Search Results (1,127)

Copper nanoparticles (CuNPs) have attracted attention due to their low cost and high specific surface area. In this work, a simple and inexpensive two-step synthesis method was proposed to prepare highly stable and well-dispersed spherical CuNPs in solution with a particle size of approximately 37 nm. Synthesis of CuNPs was carried on in the presence of complexing agent trisodium citrate (TSC), while for the chemical reduction step, sodium borohydride (NaBH₄) was used. Taking into account the potential of this type of nanoparticles, their synthesis and characterization represent a current and relevant topic in the field. The ability to control the size, shape and properties of CuNPs by adjusting the synthesis parameters (pH, precursor:stabilizer:reductant ratio, homogenization time, temperature) offers extraordinary flexibility in the development of these materials. The combination of characterization techniques such as SEM, EDX, UV–Vis, Raman, FT-IR and AFM provides a thorough understanding of the structure and properties of CuNPs, allowing the modulation of the properties of the obtained nanoparticles in the desired direction. Based on the studies, the copper reduction mechanism was proposed. For the theoretical verification of the size of the experimentally obtained spherical CuNPs, Mie theory was applied. A stability study of the synthesized CuNPs in optimal conditions was performed using UV–Vis analysis at specific time intervals (1, 3, 30 and 60 days), the sample being kept in the dark, inside a drawer at 25 °C. The CuNPs obtained after setting the optimal synthesis parameters (Cu(II):TSC:${\mathrm{B}\mathrm{H}}_4^{+}$ = 1:1:0.2, pH = 5, homogenization time 60 min and temperature 25 °C) were then tested to highlight their antibacterial effect on some reference bacterial strains. The obtained CuNPs demonstrated very good antimicrobial efficacy compared to traditional antimicrobials, for both Gram-negative and Gram-positive bacteria. This may reduce the development of antimicrobial resistance, an urgent medical issue. After evaluating the cytotoxic effects of CuNPs on the SKBR3 cancer cell line, a significant decrease in cell proliferation was observed at the 0.5 mg/mL concentration, with a reduction of 89% after 60 h of cultivation. Higher concentrations of CuNPs induced a more rapid cytotoxic effect, leading to an accelerated decline in cell viability. Full article

Although chitosan (CS) is used in many industries because of its low cost, biodegradability, nontoxic, antibacterial, and antioxidant qualities, it lacks sufficient mechanical and barrier properties. Biodegradable polymers based on CS, polyvinyl alcohol (PVA), and starch (S) were prepared at various ratios (1/3/6 and 1/5/4) via a blending polymerization process in the presence of water as the solvent and glacial acetic acid as the catalyst. The obtained biodegradable polymers were characterized via FTIR, TGA, SEM, and mechanical tests. The biodegradable polymers were mixed with rice straw and carbon black to study the effects of rice straw and carbon black on the physicomechanical properties of the biodegradable polymer films, including viscosity, tensile strength, elongation, and contact angle. The incorporation of rice straw and carbon black into a polymer blend significantly enhanced the physical and mechanical properties while also boosting their biodegradability by 36% and 15%, respectively, due to their biological activity. Notably, the CS/PVA/S blend with a ratio of 1/5/4, combined with rice straw, emerged as the standout performer. It exhibited superior mechanical strength and the shortest degradation time, outperforming the CS/PVA/S blended with a ratio of 1/3/6 mixed with carbon black. According to these findings, the biodegradable polymers became more soluble as the temperature increased from 30 to 45 °C. Full article

The necessity to develop skills in medical training, from simple procedures such as sutures, venipunctures, and peripheral venous cannulations to complex surgeries, has driven innovation in the fabrication of medical simulators throughout history. These simulators are crafted using materials that mimic the physical and mechanical characteristics of human body parts, providing realistic training experiences. However, the costs associated with developing these simulators pose a significant challenge, especially for low-income areas. This work explores practical options for creating cost-effective and useful simulators by fabricating pieces that represent the forearm, a common site for venipunctures and peripheral venous cannulations. The fabrication process involved combining three types of materials: polydimethylsiloxane (PDMS), food-grade silicone, and Artesil Shore 20 silicone, along with a Foley catheter to simulate the arm veins. The compatibility of these materials was thoroughly evaluated to produce valid prototypes, ensuring that the stress ratios closely matched the properties of human tissue. Preliminary evaluations showed a good acceptability rating from users. Medical students who tested the simulators found them effective for explaining the behavior of fluids in the body during venoclysis simulations and recommended elaborating on the replication of more complex structures. Full article

