes and biodiversity exert varying impacts on the ECCI across different regions. The ECCI decreased by 42% from 2003 to 2021 (from 4.41 to 2.54), exhibiting significant spatial autocorrelation and heterogeneity. (2) The ecological service value coefficient is the main factor increasing the ECCI, while the energy consumption value and per capita consumption value inhibited the increase in the ECCI. For every 1% increase in the ecosystem service value coefficient, the ECCI increased by 0.66%, whereas every 1% increase in energy consumption value and per capita consumption value reduced the ECCI by 0.18% and 0.28%, respectively. (3) The overall spatial distribution pattern of the ECCI is primarily “southwest to northeast”, with the distance of centroid migration expanding over time. Based on these key findings, implementing differentiated land use practices and ecological restoration measures can effectively enhance the mountain ECCI, providing scientific support for the sustainable management of mountain areas. Full article

Electric Road Systems (ERS) are emerging technologies that enable electricity transfer to electric vehicles in motion. However, their implementation presents challenges due to high energy demands and infrastructure requirements. This technology offers a significant opportunity for decarbonizing road freight transport, one of the most carbon-intensive sectors, contributing to the European Union’s climate goals. This study hypothesizes that implementing an inductive ERS for freight transport along the AP-7 corridor in Spain will generate environmental benefits—primarily through greenhouse gas (GHG) emission reductions—that outweigh the associated socioeconomic costs, making it a viable decarbonization strategy. To test this hypothesis, an impact assessment framework based on Cost–Benefit Analysis (CBA) is conducted, incorporating climate change and other environmental benefits. The framework is applied to a section of the Mediterranean Highway Corridor AP-7 in Spain. The results indicate that the most significant benefits are derived from positive environmental impacts and lower vehicle operation costs. Through a sensitivity analysis, our research identifies key variables affecting the system’s socioeconomic profitability, including payload capacity, volatility of energy prices and shadow prices of GHG emissions. The study provides insights for policymakers to optimize ERS deployment strategies, ensuring maximum social benefits while addressing economic and environmental challenges. Full article

The use of graphene oxide (GO) in combination with mesoporous materials has gained interest in the development of adsorbents. In this study, GO was impregnated into zeolite at three concentrations (ZGO2.5, ZGO5, and ZGO10) through a simple thermal process to enhance the adsorption of methylene blue (MB). Characterization of the resulting materials was performed using spectroscopic techniques such as UV-Vis and FT-IR spectroscopy, SEM, and EDS, confirming the presence of GO on zeolite. Batch experiments were conducted to evaluate their performance, analyzing contact time, pH effect, and adsorption kinetics. Pseudo-first-order, pseudo-second-order, and Elovich kinetic models were applied, and the adsorption mechanism was studied using Langmuir, Freundlich, Temkin II, and Dubinin–Radushkevich (D-R) isotherms at different temperatures. Optimal adsorption was achieved at 273 K, 100 mg L⁻¹ of MB, adsorbent mass of 100 mg, 250 rpm, and pH 5–9, with 90% removal efficiency after 70 min. The pseudo-second-order, Freundlich, and D-R models best described the process (R² > 0.98), suggesting a mixed physisorption–chemisorption mechanism. The maximum adsorption capacity from the D-R isotherm reached 119 mg g⁻¹ at 333 K. Thermodynamic studies showed that adsorption was a spontaneous and endothermic process. These findings highlight the potential of GO-impregnated zeolite as an effective adsorbent for MB. Full article

This study presents analytical models for simulating the thermal properties of linear triatomic systems, using the modified Rosen–Morse oscillator and harmonic oscillator potential to represent vibrational modes. The models employ existing partition functions to derive the thermodynamic functions for the symmetric, asymmetric, and 2-fold degenerate bending modes. These thermodynamic functions are applied to gaseous triatomic molecules such as BO₂, HCN, N₃, and Si₂N. The results demonstrate high accuracy, with mean percentage absolute deviations (MPAD) of less than 0.17% for molar entropy and Gibbs free energy. For enthalpy and heat capacity, MPAD values are below 2% compared to National Institute of Standards and Technology (NIST) data. The findings are in strong agreement with the existing literature on gaseous triatomic molecules, confirming the reliability of the proposed models. Full article

