Search Results (40,230)

Under conservation tillage in the Huang-Huai-Hai wheat–maize rotation area, the ridge-clearing no-till seeder for strip tillage mitigates the adverse impacts of surface residues on seeding quality by clearing stubble specifically within the seed rows, demonstrating significant potential for application and promotion. However, the inadequate understanding of the seeder’s operational performance and governing mechanisms under varying field conditions hinders its high-quality and efficient implementation. To address this issue, this study selected the stubble height, forward speed, and stubble knife rotational speed (PTO speed) as experimental factors. Employing a three-factor quasi-level orthogonal experimental design, coupled with response surface regression analysis, this research systematically elucidated the interaction mechanisms among these factors concerning the seeding depth consistency and seed spacing uniformity of the seeder. An optimized parameter-matching model was subsequently derived through equation system solving. Field trials demonstrated that a lower forward speed improved the seed spacing uniformity and seeding depth consistency, whereas high speeds increased the missing rates and spacing deviations. An appropriate stubble height enhanced the seed spacing accuracy, but an excessive height compromised depth precision. Higher PTO speeds reduced multiple indices but impaired depth accuracy. Response surface analysis based on the regression models demonstrated that the peak value of the seed spacing qualification index occurred within the forward speed range of 8–9 km/h and the stubble height range of 280–330 mm, with the stubble height being the dominant factor. Similarly, the peak value of the seeding depth qualification index occurred within the stubble height range of 300–350 mm and the forward speed range of 7.5–9 km/h, with the forward speed as the primary factor. Validation confirmed that combining stubble heights of 300−330 mm, forward speeds of 8−9 km/h, and PTO speeds of 540 r/min optimized both metrics. This research reveals nonlinear coupling relationships between operational parameters and seeding quality metrics, establishes a stubble–speed dynamic matching model, and provides a theoretical foundation for the intelligent control of seeders in conservation tillage systems. Full article

In this paper, SiC and Si/SiC ceramics were fabricated using direct laser powder bed fusion with chemical vapor infiltration. Their microstructure, mechanical properties and the impacts of silicon addition were analyzed. The incorporation of silicon led to an increase in the relative density of the silicon carbide ceramics from 76.4% to 78.3% and the compression strength increased from 39 ± 13 MPa to 90 ± 8 MPa after laser powder bed fusion with chemical vapor infiltration. The melting and re-solidification of silicon allows the silicon to encapsulate the silicon carbide grains, changing the microstructure and the failure mechanism of the silicon carbide ceramics, resulting in a small amount of silicon residue. In the LPBF-CVI SiC ceramic specimen, the LPBF-formed SiC exhibits a microhardness of 24.2 ± 1.0 GPa. In LPBF-CVI Si/SiC, the spherical dual-phase structure displays a moderately increased hardness (25.9 ± 4.4 GPa), and the CVI-formed SiC exhibits a hardness of 55.3 ± 9.3 GPa. Full article

The force ripple of a permanent magnet synchronous linear motor (PMSLM) caused by multi-source disturbances in practical applications seriously restricts its high-precision motion control performance. The traditional single-mechanism model has difficulty fully characterizing the nonlinear disturbance factors, while the data-driven method has real-time limitations. Therefore, this paper proposes a hybrid modeling framework that integrates the physical mechanism and measured data and realizes the dynamic compensation of the force ripple by constructing a collaborative suppression algorithm. At the mechanistic level, based on electromagnetic field theory and the virtual displacement principle, an analytical model of the core disturbance terms such as the cogging effect and the end effect is established. At the data level, the acceleration sensor is used to collect the dynamic response signal in real time, and the data-driven ripple residual model is constructed by combining frequency domain analysis and parameter fitting. In order to verify the effectiveness of the algorithm, a hardware and software experimental platform including a multi-core processor, high-precision current loop controller, real-time data acquisition module, and motion control unit is built to realize the online calculation and closed-loop injection of the hybrid compensation current. Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions. Full article