The ESG performance of enterprises is becoming an essential form of support for investors’ investment decisions and a critical aspect to follow to achieve sustainable development of enterprises. This study uses A-share listed companies in China from 2009 to 2022 as the research sample to study the impact of ESG performance on corporate over-indebtedness and its mechanism. The findings show that good ESG performance significantly negatively affects the level of corporate over-debt and the probability of over-debt. The mechanism test revealed that ESG performance reduces the level and probability of excessive corporate debt by alleviating information asymmetry, reducing corporate debt financing costs and short-term debt length, and improving corporate operating performance. The heterogeneity analysis indicates that the inhibitory effect of ESG performance on corporate over-indebtedness is more significant in polluting industries and regions with a low degree of marketization. Through the moderating effect, we find that improved internal control quality and increased analyst attention can enhance the inhibitory effect of ESG performance on excessive corporate debt. Based on the results above, enterprises should focus on improving ESG performance to reduce the risk of excessive debt and achieve sustainable development. This paper enriches the research on ESG performance and corporate leverage manipulation from the perspective of corporate over-indebtedness, deepens and expands the research on the mechanism of ESG performance affecting corporate over-indebtedness, and explores the moderating effect of internal and external governance mechanisms on ESG performance affecting corporate over-indebtedness. Full article

Rock bolting in underground environments is used for different fundamental reasons, including suspending potentially loosened blocks, clamping small wedges together, inducing a protective pressure arch along the contour of excavated voids to improve the self-supporting capacity of the ground, and providing passive pressure in integrated support systems. In this study, we describe a testing procedure that was developed to investigate the grouted annulus of a rock bolt using a low-cost investigation method. This diagnostic technique was based on the dynamic response of the system, where mechanical vibrations were induced within the rock bolt and the response was recorded by using geophones/accelerometers on the protruding element of the bolt (the collar and head). The collected signal was then processed to estimate the spectral response, and the amplitude spectrum was analyzed to detect the resonance frequencies. A 3D finite element model of the rock bolt and grouting was established to simulate the quality of the coupling by varying the mechanical properties of the grouting. The model’s response for the studied geometry of the rock bolt suggested that a poor quality of grouting was usually associated with flexural modes of vibration with a low resonance frequency. Good-quality grouting was associated with a frequency higher than 1400 Hz, where the axial vibration was mainly excited. Our analyses referred to short rock bolts, which are usually adopted in small tunnels. The interpretation of the experimental measurements assumed that the spectral response was significantly affected by the quality of the grouting, as demonstrated by the modeling procedure. The resonant frequency was compared with the results of the model simulation. The method was used to test the quality of rock bolts in a small experimental tunnel carved from andesite rock in Chile. Low-cost shock sensors (piezoelectric geophones) with low sensitivity but a wide frequency band were used. The main research outcome was the development of a reliable method to model the dynamic response of rock bolts in mines or for experimental applications in tunnels. Albeit limited to the current specific geometries, the modeling and testing will be adapted to other anchor/bolt options. Full article

China is a leading producer and consumer of coal, with coal being the dominant energy source. The accurate calculation of the mass carbon emission factor (EF_m) of coal is crucial as the carbon emissions from its combustion influence carbon emission assessment and policy formulation. However, discrepancies in EF_m values across documents, due to varying net calorific values (NCVs), carbon contents (CCs), and carbon oxidation factors (COFs), have posed challenges for enterprises in carbon emission calculations. By analyzing different coal types, it is found that for anthracite, the EF_m difference in different documents can reach 38.5%; for bituminous coal, it can reach 42.3%; and for lignite, it can reach 18.6%. These differences significantly affect carbon emission calculation accuracy, carbon allowance allocation fairness, and enterprise costs under the Carbon Border Adjustment Mechanism (CBAM). For instance, in 2023, the calculated carbon emissions of anthracite vary by over 300 million tons depending on the EF_m used. To address these issues, relevant departments should establish a unified EF_m release system, build a data sharing platform, and standardize enterprise testing standards to enhance the accuracy of carbon-related calculations and drive the low-carbon development of the coal industry. Full article

