Search Results (3,764)

Submarine pipelines are highly susceptible to lateral buckling failure under service conditions of high temperature and pressure. While existing bearing capacity evaluation methods mainly focus on flat seabeds, research on the ultimate bearing capacity of pipelines buried in sloping seabeds is limited. This study applies the FELA method to analyze the ultimate bearing capacity of pipelines buried in inclined sandy seabeds under various loading directions. The results reveal that in sloping seabeds, the minimum ultimate bearing capacity (P_u,b) does not occur in the vertical direction, but rather deviates toward the outward normal direction of the seabed surface, moving toward the foot of the slope. The P_u,b is only 57% of the uplift bearing capacity in the extreme case. A predictive model was proposed to accurately determine the direction of P_u,b. The results also indicated that increasing the seabed slope angle leads to a significant reduction of bearing capacity, while increases in the internal friction angle of the seabed and the pipeline–soil interface friction angle enhance the bearing capacity. Moreover, the design code of DNV (2017) was identified as unsafe due to its omission of seabed inclination effects, and the P_u,b is only 75% of the best estimate of DNV (2017) in the extreme case. A reduction factor model was developed to mitigate this gap, offering a more reliable framework for evaluating the bearing capacity of pipelines. Full article

Bone is a calcified tissue composed of 60% inorganic compounds, 30% organic compounds, and 10% water. Bone exhibits an intrinsic regenerative capacity, enabling it to heal after fractures or adapt during growth. However, in cases of severe injury or extensive tissue loss, this regenerative capacity becomes insufficient, often necessitating bone graft surgeries using autografts or allografts. Conventional grafting approaches present several limitations, driving the development of alternative strategies in tissue engineering. The system of hydrogel–nanoparticles (NPs) represents a new class of biomaterials designed to combine the advantages of both materials while mitigating their drawbacks. This review focuses on a combination of nature-based hydrogels with different types of nanoparticles and discusses their potential applications in bone regeneration. Full article

Artificial ground freezing (AGF), recognized for its environmental sustainability and safety, is commonly used in underground construction projects within water-saturated soils. This study presents the design scheme and monitoring results of an AGF reinforcement project for a cross passage located in strata with low seepage velocity on Hohhot Metro Line 2. A transient heat transfer model, based on the assumption of no seepage, was developed, incorporating phase transitions and nonlinear changes in thermal parameters. In the model, soil thermal parameters are treated as variables dependent on unfrozen water content, which is represented by the soil freezing characteristic curve (SFCC). To derive the SFCC expressions, a semi-empirical approach was employed. This approach avoids the complexity of obtaining SFCCs experimentally and mitigates the arbitrariness inherent in the commonly used traditional apparent heat capacity method. The model was subsequently validated using experimental data from the literature and field monitoring results. The development and key indicators, including the thickness and average temperature of the frozen curtain in a single stratum without seepage, were investigated. The results show that the central and slightly right areas of the cross-passage axis exhibit a thinner frozen curtain and higher average temperature, especially in the pump room area, where the effective thickness of the curtain is at its minimum. Therefore, it is recommended to closely monitor the development of the frozen curtain in these areas and optimize the layout of freezing pipes. This study may serve as a reference for similar projects. Full article

Urban trees play a crucial role in regulating hydrological processes within urban ecosystems by intercepting rainfall to effectively reduce surface runoff and mitigate urban flooding. Current research lacks a systematic quantification of rainfall interception capacity and its community-level impacts at the urban scale. This study adopts a city-scale perspective, integrating field survey data with the i-Tree Eco model to systematically explore the contributions of 20 factors to the average annual rainfall interception of tree species and the average annual rainfall interception efficiency of communities. The study revealed that Deciduous broadleaf trees (1.28 m³ year⁻¹) and Pure coniferous forests (90.7 mm year⁻¹) exhibited substantial rainfall interception capacity. Relative Height, Average Tree Height, Average Crown Width, and Planting Density of trees significantly influence interception capacity. Urban planning can optimize the selection of tree species (e.g., Paulownia, Populus tomentosa, etc.) and community structure (e.g., mixed planting of conifers and deciduous broadleaf trees) to improve rainfall interception capacity, thereby effectively reducing stormwater runoff, mitigating the risk of urban flooding. These findings provide a scientific basis for designing urban vegetation to mitigate flooding, support water management, and advance sponge city development. Full article

