Search Results (78)

Within transport systems, train stations cover a primary role as places where access to different modes of transport must be realised effectively, providing a valuable opportunity to make rail services, public transport, and soft mobility more attractive. This research seeks to shed some light on how Italian travellers perceive the quality of train stations, and to identify priorities for action in relation to design, building, and operation that might help revitalise their attractiveness. The methodology involved designing a questionnaire capable of identifying significant correlations between attitudinal and behavioural variables via an exploratory factor analysis, reaching around 400 respondents through a snowball sampling plan. The factor “sociality and daily life” showed the importance that people place on the vitality of urban places. Travellers also consider other factors, like the overall service quality, the cleanliness and safety of a train station, the walkability of connections within the node, and the possibility of reaching the station by bicycle. The profiling of respondents using a cluster analysis based on latent factors points to specific policies, showing how actions targeting stations can have positive effects on the use of rail transport and on the propensity towards intermodality and sustainable mobility. A safe, “living” place can mitigate the risk of social degradation, while promoting walking and cycling. Full article

This study presents a novel multi-material additive manufacturing (MMAM) strategy by combining virgin polylactic acid (vPLA) with recycled polylactic acid (rPLA) in a layered configuration to improve both performance and sustainability. Specimens were produced using fused deposition modelling (FDM) with various vPLA: rPLA ratios (33:67, 50:50, and 67:33) and two distinct layering approaches: one with vPLA forming the external layers and rPLA as the core, and a second using the reversed arrangement. Mechanical testing revealed that when vPLA is used as the exterior, printed components exhibit tensile strength and elongation improvements of 10–25% over conventional single-material prints, while the tensile modulus is largely influenced by the distribution of the two materials. Thermal analysis shows that both vPLA and rPLA begin to degrade at approximately 330 °C; however, rPLA demonstrates a higher end-of-degradation temperature (461.7 °C) and increased residue at elevated temperatures, suggesting improved thermal stability due to enhanced crystallinity. Full-field strain mapping, corroborated by digital microscopy (DM) and scanning electron microscopy (SEM), revealed that vPLA-rich regions display more uniform interlayer adhesion with minimal voids or microcracks, whereas rPLA-dominated areas exhibit greater porosity and a higher propensity for brittle failure. These findings highlight the role of optimal material placement in mitigating the inherent deficiencies of recycled polymers. The integrated approach of combining microstructural assessments with full-field strain mapping provides a comprehensive view of interlayer bonding and underlying failure mechanisms. Statistical analysis using analysis of variance (ANOVA) confirmed that both layer placement and material ratio have a significant influence on performance, with high effect sizes highlighting the sensitivity of mechanical properties to these parameters. In addition to demonstrating improvements in mechanical and thermal properties, this work addresses a significant gap in the literature by evaluating the combined effect of vPLA and rPLA in a multi-material configuration. The results emphasise that strategic material distribution can effectively counteract some of the limitations typically associated with recycled polymers, while also contributing to reduced dependence on virgin materials. These outcomes support broader sustainability objectives by enhancing energy efficiency and promoting a circular economy within additive manufacturing (AM). Overall, the study establishes a robust foundation for industrial-scale implementations, paving the way for future innovations in eco-efficient FDM processes. Full article

Reduced gravity may impair motion perception accuracy, especially in the absence of visual cues, which could degrade astronauts’ driving performance. The lack of prior research makes simulating realistic motion perception for lunar rover driving particularly challenging. We created a simulation system to quantitatively simulate the motion characteristics of a lunar rover at different gravity levels, and a software program based on the spatial orientation observer model was developed for the comparison of motion perception differences between Earth’s and lunar gravity. In comparison to Earth’s gravity, the lunar rover in lunar gravity demonstrates the following differences: (1) The rover exhibits a greater propensity to float and slip, and slower acceleration and deceleration. (2) Dynamic tilt perception may be more complicated with single vestibular information, while static tilt perception is greatly reduced; the introduction of visual information can notably improve the perception accuracy. Simulation results demonstrate that motion characteristics and perception of lunar rover driving exhibit a more variable trend at different gravity levels. An intuitive mathematical formulation was proposed to explain the single vestibular results. Our findings provide a basis for further optimizing lunar rover driving motion simulation strategies. Full article