Blade leading edge erosion (LEE) is a persistent challenge in the wind industry, resulting in reduced aerodynamic efficiency and increased maintenance costs, with an estimated total expense of GBP 1.3M over a 25-year turbine lifetime. To mitigate these effects, leading edge protection (LEP) systems are widely used, but their real-world performance often falls short of predictions based on the standard rain erosion test (RET). This study investigates the limitations of current RET practices, which are designed to accelerate testing but fail to replicate the diverse environmental conditions experienced by wind turbines. Two LEPs with contrasting viscoelastic properties were tested using a novel design of experiments (DoEs) approach. The study explored the droplet impact frequency, combination and sequencing of high or low rainfall intensities, recovery during the inspection period and droplet size effects on erosion behaviour, to uncover significant differences in material performance compared to standard RET conditions. Results, supported by dynamic mechanical analysis (DMA), indicated that the chosen LEPs undergo a transition between elastic and brittle failure modes at a critical impact frequency, influenced by the viscoelastic properties of the material. Importantly, the findings emphasise the need for revised testing protocols across a range of parameters that incorporate realistic environmental conditions to improve the predictability of LEP performance. Full article

With the development of the chemical industry, the threat of mercury pollution to human health is increasing. Therefore, it is necessary to develop a low-cost, convenient and efficient Hg²⁺ detection method. In this study, anthracene-based Hg²⁺ fluorescent probes AN-2S and AN-4S were synthesized by a dithioacetal reaction for the rapid and efficient detection of the Hg²⁺ concentration in water. Through molecular structure design and synthesis route optimization, the complexity and cost of the probe synthesis were greatly reduced. AN-2S and AN-4S had good water solubility, rapid response abilities and anti-interference abilities, and could specifically detect Hg²⁺ using “turn-off” or “turn-on” detection modes within 1 min. The AN-4S probe showed a wide linear response range (0~40 μmol/L) and high sensitivity (4.93 × 10⁻⁸ mol/L) to Hg²⁺ in 99% aqueous solutions, over a pH range of 5~13. The reaction mechanism between the probe and Hg²⁺ was determined using 1H NMR and FT-IR spectra and Job’s curves. It was proven that the AN-2S and AN-4S probes react with Hg²⁺ in a molar ratio of 1:1 or 1:2. The dual-detection mode enabled the probes to be used not only for the accurate quantitative detection of Hg²⁺ under a fluorescence spectrometer, but also for rapid qualitative analysis using a UV flashlight as a test strip, showing a broad practical application potential. Full article

The refinement of effective data generation methods has led to a growing interest in using artificial neural networks (ANNs) to solve modeling problems related to mechanical structures. This study investigates the modeling of composite sandwich structures, i.e., structures made up of two laminated composite face sheets sandwiching a lightweight honeycomb core. An ANN was utilized to predict structural deflection and face sheet stress with low computational cost. Initially, a three-point load mode was used to determine the flexural behavior of the composite sandwich structure before subsequently analyzing the sandwich structure using the Monte Carlo sampling tool. Various combinations of face sheet materials, face sheet layer numbers, core types, core thicknesses and load magnitudes were considered as design variables in data generation. The generated data were used to train a neural network. Subsequently, the predictions of the trained ANN were compared with the outcomes of a finite element model (FEM), and the comparison was extended to real structures by conducting experimental tests. A woven carbon-fiber-reinforced polymer (WCFRP) with a Nomex honeycomb core was tested to validate the ANN predictions. The predictions from the elaborated ANN model closely matched the FEM and experimental results. Therefore, this method offers a low-computational-cost technique for designing and optimizing sandwich structures in various engineering applications. Full article