Natural gas hydrate (NGH) is a clean resource characterized by abundant potential reserves, clean combustion, and high energy density. Although significant progress has been made in the development of NGH resources all around the world, challenges still exist that hinder commercial exploitation, such as a low daily gas production rate and short steady production periods. One significant reason lies in the complex gas–liquid–solid phase transitions occurring within the formation during production, which lead to changes in flow capacity. Understanding the phase change mechanism of NGH reservoirs will help to further reveal the production increase mechanism. To address the phase transitions’ effect on production, this paper establishes a numerical simulation model for the depressurization exploitation of natural gas hydrates in order to investigate phase transition characteristics at the field scale. First, the phase equilibrium calculation method is presented and the phase equilibrium curve is modified by considering the capillary effect, soluble salt, and surface adsorption. Then, the phase transition model is successfully characterized in a simulation and the numerical simulation model is established based on the first test project parameters in the Shenhu area. The production characteristics of different sediment types (montmorillonite, South China Sea sediments, kaolin, and silt) are analyzed under the effects of water content and salinity. It is shown that lower initial water content and higher salinity result in higher gas production. The results provide a better understanding of the effects of phase transition parameters on NGH production at the field scale. Full article

There is a need for new technologies in photoprotection. The negative effects of solar exposure on the skin have been amply demonstrated and there is an urgency for the development of alternative photoprotective approaches. In this respect, natural extracts represent the most interesting and promising source. Among them, Aspalathus linearis extracts appear to be an excellent candidate due to supporting evidence, their multiple beneficial biological effects, and their robust toxicological profile. Here, we first explored the photoprotective properties of two different Aspalathus linearis extracts (fermented and unfermented) individually, and then in combination, in a simplified model assessing Normal Human Dermal Fibroblast survival after UVB radiation. Surprisingly, we found the fermented extract to be more photoprotective than the unfermented one. In addition, a specific combination of the two extracts showed a synergistic effect. By HPLC and FRAP analyses, we observed that the photoprotective effect did not correlate with the amount of Aspalathus linearis main characteristic metabolites nor with the antioxidant capacity of the ingredients. Finally, an additional photoprotective effect was observed when Aspalathus linearis extracts were combined with a Polypodium leucotomos extract (Fernblock^®), a well-known botanical ingredient with demonstrated photoprotection activities. Thus, this work provides a solid scientific basis for the inclusion of this technology in future topical and systemic photoprotective strategies. Full article

To address the challenges of carbon emission reduction in the global shipping industry and the requirements of the International Maritime Organization (IMO)’s Carbon Intensity Indicator (CII) rating, this paper takes China’s commuter ships as an example to study the dynamic optimization of ship routes based on CII implementation requirements. In response to the existing research gap in the collaborative optimization of routes and carbon emissions under CII constraints, this paper constructs a mixed-integer programming model that comprehensively considers CII limits, port throughput capacity, channel capacity, and the stochastic demand for spot cargo. The objective is to minimize the operating costs of shipping companies, and an adaptive genetic algorithm is designed to solve the dynamic route scheduling problem. Numerical experiments demonstrate that the model can reasonably plan routes under different sequences of spot cargo arrivals, ensuring compliance with CII ratings while reducing total costs and carbon emissions. The results indicate that the proposed method provides efficient decision-making support for dynamic ship scheduling under CII constraints, contributing to the green transformation of the shipping industry. Future work will extend the model to scenarios involving multiple ship types and complex maritime conditions, further enhancing its applicability. Full article

With the rapid development of UAV technology, UAV delivery has gained attention for its potential to reduce labor costs. However, limitations in load capacity and energy restrict UAVs’ distribution capabilities. This paper proposes a cooperative delivery scheme combining traditional trucks and UAVs to extend UAV coverage and improve delivery completion rates. For densely distributed depots in wide-area regions, we develop algorithms for task allocation and path planning in a truck-independent UAV system. Specifically, a minimum-cost, maximum-flow model is constructed to obtain sub-paths covering all delivery tasks, and resource tree-based algorithms are used to construct global paths for UAVs and trucks. Simulation results show that our algorithms reduce total energy consumption by 11.53% and 9.15% under different task points, which suggests that our proposed method can significantly enhance delivery efficiency, offering a promising solution for future logistics operations. Full article