Bovine mastitis is a condition typically induced by various pathogens, with Escherichia coli (E. coli) being a common causative agent known for its propensity to cause persistent infections. In experimental models of bovine mastitis, lipopolysaccharide (LPS), a key component of the E. coli cell wall, is frequently employed as an inducer. The extracellular matrix (ECM) is regulated by MMPs, TIMPs, and the uPA system. They collectively participate in ECM degradation and remodeling and have been identified as promising targets for mastitis treatment. However, investigations into the precise mechanisms underlying E. coli and LPS-induced mastitis, as well as the relationship between bovine mastitis and the MAPK signaling pathway, remain limited. In this study, bovine mammary epithelial cells (BMECs) were treated in vitro with 10⁶ CFU/mL heat-inactivated E. coli, 7.5 µg/mL LPS, or a combination of both. The treatments resulted in varying degrees of activation of the MAPK signaling pathway, specifically ERK1/2, JNK, and P38. BMECs were exposed to MAPK inhibitors (the JNK inhibitor SP600125, the ERK inhibitor PD98059, and the P38 inhibitor SB203580) after treatments with heat-inactivated E. coli (10⁶ CFU/mL), LPS (7.5 µg/mL), or a combination of the two for 6, 12, 24, and 48 h. The mRNA and protein levels of MMP-1, MMP-2, MMP-3, MMP-9, MMP-13, TIMP-1, TIMP-2, uPA, uPAR, and PAI-1 were assessed using RT-qPCR and Western blot analysis. The findings indicated that heat-inactivated E. coli and LPS stimulated the expression of MAPK mRNAs (ERK1/2, P38, and JNK) in BMECs, along with corresponding increases in the phosphorylated proteins. Furthermore, MAPK inhibitors substantially upregulated the expression of TIMP-1, TIMP-2, and PAI-1. However, no significant changes were observed in the mRNA and protein levels of MMP-1, MMP-2, MMP-3, MMP-9, MMP-13, uPA, or uPAR. In conclusion, heat-inactivated E. coli and LPS can activate the MAPK signaling pathway in BMECs. Inhibiting this signaling pathway can modulate the expression of TIMP-1, TIMP -2, and PAI-1 at both mRNA and protein levels. Full article

Concerns over pharmaceutical contaminants are increasing due to their high biological activity and ubiquity, with wastewater being the main source. Ibuprofen is extensively used worldwide and commonly detected in freshwaters due to its low degradability during wastewater treatment. Daphnia magna is the most-used model taxon for toxicity testing of ibuprofen, but this crustacean is known to be less sensitive to some contaminants than several freshwater insect groups. Our study assessed the toxicity of ibuprofen (nominal concentration range 2.0–2147.5 µg/L) to a native New Zealand mayfly, Deleatidium spp., in a 7-day static renewal experiment, with the neonicotinoid imidacloprid (1.4 µg/L) as a reference toxicant. Test concentrations of ibuprofen included three field-realistic and four higher concentrations that might occur in severely polluted streams. Mayfly responses indicated some negative trends (decreased survival and moulting propensity, increased impairment and immobility), but all patterns were non-significant. The imidacloprid control also had no significant impacts but tended to increase mayfly impairment. Overall, Deleatidium nymphs were largely unaffected by the entire range of experimental ibuprofen concentrations, suggesting that ibuprofen may be a relatively benign stressor for these organisms, although longer-term exposure experiments are needed to confirm if they demonstrate susceptibility to chronic exposure. Full article

Multi-UAV path planning presents a critical challenge in Unmanned Aerial Vehicle (UAV) applications, particularly in environments with various obstacles and restrictions. These conditions transform multi-UAV path planning into a complex optimization problem with multiple constraints, significantly reducing the number of feasible solutions and complicating the generation of optimal flight trajectories. Although the slime mold algorithm (SMA) has proven effective in optimization missions, it still suffers from limitations such as inadequate exploration capacity, premature convergence, and a propensity to become stuck in local optima. These drawbacks degrade its performance in intricate multi-UAV scenarios. This study proposes a self-adaptive improved slime mold algorithm called AI-SMA to address these issues. Firstly, AI-SMA incorporates a novel search mechanism to balance exploration and exploitation by integrating ranking-based differential evolution (rank-DE). Then, a self-adaptive switch operator is introduced to increase population diversity in later iterations and avoid premature convergence. Finally, a self-adaptive perturbation strategy is implemented to provide an effective escape mechanism, facilitating faster convergence. Extensive experiments were conducted on the CEC 2017 benchmark test suite and multi-UAV path-planning scenarios. The results show that AI-SMA improves the quality of optimal fitness by approximately $7.83\%$ over the original SMA while demonstrating superior robustness and effectiveness in generating collision-free trajectories. Full article

