Search Results (65,628)

Algae communities as primary producers are essential elements of aquatic ecosystems and contribute significantly to oxygen production, carbon dioxide fixation, and nutrient transport processes in water bodies. The use of algae-based carbon capture and storage technologies does not produce harmful by-products that require disposal, and the resulting algal biomass can be valuable across various industrial sectors. In this study, model experiments were conducted to develop sequential absorption–microalgae hybrid CO₂-capture methods. To facilitate CO₂ capture from flue gases, wood biomass ash (WBA), an agricultural by-product, was utilized for its alkaline properties, while the flue gas scrubbing medium was regenerated by algae that restored alkalinity during their growth. In our experiments, one of our goals was to determine the optimal conditions for achieving maximum algal biomass growth in the shortest possible time. The suitability of WBA for flue gas cleaning was tested via simulation of CO₂ introduction. Moreover, a method was developed to determine the dissolved inorganic carbon content with the use of an OxiTop device monitoring the changes in pressure. The applied device was a closed, static, and pressure-based respirometer originally designed to determine the biological activity of microorganisms in both solid and liquid samples. In addition, the effects of CO₂-enriched WBA extract on algae cultivation were also analyzed, confirming that it imposed no growth inhibition and identifying the concentration (10% WBA) that optimally promoted algal growth. The optimal initial algal concentration and nutrient conditions for maximum growth were also determined. Full article

Aging and apolipoprotein E4 (APOE4) are the two most significant risk factors for late-onset Alzheimer’s disease (LOAD). Compared to APOE3, APOE4 disrupts cholesterol homeostasis, increases cholesteryl esters (CEs), and exacerbates neuroinflammation in brain cells, including microglia. Targeting CEs and neuroinflammation could be a novel strategy to ameliorate APOE4-dependent phenotypes. Toll-like receptor 4 (TLR4) is a key macromolecule in inflammation, and its regulation is associated with the cholesterol content of lipid rafts in cell membranes. We previously demonstrated that in normal microglia expressing APOE3, inhibiting the cholesterol storage enzyme acyl-CoA:cholesterol acyltransferase 1 (ACAT1/SOAT1) reduces CEs, dampened neuroinflammation via modulating the fate of TLR4. We also showed that treating myelin debris-loaded normal microglia with ACAT inhibitor F12511 reduced cellular CEs and activated ABC transporter 1 (ABCA1) for cholesterol efflux. This study found that treating primary microglia expressing APOE4 with F12511 also reduces CEs, activates ABCA1, and dampens LPS-dependent NFκB activation. In vivo, two-week injections of nanoparticle F12511, which consists of DSPE-PEG₂₀₀₀, phosphatidylcholine, and F12511, to aged female APOE4 mice reduced TLR4 protein content and decreased proinflammatory cytokines, including IL-1β in mice brains. Overall, our work suggests nanoparticle F12511 is a novel agent to ameliorate LOAD. Full article

The traction motor realizes the mutual conversion of electrical energy and mechanical energy during the train traction and braking process and is a key component of high-speed trains. The normal operation of the motor is directly related to the safety of high-speed train operation. Changes in temperature signals can reflect faults in the traction motor. By analyzing the internal and external influencing factors of temperature signals, a multi-factor prediction model for traction motors is established based on the maximal information coefficient and improved support vector regression. In this model, highly relevant features selections are performed based on time-delayed sequences and the maximal information coefficient. Using the adaptive particle swarm algorithm to optimize the improved support vector regression algorithm can enhance its accuracy and efficiency. Furthermore, using the K-nearest neighbor algorithm for error prediction will yield more accurate results. By comparing the , , , and other evaluation metrics of different algorithms under various working conditions, the results show that the prediction method proposed in this paper performs well across different working conditions. This method demonstrates greater adaptability to varying conditions and is more suitable for applications involving high-speed trains. Full article

