Search Results (5,489)

This study presents the fabrication and performance optimization of porous fly ash-based geopolymer (FAGP)–polyethersulfone (PES) composite fibers with tunable FAGP loading for the multivariate adsorption of heavy-metal ions from aqueous solutions. Fibers containing 20 wt%, 40 wt%, and 60 wt% FAGP were prepared using phase inversion method and were characterized using X-ray computed tomography and mechanical testing. Adsorption experiments were conducted to assess the removal efficiencies of Pb²⁺, Cd²⁺, Cu²⁺, and Ni²⁺ at different pH values, temperatures, contact times, adsorbent dosage and initial metal-ion concentrations. The composite containing 60 wt% FAGP exhibited the high performance for all ions, and its performance was especially high for Pb²⁺. The isotherm and kinetic modeling revealed that the adsorption process followed Freundlich and Redlich–Peterson models, with mixed chemisorption–physisorption mechanisms depending on the metal-ion type. Compared with conventional adsorbents, the optimized composite fibers exhibited high adsorption capacity, enhanced handling suitability, and scalability in addition to their sustainability owing to the use of industrial by-products as precursors. These findings provide new insights into the structure–function relationships of FAGP composite fiber adsorbents and their potential for wastewater treatment applications. Full article

Shipborne fighters play a critical role in far-sea operations. However, their landing process on aircraft carrier decks involves significant risks, where accidents can lead to substantial losses. Timely and accurate risk prediction is, therefore, essential for improving flight training efficiency and enhancing the combat capability of naval aviation forces. Machine-learning algorithms have been explored for predicting landing risks in land-based aircraft. However, owing to the challenges in acquiring relevant data, the application of such methods to shipborne aircraft remains limited. To address this gap, the present study proposes a deep learning-based method for predicting landing risks of shipborne aircraft. A dataset was constructed using simulated ship movements recorded during the sliding phase along with relevant flight parameters. Model training and prediction were conducted using up to ten different input combinations with artificial neural networks, long short-term memory, and transformer neural networks. Experimental results demonstrate that all three models can effectively predict landing parameters, with the lowest average test error reaching 3.5620. The study offers a comprehensive comparison of traditional machine learning and deep learning methods, providing practical insights into input variable selection and model performance evaluation. Although deep learning models, particularly the Transformer, achieved the highest accuracy, in practical applications, the support of hardware performance still needs to be fully considered. Full article

This study investigates the effect of hydrogen embrittlement on the fracture toughness of 9% Ni steel and STS 316L stainless steel under cryogenic conditions ranging from −80 °C to −253 °C. Hydrogen charging was performed using electrochemical methods, and hydrogen uptake was quantitatively analyzed using thermal desorption spectroscopy (TDS). Fracture toughness was evaluated using crack tip opening displacement (CTOD) testing per ISO 12135, both without hydrogen (WO-H) and with hydrogen (W-H). The results showed a gradual decrease in CTOD values with decreasing temperature in both steels under hydrogen-free conditions, with ductile fracture maintained even at −253 °C. In contrast, hydrogen-charged specimens exhibited significant toughness degradation at intermediate subzero temperatures (−80 °C to −130 °C), particularly in 9% Ni steel due to its BCC crystal structure. However, at −160 °C and below, the effect of hydrogen embrittlement was suppressed mainly owing to the reduced hydrogen diffusivity. Scanning electron microscopy (SEM) analysis confirmed the transition from ductile to brittle fracture with decreasing temperature and hydrogen influences. At −253 °C, fully brittle fracture surfaces were observed in all specimens, confirming that at ultra-low temperatures, fracture behavior is dominated by temperature effects rather than hydrogen. These findings identify a practical temperature limit (approximately −160 °C) below which hydrogen embrittlement becomes negligible, providing critical insights for the design and application of structural materials in hydrogen cryogenic environments. Full article

The marine environment emerges as a key provider of food and sustainable products. However, these benefits are accompanied by numerous challenges owing to harmful algal blooms (HAB) and their associated biotoxins, which accumulate in organisms, like bivalves, threatening seafood quality. Among the various biotoxins, paralytic shellfish toxins (PST), the causative agents of paralytic shellfish poisoning (PSP), are among the most potent, lethal, and frequently reported instances of human intoxication. Removing PST from marine system is particularly challenging because of their hydrophilicity, susceptibility to biotransformation and the potential influence of other substances naturally present in the environment. Although there are several methods applied to mitigate HAB, to the best of our knowledge there are no proven effective methods for removing PST in marine environments. Consequently, there is a need to develop efficient removal technologies, especially envisaging fast, environmentally safe, inexpensive, and readily available solutions. Having examined several proposed methods for removing PST (e.g., thermal and industrial procedures, adsorption using different materials, photodegradation, AOPs) and comparing their efficacy, this study aims to streamline the current knowledge on PST removal, identify knowledge gaps, and provide valuable insights for researchers, environmental managers, and policymakers engaged in mitigating the risks associated with PST. Full article