Amidst the increasingly escalating global concern regarding climate change, adopting a low-carbon approach has become crucial for charting the future developmental trajectory of urban areas. It also offers a novel angle for cities to avoid high-temperature risks. This paper estimates carbon emissions in Wuhan City from both direct and indirect aspects. Then, the ANN (artificial neural network)–CA (Cellular Automata) model is employed to establish three distinct development scenarios (Ecological Priority, Tight Growth, and Natural Growth) to predict future urban expansion. Additionally, the WRF (Weather Research and Forecasting Model)—UCM (Urban Canopy Model) model is used to investigate the thermal environmental impacts of varying urban development scenarios. This study uses a low-carbon perspective to explore how cities can develop scientifically sound urban strategies to meet climate change challenges and achieve sustainable development goals. The conclusions are as follows: (1) The net carbon emission for Wuhan in 2022 is estimated to be approximately 20.8353 million tonnes. Should the city maintain an average annual emission reduction rate of 10%, the carbon sink capacity of Wuhan would need to be enhanced by 382,200 tonnes by 2060. (2) In the absence of anthropogenic influence, there is a propensity for the urban construction zone of Wuhan to expand primarily towards the southeast and western sectors. (3) The Ecological Priority (EP) and Tight Growth (TG) scenarios are effective in alleviating the urban thermal environment, achieving a reduction of 0.88% and 2.48%, respectively, in the urban heat island index during afternoon hours. In contrast, the Natural Growth (NG) scenario results in a degradation of the urban thermal environment, with a significant increase of over 4% in the urban heat island index during the morning and evening periods. (4) An overabundance of urban green spaces and water bodies could exacerbate the urban heat island effect during the early morning and at night. The findings of this study enhance the comprehension of the climatic implications associated with various urban development paradigms and are instrumental in delineating future trajectories for low-carbon sustainable urban development models. Full article

The Altai Mountains region, characterized by its unique biodiversity and significant ecological value, is increasingly under pressure from anthropogenic activities and climate change. This study investigates the spatial and temporal dynamics of forest and grassland ecosystems in the Altai Mountains National Park Candidate Area from 2000 to 2020, and proposes a comprehensive framework for the conservation and management of national parks. Through a detailed analysis of land cover changes, we observed significant forest expansion of 13.65% and grassland degradation of 11.69%. Rapid forest expansion occurred before 2010, followed by accelerated grassland degradation after that, with 2010 identified as the critical turning point. Our analysis highlights the role of key drivers, such as soil type, elevation, cropland expansion, and human activities, in shaping these ecosystems. Using Geodetector and propensity score matching methods, we evaluated the effectiveness of existing protected areas in mitigating forest and grassland loss. While protected areas effectively contributed to forest restoration, they were less successful in preventing grassland decline, underscoring the need for integrated management approaches. The findings from this study provide critical insights into ecosystem dynamics and conservation effectiveness, offering valuable guidance for the establishment of national-park-type protected areas and broader regional conservation efforts. Full article

The bending stiffness of beams represents a pivotal parameter influencing both the dimensions of the elements during their design and their subsequent utilisation. It is evident that excessive deflections can cause discomfort to users and contribute to further structural degradation. The objective of this study was to enhance the bending stiffness of timber beams by bonding a composite sheet to their external surfaces. A carbon sheet exhibiting an ultra-high modulus of elasticity and low elongation at rupture was employed. Two variables of analysis can be distinguished including whether the reinforcement was applied or not and the number of reinforcement layers. The beams, with nominal dimensions of 80 × 80 × 1600 mm, were subjected to a four-point bending test in order to ascertain their mechanical properties. In total, 15 beams were tested (5 unreinforced and 10 reinforced). The reinforcement had no appreciable impact on the increase in flexural load capacity, with the maximum average increase recorded at 9%. Nevertheless, an increase in stiffness of 34% was observed. Additionally, significant increases were observed in ductility up to 248%. However, the ductile behaviour of the beam occurred after the rupture of the reinforcement. In all instances, the failure was attributed to the fracturing of the wooden components or the UHM CFRP (ultra-high-modulus-carbon-fibre-reinforced polymer) sheet. The numerical analysis proved to be a valuable tool for predicting the stiffness of the wood–composite system, with a relatively low error margin of a few percentage points. The modified approach, based on the equivalent cross-section method, permits the determination of a bilinear load deflection relationship for reinforced beams. The aforementioned curve is indicative of the actual behaviour. Given the propensity for the sudden rupture of reinforcement, the described method of reinforcement is recommended for beams subjected to lower levels of stress. Full article