Hydraulic functionality is crucial for tree productivity and stress tolerance. According to the theory of the fast–slow economics spectrum, the adaptive strategies of different tree species diverge along a spectrum defined by coordination and trade-offs of a suite of functional traits. The fast- and slow-growing species are expected to differ in hydraulic efficiency and safety; however, there is still a lack of investigation on the mechanistic association between tree growth rate and tree hydraulic functionality. Here, in a common garden condition, we measured radial growth rate and hydraulic traits in a fast-growing (Populus alba L. × P. berolinensis Dippel) and a slow-growing tree species (Acer truncatum Bunge), which are both important tree species for afforestation in northern China. In line with the contrasts in radial growth rate and wood anatomical traits at both the tissue and pit levels between the two species, stem hydraulic conductivity of the Populus species was significantly higher than that of the Acer species, but the resistance to drought-induced xylem cavitation was the opposite. A trade-off between hydraulic efficiency and safety was observed across the sampled trees of the two species. Higher water-transport efficiency supports the greater leaf net photosynthetic carbon assimilation capacity of the Populus species and hence facilitates fast growth, while the conservative hydraulic traits of the Acer species result in a slower growth rate but enhanced drought tolerance. Full article

Microplastics (MPs) are widespread environmental pollutants that have drawn significant attention due to their possible health risks to humans and animals, as well as their extensive presence in ecosystems. Recent growing evidence highlights a remarkable relationship between MPs and extracellular vesicles (EVs), nanoscale particles involved in intercellular communication. The purpose of this review was to investigate how the relationships between MPs and EVs can affect cellular functions and how this interaction could impact environmental conditions leading to broader ecological risks. The interaction patterns and bioactivity of both MPs and EVs are strongly influenced by biophysical characteristics such as hydrophobicity, surface charge, and particle size, which have received particular attention from the scientific community. Recent studies indicate that MPs affect EV distribution and their capacity to function appropriately in biological systems. Additionally, MPs can modify the molecular cargo of EVs, which may result in alterations of cell signaling pathways. Understanding the interactions between MPs and EVs could provide important opportunities to comprehend their potential effects on human health and environmental systems, especially when it comes to cancer development, endocrine, metabolic, and inflammatory disorders, and ecological disruptions. This review emphasizes the necessity of multidisciplinary research to clarify the molecular and biophysical mechanisms regulating the interaction between MPs and EVs. Full article

Background: Cardiovascular deserts are areas that lack medical facilities, specialists and equipment to effectively diagnose, treat and manage cardiovascular diseases (CVDs). Romania registers the highest incidence and the highest mortality due to CVDs in Europe. Population ageing is a significant concern, as it increases the risk of CVDs and the demand for specialised care. Although almost 50% of Romanians still live in rural areas, most medical resources are concentrated in a few large cities, leaving large parts of the country underserved. Methods: This study used the Application Programming Interface (API) Matrix service from Google Maps and open data sources to identify cardiovascular (CV) deserts. Results: This research indicates that over 64% of the Romanian population resides in areas lacking CV care, having to travel more than 60 km and over 30 min to reach the nearest facility that offers specialised treatment. Moreover, 14% live in areas affected by a high degree of cardiovascular desertification. These areas are primarily located in northeastern, southern and western Romania. They experience higher mortality rates from CVDs and an ageing population, along with a shortage of general physicians and a scarcity of cardiologists. Conclusions: The identified cardiovascular deserts in this study overlap mountainous regions, the Danube Delta and remote rural areas with poor transportation infrastructure. Implementing telemedicine or mobile healthcare services, involving community healthcare workers and policy support could be solutions to expand access to specialised care in cardiovascular deserts. Full article