With the global aging population, skeletal muscle aging has threatened to elderly health, making dietary interventions for age-related muscle decline a research priority. Lycium barbarum, a traditional food and medicinal herb, was used in the study to prepare Lycium barbarum water (LBW). This experiment was conducted in animals and included four groups: young control (C-Young), aged control (C-Aged), young LBW-drinking (G-Young), and aged LBW-drinking (G-Aged). Assessments covered skeletal muscle mass, cross-sectional area, and exercise ability to compare health status. The study measured mRNA expression of Atrogin-1 and MuRF-1 from the Forkhead Box O (FOXO) pathway, advanced glycation end products (AGEs) and senescence-associated β-galactosidase (SA-β-gal), oxidative stress levels via superoxide dismutase (SOD), malondialdehyde (MDA) and glutathione (GSH), inflammatory levels through interleukin-10 (IL-10) and tumor necrosis factor-alpha (TNF-α), and applied untargeted metabolomics to profile metabolic alterations. Optimal LBW was achieved at 80 °C with a 1:10 (w/v) solid-liquid ratio. In aged mice, long-term LBW administration improved exercise capacity, reduced muscle atrophy, and increased muscle mass, alongside decreased aging-related markers, alleviated oxidative stress, and modulated inflammatory levels. Additionally, metabolomics confirmed age-related oxidative stress and inflammation. Long-term LBW consumption alleviates age-related skeletal muscle dysfunction via multi-target regulation, holding promise as a natural nutritional intervention for mitigating skeletal muscle aging. Full article

Lithium–iron disulfide (Li-FeS₂) batteries are plagued by the polysulfide shuttle effect and cathode structural degradation, which significantly hinder their practical application. This study proposes a dual-strategy design that combines a polyacrylonitrile–carbon nanotube (PAN-CNT) composite cathode and a polyvinylidene fluoride (PVDF)-conductive carbon-coated separator to synergistically address these bottlenecks. The PAN-CNT binder establishes chemical anchoring between polyacrylonitrile and FeS₂, enhancing electronic conductivity and mitigating volume expansion. Specifically, the binder boosts the initial discharge capacity by 35% while alleviating the stress-induced pulverization associated with volume changes. Meanwhile, the PVDF-conductive carbon-coated separator enables effective polysulfide trapping via dipole–dipole interactions between PVDF’s polar C-F groups and Li₂S_x species while maintaining unobstructed ion transport with an ionic conductivity of 1.23 × 10⁻³ S cm⁻¹, achieving a Coulombic efficiency of 99.2%. The electrochemical results demonstrate that the dual-modified battery delivers a high initial discharge capacity of 650 mAh g⁻¹ at 0.5 C, with a capacity retention rate of 61.5% after 120 cycles, significantly outperforming the control group’s 47.5% retention rate. Scanning electron microscopy and electrochemical impedance spectroscopy confirm that this synergistic design suppresses polysulfide migration and enhances interfacial stability, reducing the charge transfer resistance from 26 Ω to 11 Ω. By integrating polymer-based functional materials, this work presents a scalable and cost-effective approach for developing high-energy-density Li-FeS₂ batteries, providing a practical pathway to overcome key challenges in their commercialization. Full article