Damage to human health caused by As-contaminated water can be prevented using proper As-removal techniques, such as employing excellent arsenic adsorbents. In this study, the combined addition of Mg- and Ca-based adsorbents was investigated for the efficient removal of As from contaminated water. Following a previous study on As(V), As-removal tests targeting As(III) and several additional tests, including X-ray diffraction analysis, were conducted to clarify the mechanism of the improved performance of the combined-addition As removal. Similarly as for As(V), the combined additions of both MgCO₃ + CaO and MgCO₃ + Ca(OH)₂ improved As(III)-removal performance while inhibiting the leaching of base material components; however, they did not remove As(III) as effectively as As(V). The differences in the removal ratios of As(V) and As(III) in these combined additions were concluded to be primarily due to the different As-removal mechanisms. Mg(OH)₂ and CaCO₃ were generated, and As(III) was incorporated into the generated precipitate of Mg(OH)₂ but not into that of CaCO₃. Conversely, As(V) was incorporated into both Mg(OH)₂ and CaCO₃. Additionally, MgCO₃ + Ca(OH)₂ was evaluated as a more efficient combined-addition method because MgCO₃ + Ca(OH)₂ exhibited a higher As-removal ratio value than MgO + CaO. Proposals have been made to remove As(III) using activated carbon modified with heavy metals or transition elements, or concrete waste grafted with polymers, but these methods are complicated to prepare, costly, and involve the risk of leaching of harmful components. Adsorbents that use general Mg and Ca components as their base material do not contain such harmful components. The Mg- and Ca-based adsorbents are readily available and low-cost, and, best of all, there is no concern that they will leach harmful components. Therefore, widespread use of Mg- and Ca-based adsorbents as a measure against arsenic contamination could greatly contribute to a sustainable society. Full article

Current trends in the development of technology are linked inextricably to the increasing level of automation in technological processes and production systems. In this regard, the development of systems for supplying working fluids with adjustable pumps that have high performance characteristics, an increased service life and low operating costs is an important scientific and technical task. A primary challenge in the development of such systems lies in achieving low fluid flow rates while maintaining stable operating characteristics. This challenge stems from the fact that currently available controlled hydraulic pumps exhibit either a high cost or suboptimal life and efficiency parameters. This work focuses on the development of a plunger hydraulic pump with a small working volume. A mathematical model has been developed to investigate the characteristics, optimize the design of this pump and further expand the size range of such pumps. The solution was implemented on a computer using the dynamic modelling environment MATLAB/Simulink. In order to verify the mathematical model’s adequacy, a plunger pump prototype was built and integrated with a test bench featuring a measurement system. The test results showed higher pump efficiency and a significant reduction in hydraulic losses. An analysis of the obtained data shows that the pump is characterized by increased efficiency due to optimal flow distribution and reduced internal leakage, which makes it promising for use in hydraulic systems requiring improved operating characteristics. The developed pump has more rational characteristics compared to existing alternatives for use in water supply systems for induction superheaters. The experimental external characteristics of the developed pump are 10% higher than the external characteristics of the ULKA EX5 pump selected as an analogue, and the pressure characteristics are 65% higher. It offers production costs that are several times lower compared to existing cam-type plunger or diaphragm pumps with oil sumps and precision valve mechanisms. Additionally, it has significantly better operating characteristics and a longer service life compared to vibrating plunger pumps. Full article

Due to their precision, compact size, and high torque transfer, Rotate vector (RV) reducers are becoming more popular in industrial robots. However, repetitive operations and varying speed conditions mean that these components are prone to mechanical failure. Therefore, it is important to develop effective health monitoring (HM) strategies. Traditional approaches for HM, including those using vibration and acoustic emission sensors, encounter such challenges as noise interference, data inconsistency, and high computational costs. Deep learning-based techniques, which use current electrical data embedded within industrial robots, address these issues, offering a more efficient solution. This research provides transfer learning (TL) models for the HM of RV reducers, which eliminate the need to train models from scratch. Fine-tuning pre-trained architectures on operational data for the three different reducers of health conditions, which are healthy, faulty, and faulty aged, improves fault classification across different motion profiles and variable speed conditions. Four TL models, EfficientNet, MobileNet, GoogleNet, and ResNET50v2, are considered. The classification accuracy and generalization capabilities of the suggested models were assessed across diverse circumstances, including low speed, high speed, and speed fluctuations. Compared to the other models, the proposed EfficientNet model showed the most promising results, achieving a testing accuracy and an F1-score of 98.33% each, which makes it best suited for the HM of robotic reducers. Full article