The receptor transporter protein 4 (RTP4) is a receptor chaperone protein that targets class A G-protein coupled receptor (GPCR)s. Recently, it has been found to play a role in peripheral inflammatory regulation, as one of the interferon-stimulated genes (ISGs). However, the detailed role of RTP4 in response to inflammatory stress in the central nervous system has not yet been fully understood. While we have previously examined the role of RTP4 in the brain, particularly in neuronal cells, this study focuses on its role in microglial cells, immunoreactive cells in the brain that are involved in inflammation. For this, we examined the changes in the RTP4 levels in the microglial cells after exposure to inflammatory stress. We found that lipopolysaccharide (LPS) treatment (0.1~1 µg/mL, 24 h) significantly upregulated the RTP4 mRNA levels in the microglial cell line, SIM-A9. Furthermore, the interferon (IFN)-β mRNA levels and extracellular levels of IFN-β were also increased by LPS treatment. This upregulation was reversed by treatment with neutralizing antibodies targeting either the interferon receptor (IFNR) or toll-like receptor 4 (TLR4), and with a TLR4 selective inhibitor, or a Janus kinase (JAK) inhibitor. On the other hand, the mitogen-activated protein kinase kinase (MEK) inhibitor, U0126, significantly enhanced the increase in RTP4 mRNA following LPS treatment, whereas the PKC inhibitor, calphostin C, had no effect. These findings suggest that in microglial cells, LPS-induced inflammatory stress activates TLR4, leading to the production of type I IFN, the activation of IFN receptor and JAK, and finally, the induction of RTP4 gene expression. Based on these results, we speculate that RTP4 functions as an inflammation-responsive molecule in the brain. However, further research is needed to fully understand its role. Full article

The electrochemical interface (EI) is the determining factor in the yield and mechanism of sustainable energy storage and conversion systems due to its intrinsic functionality as a dynamic junction with the symmetry breaking of the molecular arrangement for complex reaction fields of mass transport and heterogeneous electron transfer. At the EI, the externally applied potential stimulus drives the formation of the electrical double layer (EDL) and governs the adsorption of interfacial adsorbate species in aqueous electrolyte solutions. Water and its aqueous electrolyte systems are integral and quintessential elements in the technological innovation of various fields such as environmental sciences, electrocatalysis, photocatalysis, and biochemistry. Although deciphering the structure and orientation of water molecules at the electrode–electrolyte interface in a quantitative analysis is of utmost importance, assessing chemical phenomena at the buried EI was rather challenging due to the intricacy of selecting interface-specific methodologies. Based on the non-centrosymmetry of the interfaces’ electronic properties, sum-frequency generation (SFG) spectroscopy has been manifested to be specifically well suited for probing the EI with detailed and comprehensive characteristics of adsorbates’ chemical structures and electrochemical events. In this review, we holistically engage in a methodical and scrupulous assessment of the fundamental EDL models and navigate towards the connection of the renowned Stark effect and potential dependence of SFG spectra at heterogeneous electrode–electrolyte interfaces. We dissect the development, advantages, and available geometrical configurations of in situ SFG spectroscopy in harnessing the EI. A broad spectrum of applications in unraveling the water orientations and rationalizing the convoluted mechanism of fuel-generated electrocatalytic reactions with particular encumbrances and potential resolutions is underscored by leveraging SFG spectroscopy. Full article

Historical maps are valuable sources of geospatial data for various geography-related applications, providing insightful information about historical land use, transportation infrastructure, and settlements. While transformer-based segmentation methods have been widely applied to image segmentation tasks, they have mostly focused on satellite images. There is a growing need to explore transformer-based approaches for geospatial object extraction from historical maps, given their superior performance over traditional convolutional neural network (CNN)-based architectures. In this research, we aim to automatically extract five different road types from historical maps, using a road dataset digitized from the scanned Deutsche Heereskarte 1:200,000 Türkei (DHK 200 Turkey) maps. We applied the variants of the transformer-based SegFormer model and evaluated the effects of different encoders, batch sizes, loss functions, optimizers, and augmentation techniques on road extraction performance. Our best results, with an intersection over union (IoU) of 0.5411 and an F1 score of 0.7017, were achieved using the SegFormer-B2 model, the Adam optimizer, and the focal loss function. All SegFormer-based experiments outperformed previously reported CNN-based segmentation models on the same dataset. In general, increasing the batch size and using larger SegFormer variants (from B0 to B2) resulted in improved accuracy metrics. Additionally, the choice of augmentation techniques significantly influenced the outcomes. Our results demonstrate that SegFormer models substantially enhance true positive predictions and resulted in higher precision metric values. These findings suggest that the output weights could be directly applied to transfer learning for similar historical maps and the inference of additional DHK maps, while offering a promising architecture for future road extraction studies. Full article