The inchworm piezoelectric motor, with the advantages of long stroke and high resolution, is ideally suited for precise positioning in wafer-level electron beam inspection systems. However, the large number of piezoelectric actuators and the complex excitation signal sequences significantly increase the complexity of system assembly and temporal control. A flexure-based actuation stator structure, along with simplified excitation signal sequences of a high-precision inchworm piezoelectric motor, is proposed. The alternating actuation of upper/lower clamping mechanisms and the driving mechanism fundamentally mitigates backstep effects while generating stepping linear displacement. The inchworm piezoelectric motor achieves precision linear motion operation using only two piezoelectric actuators. The actuation stator is analyzed via the compliance matrix method to derive its output compliance, input stiffness, and displacement amplification ratio. Furthermore, a kinematic model and natural frequency expression incorporating the pseudo-rigid-body method and Lagrange’s equations are established. The actuation stator and inchworm piezoelectric motor are analyzed through both simulations and experiments. The results show that the maximum step displacement of the motor is 16.3 μm, and the maximum speed is 9.78 mm/s, at a 600 Hz operation frequency with a combined alternating piezoelectric voltage of 135 V and 65 V. These findings validate the designed piezoelectric motor’s superior motion resolution, operational stability, and acceptable load capacity. Full article

Batteries are ubiquitous, with their presence ranging from electric vehicles to portable electronics. Research focused on increasing average voltage, improving stability, and extending cycle longevity of batteries is pivotal for the advancement of battery technology. These advancements can be accelerated through research into battery chemistries. The traditional approach, which examines each material combination individually, poses significant challenges in terms of resources and financial investment. Physics-based simulations, while detailed, are both time-consuming and resource-intensive. Researchers aim to mitigate these concerns by employing Machine Learning (ML) techniques. In this study, we propose a Transformer-based deep learning model for predicting the average voltage of battery electrodes. Transformers, known for their ability to capture complex dependencies and relationships, are adapted here for tabular data and regression tasks. The model was trained on data from the Materials Project database. The results demonstrated strong predictive performance, with lower mean absolute error (MAE) and mean squared error (MSE), and higher R² values, indicating high accuracy in voltage prediction. Additionally, we conducted detailed per-ion performance analysis across ten working ions and apply sample-wise loss weighting to address data imbalance, significantly improving accuracy on rare-ion systems (e.g., Rb and Y) while preserving overall performance. Furthermore, we performed SHAP-based feature attribution to interpret model predictions, revealing that gravimetric energy and capacity dominate prediction influence, with architecture-specific differences in learned feature importance. This work highlights the potential of Transformer architectures in accelerating the discovery of advanced materials for sustainable energy storage. Full article

Alzheimer’s disease (AD) is a significant global health challenge, further exacerbated by the anticipated increase in prevalence in the coming years. The accumulation of β-amyloid peptide plays a critical role in the onset of AD; however, emerging evidence suggests that soluble oligomers of β-amyloid may primarily drive the neuronal impairments associated with this condition. Additionally, neurodegenerative diseases like AD are linked to oxidative stress and reduced antioxidant capacity in the brain. Natural products, particularly polysaccharides extracted from mushrooms, have garnered interest due to their neuroprotective properties and the potential to enhance the value of natural sources in addressing human diseases. This study examines the antioxidant and neuroprotective properties of polysaccharides derived from Cyttaria espinosae Lloyd (CePs), a relatively underexplored fungus native to Chile. Using Fourier Transform Infrared Spectroscopy (FT-IR) and Gas Chromatography-Mass Spectrometry (GC-MS), we characterized CePs. We assessed their antioxidant capacity using DPPH and ABTS assays, yielding maximum inhibition rates of 32.14% and 19.10%, respectively, at a concentration of 10 mg mL⁻¹. CePs showed no toxicity in zebrafish embryos and maintained high cell viability in PC-12 cells exposed to amyloid β peptide (Aβ). Our findings suggest that CePs exhibit significant antioxidant and neuroprotective properties against Aβ peptide toxicity while remaining non-toxic to zebrafish embryos. This underscores the potential of the polysaccharides from this mushroom to serve as functional foods that mitigate oxidative stress and warrant further investigation into their mechanisms in the context of the physiopathology of Alzheimer’s disease. Full article