Background/Objectives: Most snakebite incidents in Latin America are caused by species of the Bothrops genus. Their venom induces severe local effects, against which antivenom therapy has limited efficacy. Metabolites derived from Coffea arabica have demonstrated anti-inflammatory and anticoagulant properties, suggesting their potential as therapeutic agents to inhibit the local effects induced by B. asper venom. Methods: Three enzymatic assays were performed: inhibition of the procoagulant and amidolytic activities of snake venom serine proteinases (SVSPs); inhibition of the proteolytic activity of snake venom metalloproteinases (SVMPs); and inhibition of the catalytic activity of snake venom phospholipases A₂ (PLA_2s). Additionally, molecular docking studies were conducted to propose potential inhibitory mechanisms of the metabolites chlorogenic acid, caffeine, and caffeic acid. Results: Green and roasted coffee extracts partially inhibited the enzymatic activity of SVSPs and SVMPs. Notably, the green coffee extract, at a 1:20 ratio, effectively inhibited PLA₂ activity. Among the individual metabolites tested, partial inhibition of SVSP and PLA₂ activities was observed, whereas no significant inhibition of SVMP proteolytic activity was detected. Chlorogenic acid was the most effective metabolite, significantly prolonging plasma coagulation time and achieving up to 82% inhibition at a concentration of 62.5 μM. Molecular docking analysis revealed interactions between chlorogenic acid and key active site residues of SVSP and PLA₂ enzymes from B. asper venom. Conclusions: The roasted coffee extract demonstrated the highest inhibitory effect on venom toxins, potentially due to the formation of bioactive compounds during the Maillard reaction. Molecular modeling suggests that the tested inhibitors may bind to and occupy the substrate-binding clefts of the target enzymes. These findings support further in vivo research to explore the use of plant-derived polyphenols as adjuvant therapies in the treatment of snakebite envenoming. Full article

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with hypercholesterolemia identified as a major, but modifiable risk factor. This review serves as the second part of a comprehensive analysis of dyslipidemia management. The first installment laid the groundwork by detailing the key pathophysiological mechanisms of lipid metabolism, the development of atherosclerosis, major complications of hyperlipidemia, and the importance of cardiovascular risk assessment in therapeutic decision-making. It also examined non-pharmacological interventions and conventional therapies, with a detailed focus on statins and ezetimibe. Building upon that foundation, the present article focuses exclusively on emerging pharmacological therapies designed to overcome limitations of standard treatment. It explores the mechanisms, clinical applications, safety profiles, and pharmacogenetic aspects of novel agents such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors (alirocumab, evolocumab), small interfering RNA (siRNA) therapy (inclisiran), adenosine triphosphate–citrate lyase (ACL) inhibitor (bempedoic acid), microsomal triglyceride transfer protein (MTP) inhibitor (lomitapide), and angiopoietin-like protein 3 (ANGPTL3) inhibitor (evinacumab). These agents offer targeted strategies for patients with high residual cardiovascular risk, familial hypercholesterolemia (FH), or statin intolerance. By integrating the latest advances in precision medicine, this review underscores the expanding therapeutic landscape in dyslipidemia management and the evolving potential for individualized care. Full article

The 1.9 billion metric tons of steel globally manufactured in 2023 justify the steel industry’s pivotal role in modern society’s growth. Considering the rapid development of countries that have not fully taken part in the global market, such as Africa, steel production is expected to increase in the next decade. However, the environmental burden associated with steel manufacturing must be mitigated to achieve sustainable production, which would align with the European Green Deal pathway. Such a burden is associated both with the GHG emissions and with the solid residues arising from steel manufacturing, considering both the integrated and electrical routes. The valorisation of the main steel residues from the electrical steelmaking is the central theme of this work, referring to the steel electric manufacturing in the Dalmine case study. The investigation was carried out from two different points of view, comprising the action of a plasma electric reactor and a RecoDust unit to optimize the recovery of iron and zinc, respectively, being the two main technologies envisioned in the EU-funded research project ReMFra. This work focuses on those preliminary steps required to detect the optimal recipes to consider for such industrial units, such as thermodynamic modelling, testing the mechanical properties of the briquettes produced, and the smelting trials carried out at pilot scale. However, tests for the usability of the dusty feedstock for RecoDust are carried out, and, with the results, some recommendations for pretreatment can be made. The outcomes show the high potential of these streams for metal and mineral recovery. Full article