Utilizing crushed spontaneous combustion coal gangue as a coarse aggregate in concrete preparation effectively reduces reliance on natural resources and mitigates environmental pollution; however, the suboptimal workability of spontaneous combustion coal gangue coarse aggregate concrete (SCG-CAC) limits its engineering applications. To address this issue, this study places SCGCAC at the center of a CFDST (Concrete-Filled Double-Skin Steel Tubular) stub column. Through finite element modeling validated for reliability, this study examines the structural mechanical response to axial loading, along with the effects of various parameters. The analysis encompasses parameters such as the strength of the core SCGCAC (f_c,i), the strength of the sandwiched concrete (f_c,o), the yield strength of the outer steel tube (f_y,o), the yield strength of the inner steel tube (f_y,i), the width-to-thickness ratio (B/t_o), the diameter-to-thickness ratio of the inner tube (D/t_i), and the diameter-to-width ratio of the outer tube (D/B). Results show that this structural configuration significantly enhances the core SCGCAC ultimate bearing capacity, and increases in D/t_i, f_c,i, f_c,o, f_y,i, and B/t_o all lead to an increase in the peak load. Particularly, when D/t_i increases from 28.57 to 80, the peak load increases by 42.72%. However, changes in f_y,o and D/B have no significant effect on the peak load. Full article

The present study focuses on advancing one of the most popular AM techniques, namely, laser powder bed fusion (LPBF) technology, which has the ability to produce complex geometry parts with minimum material waste but continues to face challenges in minimizing the surface roughness. For this purpose, a novel hybrid manufacturing technology, which applies in a single setup (in-envelope) both LPBF technology and high-speed machining, was examined in this research for the fabrication of tensile specimens with three different surface finish conditions: as-built, hybrid (in-envelope machining) and post-machining (out-of-envelope) on Inconel^® alloy 718, hereafter referred to as IN718. As the application of the IN718 alloy in service is typically specified in the precipitation-hardened condition, three different heat treatments were applied to the tensile specimens based on the most promising thermal cycles identified previously for room-temperature tensile properties by the authors. The as-built (AB) specimens had the highest average surface roughness (R_a) of 5.1 μm ± 1.6 μm, which was a significant improvement (five-fold) on the hybrid (1.0 μm ± 0.2 μm) and post-machined (0.8 μm ± 0.5 μm) surfaces. The influence of this surface roughness on the mechanical properties was studied both at ambient temperature and at 650 °C, which is close to the maximum service temperature of this alloy. Regardless of the surface conditions, the room-temperature mechanical properties of the as-fabricated IN718 specimens were within the range of properties reported for standard wrought IN718 in the annealed condition. Nonetheless, detailed examination of the strain localization behavior during tensile testing using digital image correlation showed that the IN718 specimens with AB surfaces exhibited lower ductility (global and local) relative to the hybrid and post-machined ones, most likely due to the higher surface roughness and near-surface porosity in the former. At 650 °C, even though the mechanical properties of all the heat-treated IN718 specimens surpassed the minimum specifications for the wrought precipitation-hardened IN718, the AB surface condition showed up to 4% lower strength and 33–50% lower ductility compared with the hybrid and PM surface conditions. Microfocus X-ray computed tomography (µXCT) of the fractured specimens revealed the presence of numerous open cracks on the AB surface and a predisposition for the near-surface pores to accelerate rupture, leading to premature failure at lower strains. Full article