Green and digital transitions represent a dual strategic objective for the European Union (EU), requiring behavioral changes from citizens, markets, and state institutions. To support these transformations, the EU has developed an extensive policy framework that is backed by significant financial instruments. However, the existing research suggests that these transitions may exacerbate both spatial and socioeconomic inequalities, depending on country-specific conditions and institutional capacities. This paper investigates how environmental and technological contexts, alongside EU-transition-related policies, influence regional and income inequalities within the selected EU countries. Using panel data covering the period 2007–2020 and employing a Generalized Least Squares (GLS) estimator, the present study reveals the complex relationship between structural conditions, policy designs, and inequality outcomes. The results show that smart and green policies tend to mitigate spatial inequalities, though they are found to be less effective in addressing income inequalities. By contrast, the contextual dynamics of the twin transition, such as skill intensity, digital adoption, and emissions, exhibit mixed effects, sometimes reinforcing inequality. The findings underline the urgency of designing inclusive EU policies that combine green and smart transition measures while accounting for country- and region-specific challenges. Such an integrated approach is essential for ensuring that the twin transition strengthens social cohesion in Europe, rather than undermining it. Full article

The use of commercial off-the-shelf smart devices in digital signage for sentient spaces is emerging as a promising solution within smart city environments. In such scenarios, these devices are often required to execute resource-intensive applications despite limited local computational capacity. Although cloud and fog infrastructures have been proposed to offload demanding workloads, they are not always suitable due to privacy and security concerns. As a result, executing sentient space applications directly on smart devices may exceed their processing capabilities. To address this limitation, state-of-the-art solutions have introduced load balancing techniques for smart devices. However, these approaches typically rely on centralized coordination or require extensive system profiling, making them unsuitable for sentient spaces, where device availability is intermittent and cooperative behavior must remain lightweight, adaptive, and decentralized. This paper proposes a distributed load balancing strategy tailored for sentient spaces that operate without reliance on cloud or fog infrastructures. The approach is based on reactive cooperation among neighboring devices and employs a local feasibility-check mechanism to determine when to offload computation and which neighboring devices are available to process it. The proposed solution is evaluated in a laboratory setting that emulates a real-world sentient space scenario within a commercial mall. Experimental results show the effectiveness of the proposed approach in maintaining real-time performance and mitigating local computational overload without relying on centralized infrastructure. Even under dynamic operating conditions, the system achieves a load balancing execution time of 5 ms on an ARM Cortex-A53 processor integrated in an AMD Zynq UltraScale+ platform. Full article

Introduction: People who exercise outdoors in urban environments may inhale increased amounts of polluted air due to temporary respiratory changes induced by physical activity. The objective of this scoping review was to map the physiological, morphological, and/or functional responses of the respiratory system to air pollution in healthy adults who exercise outdoors in urban environments. Methods: This review was conducted following the guidelines of the Preferred Reporting Items Extension for Scoping Reviews (PRISMA-ScR). A comprehensive search of Medline (PubMed), Redalyc, Scielo, and Web of Science was conducted to identify clinical trials, quasi-experimental studies, and cross-sectional studies published in the last 10 years in English. Studies with healthy adult participants engaged in outdoor physical activity in urban environments were included. Texts with participants with preexisting respiratory diseases, elite athletes, animal models, and computer simulations were excluded. Results: The most frequently reported air pollutants were PM_2.5, PM₁₀, and ozone (O₃); the most common forms of exercise were walking, running, and cycling. Exposure to air pollutants during physical activity was associated with reductions in forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV₁), as well as increases in the fraction of exhaled nitric oxide (FeNO) and proinflammatory biomarkers. Conclusion: The findings indicated that there are modifications in lung function in those who exercise outdoors. However, the association between these respiratory responses and air pollution was not statistically significant in most cases. Some authors suggested that the health benefits of physical activity could mitigate the harmful effects of air pollution. Full article