N-Acetylneuraminic acid (Neu5Ac), the predominant form of sialic acids (Sias), is extensively utilized in the food, pharmaceutical, and cosmetic industries. Microbial fermentation serves as a critical production method for its economical, eco-friendly, and scalable production. Escherichia coli and Bacillus subtilis, as primary industrial workhorses for Neu5Ac production, have been extensively investigated owing to their well-characterized genetic frameworks and mature molecular toolkits. Nevertheless, the intricate regulatory networks inherent to microbial systems present formidable obstacles to the high-efficiency biosynthesis of Neu5Ac. This review delineates the genetic and molecular mechanisms underlying Neu5Ac biosynthesis in both E. coli and B. subtilis. Furthermore, the rational and irrational strategies for constructing Neu5Ac microbial cell factories are systematically summarized, including the application of rational metabolic engineering to relieve feedback regulation, reconfigure metabolic networks, implement dynamic regulation, and optimize carbon sources; as well as the use of irrational strategies including directed evolution of key enzymes and high-throughput screening based on biosensors. Finally, this review addresses current challenges in Neu5Ac bioproduction and proposes integrative solutions combining machine learning with systems metabolic engineering to advance the construction of high-titer Neu5Ac microbial cell factory and the refinement of advanced fermentation technologies. Full article

Spatializing crop yield statistical data with administrative divisions as the basic unit helps reveal the spatial distribution characteristics of crop yield and provides necessary spatial information to support field management and government decision-making. However, owing to an insufficient understanding of the factors affecting yield, accurately depicting its spatial differences remains challenging. Taking Hailun city, Heilongjiang Province, as an example, this study proposes a yield downscaling method based on the standardized deviation from the mean of the comprehensive crop condition index (CCCI) during key phenological periods of the growing season. First, Sentinel-2 remote sensing data were used to retrieve crop condition parameters during key phenological periods, and the CCCI was constructed using the correlation between crop condition parameters in key phenological periods and statistical yield as the weight. Subsequently, regression analysis and the entropy weight method were applied to determine the spatiotemporal dynamic weights of the CCCI during key phenological stages and to calculate the standardized deviation from the mean. By combining these two components, the comprehensive spatial difference index of the crop growth condition (CSDICGC) was derived, which offered a new way to characterize the discrepancies between the pixel-level yield and statistical yield, thereby downscaling the yield statistical data from the administrative unit to the pixel scale. The results indicated that this method achieved a regional accuracy close to 100%, with a strong fit at the pixel scale. Pixel-level accuracy validation against ground-truth maize yield data resulted in an R² of 0.82 and a mean relative error (MRE) of 4.75%. The novelty of this study was characterized by the integration of multistage crop condition parameters with dynamic spatiotemporal weighting to overcome the limitations of single-index methods. The crop yield statistical data downscaling spatialization method proposed in this paper is simple and efficient and has the potential to be popularized and applied over relatively large regions. Full article

As noted in recent blockchain review articles, several blockchain studies have attracted attention to the architecture, engineering, construction, and operation (AECO) industry. The reason is that blockchain offers opportunities to revolutionize the AECO industry owing to its transparency, traceability, and immutability. However, these benefits cannot be realized without blockchain “oracles”. Oracles are intermediary agents that connect blockchain systems to real-world applications. They function by collecting and verifying off-chain data, which is then fed into the blockchain for use by smart contracts. To investigate this uncharted territory, this paper adopts a hybrid research method of descriptive, bibliometric and content analysis; cross-mapping; and gap analysis to identify the trend; key topics; current status; future directions; and governance, ethical, legal, and social implications (GELSI) framework of blockchain oracles. This paper contributes to the body of knowledge by synthesizing trends, current status, key topics, and GELSI of blockchain oracles, promoting areas of improvement, and bridging knowledge gaps on blockchain oracles in the AECO industry. Full article