Electricity is a significant factor in the life cycle of many products, so the reliability of greenhouse gas (GHG) emissions data is crucial. The article presents publicly available sources of emission factors representative of Poland. The aim of the study is to assess their strengths and weaknesses in the context of the calculation requirements of carbon footprint analysis in accordance with the GHG Protocol. The article presents the results of carbon footprint calculations for different ranges of emissions in the life cycle of 1 kWh of electricity delivered to a hypothetical organization. Next, a discussion on the quality of the emissions factors has been provided, taking account of data quality indicators. It was concluded that two of the emissions factors that are compared—those based on the national consumption mix and the residual mix for Poland—have been recognized as suitable for use in carbon footprint calculations. Beyond the calculation results, the research highlights the significance of the impact of the selection of emissions factors on the reliability of environmental analysis. The article identifies methodological challenges, including the risk of double counting, limited transparency, methodological inconsistency, and low correlation of data with specific locations and technologies. The insights presented contribute to improving the robustness of carbon footprint calculations. Full article

Salinization of olive orchards constitutes a front-line agronomic challenge for farmers, consumers, and the scientific community as food security, olive logistics, and land use become more unsustainable and problematic. Plantlets of two olive varieties (var. Kalamon and var. Koroneiki) were tested for their performance under soil saline conditions, in which L-methionine, choline-Cl, and L-proline betaine were applied foliarly to alleviate adverse effects. The ‘Kalamon’ variety ameliorated its photosynthetic rates when L-proline betaine and L-methionine were administered at low saline exposure. The stressed varieties achieved higher leaf transpiration rates in the following treatment order: choline-Cl > L-methionine > L-proline betaine. Choline chloride supported stomatal conductance in stressed var. Kalamon olives without this pattern, which was also followed by var. Koroneiki. Supplementation regimes created a mosaic of responses on varietal water use efficiency under stress. The total phenolic content in leaves increased in both varieties after exogenous application only at the highest levels of saline stress. None of the substances applied to olive trees could stand alone as a tool to mitigate salinity stress in order to be recommended as a solid agronomic practice. The residual exploitation of amino acids by the olive orchard microbiome must also be considered as part of an environmentally friendly, integrated strategy to mitigate salinity stress. Full article

Numerical simulations enable us to couple multiphase flow and geochemical processes to evaluate how sequestration impacts brine chemistry and reservoir properties. This study investigates these impacts during CO₂ storage at the San Juan Basin CarbonSAFE (SJB) site. The hydrodynamic model was calibrated through history-matching, utilizing data from saltwater disposal wells to improve predictive accuracy. Core-scale simulations incorporating mineral interactions and equilibrium reactions validated the model against laboratory flow-through experiments. The calibrated geochemical model was subsequently upscaled into a field-scale 3D model of the SJB site to predict how mineral precipitation and dissolution affect reservoir properties. The results indicate that the majority of the injected CO₂ is trapped structurally, followed by residual trapping and dissolution trapping; mineral trapping was found to be negligible in this study. Although quartz and calcite precipitation occurred, the dissolution of feldspars, phyllosilicates, and clay minerals counteracted these effects, resulting in a minimal reduction in porosity—less than 0.1%. The concentration of the various ions in the brine is directly influenced by dissolution/precipitation trends. This study provides valuable insights into CO₂ sequestration’s effects on reservoir fluid dynamics, mineralogy, and rock properties in the San Juan Basin. It highlights the importance of reservoir simulation in assessing long-term CO₂ storage effectiveness, particularly focusing on geochemical interactions. Full article