Therapeutic antibodies such as monoclonal antibodies (mAbs), bispecific and multispecific antibodies are pivotal in therapeutic protein development and have transformed disease treatments across various therapeutic areas. The integrity of therapeutic antibodies, however, is compromised by sequence liabilities, notably deamidation, where asparagine (N) and glutamine (Q) residues undergo chemical degradations. Deamidation negatively impacts the efficacy, stability, and safety of diverse classes of antibodies, thus necessitating the critical need for the early and accurate identification of vulnerable sites. In this article, a comprehensive antibody deamidation-specific dataset (n = 2285) of varied modalities was created by using high-throughput automated peptide mapping followed by supervised machine learning to predict the deamidation propensities, as well as the extents, throughout the entire antibody sequences. We propose a novel chimeric deep learning model, integrating protein language model (pLM)-derived embeddings with local sequence information for enhanced deamidation predictions. Remarkably, this model requires only sequence inputs, eliminating the need for laborious feature engineering. Our approach demonstrates state-of-the-art performance, offering a streamlined workflow for high-throughput automated peptide mapping and deamidation prediction, with the potential of broader applicability to other antibody sequence liabilities. Full article

The development of an ideal membrane for membrane distillation (MD) is of the utmost importance. Enhancing the efficiency of MD by adding nanoparticles to or onto a membrane’s surface has drawn considerable attention from the scientific community. It is crucial to thoroughly examine state-of-the-art nanomaterials-enabled MD membranes with desirable properties, as they greatly enhance the efficiency and reliability of the MD process. This, in turn, opens up opportunities for achieving a sustainable water–energy–environment nexus. By introducing carbon-based nanomaterials into the membrane’s structure, the membrane gains excellent separation abilities, resistance to various feed waters, and a longer lifespan. Additionally, the use of carbon-based nanomaterials in MD has led to improved membrane performance characteristics such as increased permeability and a reduced fouling propensity. These nanomaterials have also enabled novel membrane capabilities like in situ foulant degradation and localized heat generation. Therefore, this review offers an overview of how the utilization of different carbon-based nanomaterials in membrane synthesis impacts the membrane characteristics, particularly the liquid entry pressure (LEP), hydrophobicity, porosity, and membrane permeability, as well as reduced fouling, thereby advancing the MD technology for water treatment processes. Furthermore, this review also discusses the development, challenges, and research opportunities that arise from these findings. Full article

Background: Sarcopenia, characterized by degenerative skeletal muscle loss, is increasingly linked to poor surgical outcomes. Glutamine, an immune-modulating formula, may stimulate muscle protein synthesis and inhibit degradation. We used the psoas major muscle area (PMMA) at the third lumbar vertebra, normalized for height (PMMA index), as a skeletal muscle indicator. This study investigates whether perioperative glutamine supplementation mitigates psoas muscle atrophy. Methods: We enrolled gastric adenocarcinoma (GA) patients undergoing gastrectomy. Computed tomography assessed the psoas muscle short axis. Muscle atrophy was estimated by changes between preoperative and three-month post-gastrectomy scans. Perioperative glutamine supplementation (PGS) comprised five-day parenteral plus one-month oral use. Propensity score matching minimized potential bias. A linear regression model predicted the association. Results: Of 516 patients analyzed (2016–2019), 100 (19.4%) received PGS. After propensity score matching, each group contained 97 cases. The PGS group showed a significantly higher median PMMA index change than the non-PGS group (0.3 vs. −0.3 cm²/m², p = 0.004). Multivariate analysis revealed that PGS was significantly associated with increased PMMA index (coefficient = 0.60; 95% CI: 0.19–1.01; p = 0.005). Conclusions: PGS may help restore psoas muscle atrophy in GA patients undergoing gastrectomy. The underlying mechanisms likely relate to glutamine’s role in protein metabolism and immune function. Further studies are needed to elucidate these mechanisms fully. Full article