Silver nanoparticles (AgNPs) have attracted significant attention in recent years in diverse fields owing to their broad mechanisms of action. In particular, the wound healing process has become one of the main fields where the therapeutic potential of AgNPs is highlighted. AgNPs can be used as monotherapy or incorporated into composite structures in various formulations such as nanogels, hydrogels, powders, ointments, and sprays, for the treatment of a wide range of wound types including burns, excisional and incisional wounds, bone defects, surgical wounds, and diabetic ulcers. This widespread use is attributed to the strong antibacterial, anti-inflammatory, antioxidant, and cell proliferation-promoting biological properties of AgNPs. Moreover, AgNPs exhibit synergistic effects when combined with conventional antibiotics, enhancing their efficiency against resistant bacterial strains or even restoring the lost antibacterial activity. These biological properties enable AgNPs to reduce infection risk while simultaneously promoting high-quality healing by accelerating tissue regeneration. The therapeutic effectiveness of AgNPs is influenced by their physicochemical properties, including particle size, shape, and surface chemistry. In particular, synthesis methods play a significant role in determining both the biological activity and the safety profile of AgNPs. Among various methods, green synthesis approaches stand out for enabling the production of environmentally friendly, non-toxic, and highly biocompatible AgNPs. In this review, the mechanisms of action of AgNPs in wound healing are examined in detail, and recent scientific developments in this field are evaluated based on current in vitro, in vivo, and clinical studies. Full article

High-pressure hydrogen compatibility evaluations of alloys using hollow specimens were performed in accordance with ISO 7039. Hollow tensile specimens containing high-pressure hydrogen gas in a small-diameter hole along the axis can also be used to evaluate the influence of hydrogen gas without using high-pressure vessels. This method is not only simpler and less costly than the conventional approach, but it can also evaluate the instantaneous change in the environmental gas at specimen break. The following findings were obtained from slow-strain-rate tensile (SSRT) tests in a high-pressure hydrogen gas environment using hollow specimens of austenitic stainless steels: (1) the work hardening of the specimen in the SSRT tests stopped several minutes before the crack reached the outer surface owing to the influence of hydrogen; (2) the work hardening of the specimen resumed immediately after the hydrogen gas was released; (3) the crack growth took several minutes to reach the specimen’s surface; and (4) the fracture surface was not a cleavage fracture. These results indicate that materials are still ductile after exposure to the high-pressure hydrogen environment. This can be explained by the fact that hydrogen does not embrittle the material itself but inhibits the work hardening of the material. This phenomenon can be explained by the behavior of chemical bonds among atoms, and more discussion on strength from the perspective of chemical bonds is expected. Full article

Accurate online inspection of train wheelset tread defects is challenging owing to the variety and position uncertainty of defects. This study develops an improved YOLOv7 model capable of inspecting various wheelset tread defects with high accuracy and low computation complexity. This model comprises GSConv, a small target enhancement (STE) module, and StyleGAN3. GSConv significantly reduces the model volume while maintaining the feature expression ability, achieving a lightweight structure. The STE module enhances the fusion of shallow features and distribution of attention weights, significantly improving the sensitivity to small-sized defects and positioning robustness. StyleGAN3 enhances small samples by addressing inhomogeneity, thereby generating high-quality defect samples; it overcomes the limitations of traditional amplification methods regarding texture authenticity and morphological diversity, systematically improving the model’s generalization ability under sample scarcity conditions. The model achieves 1.6%, 10.7%, 48.63% and 37.97% higher mean average precision values than YOLOv7, YOLOv5, SSD, and Faster R-CNN, respectively, and the model parameter size is reduced by 73.91, 94.69, 122.11, and 154.91 MB, respectively. Hence, the proposed YOLOv7-STE model outperforms traditional models. Moreover, it demonstrates satisfactory performance in detecting small target defects in different samples, highlighting its potential applicability in online wheel tread defect inspection. Full article

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices. Full article

CO₂ hydrogenation to methanol has attracted considerable attention as a promising catalytic route for both reducing CO₂ emissions and producing valuable chemical intermediates. Among various catalysts, Cu–ZnO-based systems are the most widely studied; however, their performance remains constrained by limited methanol selectivity and stability, highlighting the need for improved catalytic strategies. In this work, liquid metal gallium (Ga) was incorporated into Cu–ZnO catalysts as an additive for CO₂ hydrogenation to methanol. Owing to its high dispersibility and fluidity, Ga helps maintain long-term catalyst stability. We investigated different introduction methods for Ga promoters and found that the physical mixing approach generated the strongest alkaline sites, thereby enhancing CO₂ activation and increasing the CO₂ conversion to methanol. Moreover, this catalyst effectively suppressed carbon deposition, further improving its stability. These findings offer new insights into the use of liquid metal Ga in CO₂ hydrogenation and provide fresh perspectives for the rational design of efficient methanol synthesis catalysts. Full article