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

Carbon deposits on the crown of engine pistons can markedly reduce combustion efficiency and shorten service life. Conventional cleaning techniques often fail to simultaneously ensure a high carbon removal efficiency and maintain optimal surface integrity. To enable efficient and precise carbon removal, this study proposes the application of hybrid laser cleaning—combining continuous-wave (CW) and pulsed lasers—to piston carbon deposit removal, and employs response surface methodology (RSM) for multi-objective process optimization. Using the N52B30 engine piston as the experimental substrate, this study systematically investigates the combined effects of key process parameters—including CW laser power, pulsed laser power, cleaning speed, and pulse repetition frequency—on surface roughness (Sa) and carbon residue rate (RC). Plackett–Burman design was employed to identify significant factors, the method of the steepest ascent was utilized to approximate the optimal region, and a quadratic regression model was constructed using Box–Behnken response surface methodology. The results reveal that the Y-direction cleaning speed and pulsed laser power exert the most pronounced influence on surface roughness (F-values of 112.58 and 34.85, respectively), whereas CW laser power has the strongest effect on the carbon residue rate (F-value of 57.74). The optimized process parameters are as follows: CW laser power set at 625.8 W, pulsed laser power at 250.08 W, Y-direction cleaning speed of 15.00 mm/s, and pulse repetition frequency of 31.54 kHz. Under these conditions, the surface roughness (Sa) is reduced to 0.947 μm, and the carbon residue rate (RC) is lowered to 3.67%, thereby satisfying the service performance requirements for engine pistons. This study offers technical insights into the precise control of the hybrid laser cleaning process and its practical application in engine maintenance and the remanufacturing of end-of-life components. Full article

High-strength steel has high strength and low thermal conductivity, and its thin-walled parts are very susceptible to residual stress and deformation caused by cutting heat during the drilling process, which affects the machining accuracy and quality. High-strength steel thin-walled components are widely used in aerospace and other high-end sectors; however, systematic investigations into their temperature fields during drilling remain scarce, particularly regarding the evolution characteristics of the temperature field in thin-wall drilling and the quantitative relationship between drilling parameters and these temperature variations. This paper takes the thin-walled parts of AF1410 high-strength steel as the research object, designs a special fixture, and applies infrared thermography to measure the bottom surface temperature in the thin-walled drilling process in real time; this is carried out in order to study the characteristics of the temperature field during the thin-walled drilling process of high-strength steel, as well as the influence of the drilling dosage on the temperature field of the bottom surface. The experimental findings are as follows: in the process of thin-wall drilling of high-strength steel, the temperature field of the bottom surface of the workpiece shows an obvious temperature gradient distribution; before the formation of the drill cap, the highest temperature of the bottom surface of the workpiece is distributed in the central circular area corresponding to the extrusion of the transverse edge during the drilling process, and the highest temperature of the bottom surface can be approximated as the temperature of the extrusion friction zone between the top edge of the drill and the workpiece when the top edge of the drill bit drills to a position close to the bottom surface of the workpiece and increases with the increase in the drilling speed and the feed volume; during the process of drilling, the highest temperature of the bottom surface of the workpiece is approximated as the temperature of the top edge of the drill bit and the workpiece. The maximum temperature of the bottom surface of the workpiece in the drilling process increases nearly linearly with the drilling of the drill, and the slope of the maximum temperature increases nearly linearly with the increase in the drilling speed and feed, in which the influence of the feed on the slope of the maximum temperature increases is larger than that of the drilling speed. Full article