Metal oxide semiconductor (MOS) hydrogen sensors offer advantages, such as high sensitivity and fast response, but their challenges remain in achieving low-cost fabrication and stable operation at room temperature. This study investigates Nb-doped TiO₂ (NTO) thin films prepared via a one-step micro-arc oxidation (MAO) with the addition of Nb₂O₅ nanoparticles into the electrolyte for room-temperature hydrogen sensing. The characterization results revealed that the incorporation of Nb₂O₅ altered the film’s morphology and phase composition, increasing the Nb content and forming a homogeneous composite thin film. Hydrogen sensing tests demonstrated that the NTO samples exhibited significantly improved sensitivity, selectivity, and stability compared to undoped TiO₂. Among the fabricated samples, NTO thin film prepared at Nb₂O₅ concentration of 6 g/L (NTO-6) showed the best performance, with a broad detection range, excellent sensitivity, rapid response, and good specificity to hydrogen. A strong linear relationship between response values and hydrogen concentration (10–1000 ppm) highlights its potential for precise hydrogen detection. The enhanced hydrogen sensing mechanism of NTO thin films primarily stems from the influence of Nb₂O₅; nanoparticles doping in the anatase-phase TiO₂ structure on the semiconductor surface depletion layer, as well as the improved charge transfer and additional adsorption sites provided by the Nb/Ti composite metal oxides, such as TiNb₂O₇ and Ti_0.95Nb_0.95O₄. This study demonstrates the potential of MAO-fabricated Nb-doped TiO₂ thin films as efficient and reliable hydrogen sensors operating at room temperature, offering a pathway for novel gas-sensing technologies to support clean energy applications. Full article

Gastrointestinal nematodes (GINs) inflict significant economic losses on sheep and goat farming globally due to reduced productivity and the development of anthelmintic resistance. Sustainable control strategies are urgently needed including the exploration of medicinal plants as safer alternatives to chemical anthelmintics. This genus of plants is used for anti-inflammatory, antioxidant, and antimicrobial activities. In this study, we aimed to evaluate the anthelmintic activities of Nepeta racemosa Lam. MeOH extract, n-hexane, dichloromethane (DCM), ethyl acetate (EtOAc), n-buthanol (n-BuOH) and aqueous (H₂O) subextracts, and quantify rosmarinic acid in the active extract by the HPLC method, and perform in silico molecular docking studies of rosmarinic acid to examine its binding interactions with tubulin. The anthelmintic activity of the plant extracts on gastrointestinal nematode eggs and larvae (L3) of the sheep was assessed using in vitro test methods such as the egg hatch assay and larval motility assay, conducted over a 24 h period (1, 2, 3, 4, 6, 8, 24). All extracts exhibited 100% effectiveness in the egg hatch inhibition assay, regardless of concentration (50–1.5625 mg/mL). The EtOAc subextract shows the highest effectiveness at 79.66%, followed by the MeOH extract at 74.00%, water at 64.00%, n-hexane at 67.00%, and DCM at 61.00%, and the lowest effectiveness is observed with n-BuOH at 51.66% in the larval motility assay. The major compound of EtOAc extract, the most active extract of N. racemosa, was determined as rosmarinic acid and its amount in the extract was determined as 14.50 mg/100 mg dry extract. The amount of rosmarinic acid in the MeOH extract was found to be 0.21 mg/100 mg dry extract. n-Hexane, DCM, n-BuOH, and H₂O extracts’ rosmarinic acid content was lower than the LOQ value. As tubulin plays an important role in the mechanism of anthelmintics, the major compound of the most active extract (NR-EtOAc) rosmarinic acid was docked onto the colchicine-binding site of the tubulin (5OV7) protein. Rosmarinic acid showed a similar activity spectrum to the anthelmintic drug albendazole. The discovery of low-cost and low-toxicity anthelmintic compounds is very important. Full article

In this paper, we propose a multilevel-based intrusion detection model. Firstly, we design an integrated shared feature technique, which filters the features to create a general dataset, retaining fewer but more significant features to enhance the detection accuracy of the model and reduce computational costs. The first stage employs OC-SVM to achieve the efficient classification of normal and abnormal traffic based on a general dataset. Additionally, the first stage is deployed close to the monitored system to enable low-latency prediction and privacy-preserving operations, thus enhancing flexibility and improving global classification performance. The second stage proposes a novel Edge Attention Network (EGAT) with a Multi-Head Dynamic Mechanism (MHD) framework, which introduces the graph attention mechanism and considers edge information as the only element, assigning greater weights to nodes and edges exhibiting high similarity, emphasizing their relationships and thereby improving the model’s accuracy and expressiveness. The MHDEGAT model facilitates additional weight learning by integrating the multi-head attention mechanism with edge features, while the weighted aggregation process enhances the data utilization across different network traffic. Finally, the model is trained and tested using the method of on-network data from a gas industrial control system, with an accuracy of 96.99%, a precision of 97.11%, a recall of 96.99%, and an F1 score of 96.93%, all of which outperform the comparison method. Full article