Nuts, including tree nuts such as almonds, walnuts, cashews, and macadamias, as well as peanuts, are widely consumed for their health benefits owing to their high-quality protein content. Globally, the nut industry represents a multi-billion-dollar sector, with increasing demand driven by consumer interest in nutrition, functional foods, and plant-based diets. Recent advances in proteomic technologies have enabled comprehensive analyses of nut seed proteins, shedding light on their roles in nutrition, allergenicity, stress responses, and food functionality. Seed storage proteins such as 2S albumins, 7S vicilins, and 11S legumins, are central to nutrition and allergenicity. Their behavior during processing has important implications for food safety. Proteomic studies have also identified proteins involved in lipid and carbohydrate metabolism, stress tolerance, and defense against pathogens. Despite technical challenges such as high lipid content and limited genomic resources for many nut species, progress in both extraction methods and mass spectrometry has expanded the scope of nut proteomics. This review underscores the central role of proteomics in improving nut quality, enhancing food safety, guiding allergen risk management, and supporting breeding strategies for sustainable crop improvement. Full article

Quasi-two-dimensional (Q2D) perovskite films have garnered significant attention as novel gain media for lasers due to their tunable bandgap, narrow linewidth, and solution processability. Q2D perovskites endowed with intrinsic quantum well structures demonstrate remarkable potential as gain media for cost-effective miniaturized lasers, owing to their superior ambient stability and enhanced photon confinement capabilities. However, the mixed-phase distribution within Q2D films constitutes a critical determinant of their optical properties, exhibiting pronounced sensitivity to specific fabrication protocols and processing parameters, including annealing temperature, duration, antisolvent volume, injection timing, and dosing rate. These factors frequently lead to broad phase distribution in Q2D perovskite films, thereby inducing incomplete exciton energy transfer and multiple emission peaks, while simultaneously making the fabrication processes intricate and reducing reproducibility. Here, we report a novel annealing-free and antisolvent-free method for the preparation of Q2D perovskite films fabricated in ambient atmosphere. By constructing a tailored mixed-solvent vapor atmosphere and systematically investigating its regulatory effects on the nucleation and growth processes of film via in situ photoluminescence spectra, we successfully achieved the fabrication of Q2D perovskite films with large n narrow phase distribution characteristics. Due to the reduced content of small n domains, the incomplete energy transfer from small n to large n phases and the carriers’ accumulation in small n can be greatly suppressed, thereby suppressing the trap-assistant nonradiative recombination and Auger recombination. Ultimately, the Q2D perovskite film showed a single emission peak at 519 nm with the narrow full width at half maximum (FWHM) of 21.5 nm and high photoluminescence quantum yield (PLQY) of 83%. And based on the optimized Q2D film, we achieved an amplified spontaneous emission (ASE) with a low threshold of 29 μJ·cm⁻², which was approximately 60% lower than the 69 μJ·cm⁻² of the control film. Full article

Polyethylene terephthalate (PET) films were modified by direct fluorination using fluorine gas at room temperature and 660 torr for reaction times ranging from 10 min to 5 h. Some of the fluorinated samples were dried at 70 °C for 7 days. FT-IR and XPS analyses confirmed the successful incorporation of fluorine into the PET structure, with the formation of -CHF- and -CF₂- groups. The degree of fluorination increased with the reaction time, but excessive reaction led to the formation and loss of CF₄. Drying further decreased the fluorine content due to the continued CF₄ formation. XRD revealed that fluorination increased the crystallinity of PET owing to increased polarity, whereas drying decreased the crystallinity owing to increased crosslinking. The DSC results showed an increase in the glass transition temperature (T_g) after fluorination and drying, which was attributed to increased polarity and crosslinking, respectively. The surface hydrophilicity of PET increased significantly with fluorination time, and the water contact angle decreased to as low as 3.35°. This was due to the introduction of polar fluorine atoms and the development of a rough and porous surface morphology, as observed by AFM. Interestingly, drying of the fluorinated samples led to an increase in the water contact angle, with a maximum of 85.95°, owing to increased crosslinking and particle formation on the surface. This study demonstrates a simple and effective method for controlling the hydrophilicity and hydrophobicity of PET surfaces via direct fluorination and drying. Full article