The coexistence of traditional knowledge and environmental preservation presents a critical nexus in advancing sustainable development efforts, particularly concerning the conservation of indigenous medicinal plants. These plants play a dual role: they are essential components of traditional healing practices and are integral to economic stability, food security, and nutrition in communities worldwide. However, the rapid depletion of biodiversity and ecosystem degradation threaten the availability and sustainability of these vital resources. Despite their cultural and economic importance, there is a noticeable gap in the research addressing the conservation and sustainable use of indigenous medicinal plants, particularly focusing on the preservation of traditional knowledge systems. The existing literature often lacks comprehensive studies that document traditional knowledge practices related to medicinal plant conservation. Additionally, there is limited understanding of how the mismanagement of medicinal plant resources impacts the livelihoods of rural smallholder farmers who heavily rely on these plants for economic gains and food security. Hence, this study sought to explore and investigate the harmonious strategies that integrate traditional knowledge systems with modern conservation practices to safeguard indigenous medicinal plants on economic well-being in the Amatole District Municipality of the Eastern Cape. The study was conducted in 2023, and a structured questionnaire was used to capture the realities and experiences of prominent stakeholders (smallholder medicinal plant farmers). A multi-stratified sampling technique was used to draw up an appropriate sample of 150 smallholder farmers. Descriptive statistics and propensity-score matching were used for analysis. The study results indicated that the women farmers who are 44 years of average age and have 10 years of average schooling duration participate more in the production of indigenous medicinal plants. The average farm size per household is 1 ha, and it is reliant on an average of five members per household. The participation of women with indigenous medicinal plants underscores the significant role of women in traditional knowledge systems and sustainable agricultural practices, contributing to household income and community resilience. Additionally, the findings indicated that smallholder farmers are only aware of keeping indigenous medicinal plants by producing them in protected areas and on-farm conservation; other measures appear challenging to them. The study results reveal that knowledge of seed propagation, lack of knowledge of the implications of endangerment, the removal of forests with the motive of building houses, and, lastly, financial support were the constraints faced by smallholder farmers. Empirical results on the conservation and sustainable use of indigenous medicinal plants revealed that farmers are generating income to sustain the household as well as enhancing food and nutrition security. Based on the study results, it is recommended that government entities and policymakers are urged to prioritize supporting traditional knowledge, implement on-farm conservation, and foster sustainable agricultural practices to ensure biodiversity conservation, cultural preservation, and sustainable livelihoods. Enhancing targeted support for smallholder farmers, including access to land, agricultural services, and financial aid, alongside market development, ensures equitable benefits and sustainable livelihoods. Educational campaigns should raise awareness about indigenous medicinal plants’ ecological and economic importance, integrating traditional knowledge into formal education. Full article

Heavy metals (HMs) in aquatic environments are characterized by high toxicity, a propensity for bioaccumulation, and non-degradability, and pose significant risks to biological communities. Previous studies of HMs in lakes have shown that the physical and chemical characteristics of the lake water may control both the migration of HMs in the sediments and the concentration of heavy metals in the lake water. In fact, the change in aquatic environments changes the heavy metal fraction in the sediment, which controls the release of HMs. In this paper, we investigated the effects of the pH, temperature, and salinity levels of overlying water on the chemical fraction of Cu and Zn in Wuliangsuhai Lake surface sediments. The results show that lower water pH and higher water salinity and temperature could increase Cu and Zn release from the sediment. An increase in pH led to changes in the speciation of solid fractions of Zn, namely increases in the residual fraction and decreases in the organic matter and sulfide, whereas acid-extractable and Fe-Mn oxide fractions remained largely the same. Increases in temperature and salinity led to opposite changes in the speciation of solid fractions, namely decreases in the residual fraction and increases in the organic matter and sulfide and Fe-Mn oxide fractions, whereas acid-extractable fractions remained largely the same. The effect of pH, temperature, and salinity on Cu fractions in the solids was much smaller. According to the ratio of the secondary phase to the primary phase (RSP), acidic, high-temperature, and high-salt conditions increase the release risks of Zn. Changes in water temperature have the greatest influence on the risk of Zn and Cu release from sediments, followed by the influence of salinity changes. Full article

Due to their robust migration capabilities, slow degradation, and propensity for adsorbing environmental pollutants, micro(nano)plastics (MNPs) are pervasive across diverse ecosystems. They infiltrate various organisms within different food chains through multiple pathways including inhalation and dermal contact, and pose a significant environmental challenge in the 21st century. Research indicates that MNPs pose health threats to a broad range of organisms, including humans. Currently, extensive detection data and studies using experimental animals and in vitro cell culture indicate that MNPs can trigger various forms of programmed cell death (PCD) and can induce various diseases. This review provides a comprehensive and systematic analysis of different MNP-induced PCD processes, including pyroptosis, ferroptosis, autophagy, necroptosis, and apoptosis, based on recent research findings and focuses on elucidating the links between PCD and diseases. Additionally, targeted therapeutic interventions for these diseases are described. This review provides original insights into the opportunities and challenges posed by current research findings. This review evaluates ways to mitigate various diseases resulting from cell death patterns. Moreover, this paper enhances the understanding of the biohazards associated with MNPs by providing a systematic reference for subsequent toxicological research and health risk mitigation efforts. Full article