Transporting precast modules via water is a vital component of multimodal transportation systems, increasingly utilized in large-scale Modular integrated Construction (MiC) projects where modules are prefabricated in remote factories. The effectiveness of module transportation planning significantly impacts the overall costs and productivity of MiC projects. However, existing studies on module transportation planning neglect the uncertainty inherent in MiC projects, thereby resulting in increased costs. This study proposes a two-stage stochastic programming model to optimize transportation planning through water, addressing this uncertainty. A real Hong Kong case study with 418 modules is employed to assess the effectiveness of the proposed model in comparison with three deterministic models. The optimal transportation plan of modules solved by the proposed model costs HKD 148,951, comprising 21% from temporary rentals and 79% from advance bookings. The results show that the three deterministic models, without considering the uncertainty in module demand, will incur additional transportation costs that are 25% higher on average than the results of the developed two-stage stochastic model. Additionally, this paper conducts a sensitivity analysis on the price ratio of pre-booked barges to on-demand barges to evaluate its impact on total transportation costs. The two-stage programming model developed in this paper can effectively help transport planners reduce the costs associated with module water transportation. Full article

Hydrogen, as a zero-emission fuel, produces only water when used in fuel cells, making it a vital contributor to reducing greenhouse gas emissions across industries like transportation, energy, and manufacturing. Efficient hydrogen storage requires lightweight, high-strength vessels capable of withstanding high pressures to ensure the safe and reliable delivery of clean energy for various applications. Type V composite pressure vessels (CPVs) have emerged as a preferred solution due to their superior properties, thus this study aims to predict the performance of a Type V CPV by developing its numerical model and calculating numerical burst pressure (NBP). For the validation of the numerical model, a Hydraulic Burst Pressure test is conducted to determine the experimental burst pressure (EBP). The comparative study between NBP and EBP shows that the numerical model provides an accurate prediction of the vessel’s performance under pressure, including the identification of failure locations. These findings highlight the potential of the numerical model to streamline the development process, reduce costs, and accelerate the production of CPVs that are manufactured by prepreg hand layup process (PHLP), using carbon fiber/epoxy resin prepreg material. Full article

The production of green hydrogen through proton exchange membrane water electrolysis (PEMWE) is a promising technology for industry decarbonization, outperforming alkaline water electrolysis (AWE). However, PEMWE requires significant investment, which can be mitigated through material and design advancements. Components like bipolar porous plates (BPPs) and porous transport films (PTFs) contribute substantially to costs and performance. BPPs necessitate properties like corrosion resistance, electrical conductivity, and mechanical integrity. Titanium, commonly used for BPPs, forms a passivating oxide layer, reducing efficiency. Effective coatings are crucial to address this issue, requiring conductivity and improved corrosion resistance. In this study, porous Ti64 structures were fabricated via powder technology, treating them with thermochemical nitriding. The resulting structures with controlled porosity exhibited enhanced corrosion resistance and electrical conductivity. Analysis through scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), grazing incidence XRD and X-ray photoelectron spectroscopy (XPS) confirmed the effectiveness of the coating, meeting performance requirements for BPPs. Full article

This study evaluated the properties and processing of cemented paste backfills (CPBs) for potash mining through loop tests. The CPBs were made with steel slags as the binder, granulated potash tailings as the aggregate, and waste brine water as the liquid phase. The effects of solid concentration and steel slag dosage on the transport and mechanical properties of CPBs were assessed. The loop test demonstrated that all CPB slurries performed well, exhibiting strong long-distance pipeline transport capabilities. The 28-day compressive strength of the backfills exceeded 1 MPa, meeting the design requirements for backfill strength. The key rheological parameters, including yield stress (τ₀) and viscosity coefficient (η), were comprehensively and theoretically analyzed based on the variations in pressure loss per unit distance of the filling slurry measured during the loop test. The empirical formulas for CPB pressure loss, accounting for varying flow rates and pipeline diameters, were derived with an error margin under 2%. The response surface analysis showed that the affecting extents of factors on pressure loss in CPB slurry were ranked as follows: solid concentration > cementing agent content > flow rate. This study offered valuable guidance for the processing of potash mine backfill operations. Full article