This study applies the Integrated Modification Methodology (IMM) to assess how morphology-driven, nature-based solutions reduce urban heat island (UHI) effects and flooding in Rio de Janeiro’s Cidade Nova. Multi-scale GIS diagnostics identify green continuity and vertical permeability as critical weaknesses. Simulations (Ladybug/Dragonfly) and hydrological modelling (rational method) quantify the intervention’s impact, including greening, material retrofits, and drainage upgrades. Results show a 38% increase in albedo, a 13% reduction in volumetric heat capacity, and a 30% drop in thermal conductivity. These changes reduce the peak UHI by 0.2 °C hourly, narrowing the urban–rural temperature gap to 3.5 °C (summer) and 4.3 °C (winter). Hydrologically, impervious cover decreases from 22% to 15%, permeable surfaces rise from 9% to 29%, and peak runoff volume drops by 27% (16,062 to 11,753 m³/h), mitigating flood risks. Green space expands from 7.8% to 21%, improving connectivity by 50% and improving park access. These findings demonstrate that IMM-guided interventions effectively enhance thermal and hydrological resilience in dense tropical cities, aligning with climate adaptation and the Sustainable Development Goals. Full article

Although wind-assisted ship propulsion (WASP) is an effective technique for reducing the emissions of merchant ships, the best fuel type for complementing WASP remains an open question. This study presents a new original life cycle assessment method for ship fuels that uses a validated ship performance prediction model and actual operation conditions for a WASP ship. As a case study, the method is used to evaluate the fuel consumption and environmental impact of different fuels for a WASP ship operating in the Baltic Sea. Using a novel in-house-developed platform for predicting ship performance under actual operation conditions using hindcast data, the engine and fuel tank were sized while accounting for fluctuating weather conditions over a year. The results showed significant variation in the required fuel tank capacity across fuel types, with liquid hydrogen requiring the largest volume, followed by LNG and ammonia. Additionally, a well-to-wake life cycle assessment revealed that dual-fuel engines using green ammonia and hydrogen exhibit the lowest global warming potential (GWP), while grey ammonia and blue hydrogen have substantially higher GWP levels. Notably, NOx, SOx, and particulate matter emissions were consistently lower for dual-fuel and liquid natural gas scenarios than for single-fuel marine diesel oil engines. These results underscore the importance of selecting both an appropriate fuel type and production method to optimize environmental performance. This study advocates for transitioning to greener fuel options derived from sustainable pathways for WASP ships to mitigate the environmental impact of maritime operations and support global climate change efforts. Full article

Water scarcity and greenhouse gas (GHG) emissions pose significant challenges to sustainable wheat production in tropical regions such as the Brazilian Cerrado. This study evaluated the effects of different soil water depletion levels, denoted as f (20%, 40%, 60%, and 80% of available water capacity—AWC), on no-tillage winter wheat irrigated after rainfed soybean cultivation. Grain yield decreased significantly at depletion levels ≥ 60%, with the highest yields observed at f = 20% (6933 kg ha⁻¹) and f = 40% (6814 kg ha⁻¹). Water use efficiency (WUE) ranged from 12.4 to 14.0 kg ha⁻¹ mm⁻¹, with no significant differences among treatments. Nitrous oxide (N₂O) emissions peaked at f = 60% (4.55 kg ha⁻¹), resulting in the highest average global warming potential (GWP = 1.185.78 kg CO₂ eq ha⁻¹) and greenhouse gas intensity (GHGI = 192.66 kg CO₂ eq Mg⁻¹ grain). Methane (CH₄) acted as a net sink across all irrigation levels. Soil enzymatic activities (β-glucosidase and arylsulfatase) were not significantly affected by irrigation management. Overall, irrigation scheduling based on f = 40% soil water depletion provided the best balance between productivity and environmental sustainability, representing a climate-smart and resource-efficient strategy for wheat production in tropical agroecosystems. These findings provide promising insights for tropical agriculture by showing that sustainable irrigation can balance productivity and climate mitigation in the Cerrado. Maintaining soil water depletion below 60% significantly reduces N₂O emissions and environmental impact, emphasizing the importance of conservation practices. Additionally, preserving soil biological quality supports the long-term viability of these practices and offers valuable guidance for policies promoting efficient irrigation in climate-vulnerable regions. Full article