Effective earthquake early warning (EEW) is essential for disaster prevention in the built environment, enabling a rapid structural response, system shutdown, and occupant evacuation to mitigate damage and casualties. However, most current EEW systems lack rigorous reliability analyses of their predictive outcomes, limiting their effectiveness in real-world scenarios—especially for on-site warnings, where data are limited and time is critical. To address these challenges, we propose a Bayesian neural network (BNN) framework based on Stein variational gradient descent (SVGD). By performing Bayesian inference, we estimate the posterior distribution of the parameters, thus outputting a reliability analysis of the prediction results. In addition, we incorporate a continual learning mechanism based on elastic weight consolidation, allowing the system to adapt quickly without full retraining. Our experiments demonstrate that our SVGD-BNN model significantly outperforms traditional peak displacement (Pd)-based approaches. In a 3 s time window, the Pearson correlation coefficient R increases by 9.2% and the residual standard deviation $SD$ decreases by 24.4% compared to a variational inference (VI)-based BNN. Furthermore, the prediction variance generated by the model can effectively reflect the uncertainty of the prediction results. The continual learning strategy reduces the training time by 133–194 s, enhancing the system’s responsiveness. These features make the proposed framework a promising tool for real-time, reliable, and adaptive EEW—supporting disaster-resilient building design and operation. Full article

The recent discovery of Orthonairovirus songlingense (SGLV) and Norwavirus beijiense (BJNV) in China has raised significant concern due to their potential to cause severe human disease. However, little is known about the structural features and function of their nucleoproteins, which play a key role in the viral life cycle. By combining small-angle X-ray scattering (SAXS) data and AlphaFold 3 simulations, we reconstructed the BJNV and SGLV nucleoprotein structures for the first time. The SGLV and BJNV nucleoproteins have structures that are broadly similar to those of Orthonairovirus haemorrhagiae (CCHFV) nucleoproteins despite low sequence similarity. Based on structural analysis, several residues located in the positively charged region of BJNV and SGLV nucleoproteins have been indicated to be important for viral RNA binding. A positively charged RNA-binding crevice runs along the interior of the SGLV and BJNV ribonucleoprotein complex (RNP), shielding the viral RNA. Despite the high structural similarity between SGLV and BJNV nucleoprotein monomers, their RNPs adopt distinct conformations. These findings provide important insights into the molecular mechanisms of viral genome packaging and replication in these emerging pathogens. Also, our work demonstrates that experimental SAXS data can validate and improve predicted AlphaFold 3 structures to reflect their solution structure and also provides the first low-resolution structures of the BJNV and SGLV nucleoproteins for the future development of POC tests, vaccines, and antiviral drugs. Full article

In recent years, biofuels and bioenergy derived from algae have gained increasing attention, fueled by the growing demand for renewable energy sources and the urgent need to lower CO₂ emissions. This research examines the generation of bioethanol and biomethane using freshly harvested and sedimented algal biomass. Employing a factorial experimental design, various trials were conducted, with ethanol yield as the primary optimization target. The findings indicated that the sodium hydroxide concentration during pretreatment and the amylase dosage in enzymatic hydrolysis were key parameters influencing the ethanol production efficiency. Under optimized conditions—using 0.3 M NaOH, 25 μL/g starch, and 250 μL/g cellulose—fermentation yielded ethanol concentrations as high as 2.75 ± 0.18 g/L (45.13 ± 2.90%), underscoring the significance of both enzyme loading and alkali treatment. Biomethane potential tests on the residues of fermentation revealed reduced methane yields in comparison with the raw algal feedstock, with a peak value of 198.50 ± 25.57 mL/g volatile solids. The integrated process resulted in a total energy recovery of up to 809.58 kWh per tonne of algal biomass, with biomethane accounting for 87.16% of the total energy output. However, the energy recovered from unprocessed biomass alone was nearly double, indicating a trade-off between sequential valorization steps. A comparison between fresh and dried feedstocks also demonstrated marked differences, largely due to variations in moisture content and biomass composition. Overall, this study highlights the promise of integrated algal biomass utilization as a viable and energy-efficient route for sustainable biofuel production. Full article