Search Results (17,477)

Microalgae grow rapidly, require minimal space, can proliferate in non-agricultural land, do not compete with human food sources, and can be cultivated in a variety of environments, including wastewater. They are considered an ecological source of bioactive compounds, offering an environmentally friendly alternative to conventional industrial production methods, which are often resource-intensive. It is important to emphasize that both the species of microalgae and the specific culture conditions play a decisive role in the generation and storage of valuable bioactive compounds, which can act as biostimulants. Biostimulants are organic compounds or microorganisms capable of enhancing crop quality parameters by optimizing nutrient and water use efficiency, while also strengthening tolerance to abiotic stress. The aim of this article is to provide an updated understanding of biostimulants, their modes of action, and their role in regulating plant responses to abiotic stress. It further incorporates examples of successful trials that demonstrate the advantageous applications of microalgae-based biostimulants, while also addressing the barriers and limitations to their commercialization and integration into sustainable agricultural practices. Full article

Ultrafine particles, as raw materials for various industries such as construction and environmental protection, are currently obtained through repeated ball milling and multiple classifications, but classification efficiency remains at a low level. Based on the principle of hydrocyclone classification, this paper designs a hydrocyclone with a triple-vortex finder structure that can achieve finer particle size distributions without altering the main structure of the hydrocyclone. The classification performance of the triple-vortex finder hydrocyclone is investigated through numerical analysis and experimental methods, with numerical comparisons made to single-vortex finder and double-vortex finder structures. The results indicate that with an increase in the number of vortex finders, the static pressure and tangential velocity gradually decrease, reducing the likelihood of tangential vortex formation while meeting classification requirements. The axial velocity in the triple-vortex finder structure is significantly reduced, which extends the residence time within the hydrocyclone and facilitates sufficient particle classification. As the number of vortex finders increases, the zero-velocity envelope surface (LZVV) gradually migrates inward, enlarging the external swirling classification space. Through numerical and experimental analyses, it is found that the triple-vortex finder hydrocyclone exhibits the highest classification efficiency, the strongest cutting ability, and the best classification accuracy. Compared to the single-vortex finder structure, the cutting particle size of the triple-vortex finder hydrocyclone decreases by 2.5 µm, and the content of fine particles in the underflow is reduced by 4.36 percentage points, effectively decreasing the fine particle content in the underflow. The quality efficiency improves by 18.85 percentage points compared to the single-vortex finder, while the quantity efficiency shows no significant decline. The obtained data provide a theoretical foundation and data support for the structural design of the new hydrocyclone. Full article

Prestressing wedges are critical in bridge and road construction, but flaws in wedge threads lead to severe safety hazards, construction delays, and costly maintenance. Traditional manual inspection remains labor-intensive and inconsistent, particularly under variable illumination and complex surface conditions. However, few studies have investigated improving the inspection effectiveness. Therefore, this study aims to propose a lightweight FasterNET-YOLOv5 framework for accurate and robust prestress wedge flaw detection in industrial applications. The framework achieves a detection precision of 96.3%, recall of 96.2, and mAP@0.5 of 96.5 with 18% faster end-to-end inference speed, enabling deployable system configuration on portable or embedded devices, making the approach suitable for real-time industrial inspection. Further practical guidance for workshop inspection illumination conditions was confirmed by robustness evaluations, as white lighting background provides the most balanced performance for incomplete thread and scratch defects. Moreover, a mechanical model-based inverse method was exploited to link the detections from machine vision. The results also demonstrate the potential for broader 3D surface inspection tasks in threaded, machined, and curved components of intelligent, automated, and cost-effective quality control. In general, this research contributes to computational inspection systems by bridging deep learning-based flaw detection with engineering-grade reliability and deployment feasibility. Full article

Broad bean paste (BBP), a traditional Chinese fermented condiment, often suffers from inconsistent quality during spontaneous fermentation. In this study, Weissella confusa KUST3424 and Bacillus subtilis KUST4527 were isolated from BBP and evaluated as starter cultures, either individually or in combination. Flavor characteristics were analyzed using an electronic nose, electronic tongue, and GC–MS combined with odor activity value (OAV) calculations. Results showed that 13 key flavor compounds with OAVs greater than 1 were identified as major contributors to the overall aroma of fermented BBP juice (FBPJ). Moreover, inoculated groups exhibited distinct flavor profiles compared with natural fermentation, with the co-culture producing the most pronounced improvements. The mixed fermentation markedly enhanced desirable alcohols and esters, including significant increases in isoamyl alcohol (125.87%), 2-furanmethanol (128.91%), phenethyl alcohol (354.06%), and 4-vinylguaiacol (150.99%). In addition, compounds such as acetoin, guaiacol, ethyl hexanoate, and ethyl benzoate were newly generated in the co-culture group, while the diversity and total content of esters increased significantly from 0.52% to 9.69%. These findings demonstrate that the combined use of W. confusa KUST3424 and B. subtilis KUST4527 as starter cultures can effectively enhance the complexity and overall quality of BBP flavor. This co-culture strategy shows promise for enhancing flavor control and consistency in industrial-scale BBP production. Full article

Thanks to its excellent material properties, diamond-based power electronic devices have garnered widespread attention. The realization of large-sized (over 2 inches) and high-quality single-crystal diamond wafers has significantly accelerated the industrialization of diamond semiconductor materials and devices. Over years of development, diamond Schottky barrier diodes (SBDs) have evolved into three primary device structures: lateral conduction type, quasi-vertical conduction type, and vertical conduction type. However, the performance of these devices has yet to fully unlock the potential of diamond materials. Efficient edge termination structures need to be designed to synergistically optimize the forward turn-on voltage, on-resistance, and off-state breakdown voltage. This paper reviews the research progress on various existing edge termination structures of diamond SBDs, analyzes the advantages of each structure, and discusses the key challenges faced in the device fabrication processes. Full article

The cloud manufacturing (CMfg) platform serves as a centralized hub for allocating and scheduling tasks to distributed resources. It features a concrete two-agent model that addresses real-world industrial needs: the first agent handles long-term flexible tasks, while the second agent manages urgent short-term tasks, both sharing a common due date. The second agent employs multitasking scheduling, which allows for the flexible suspension and switching of tasks. This paper addresses a novel scheduling problem aimed at minimizing the total weighted completion time of the first agent’s jobs while guaranteeing the second agent’s due date. For single-machine cases, a polynomial algorithm provides an efficient baseline; for parallel machines, an exact branch-and-price approach is developed, where the polynomial method informs the pricing problem and structural properties accelerate convergence. Computational results demonstrate significant improvements: the branch-and-price solves large-sized instances (up to 40 jobs) within 7200 s, outperforming CPLEX, which fails to find solutions for instances with more than 15 jobs. This approach is scalable for industrial cloud manufacturing applications, such as automotive parts production, and is capable of handling both design validation and quality inspection tasks. Full article

In the field of acoustic wave detection, optical sensors have significant potential applications in numerous civilian and military fields due to their high sensitivity and immunity to electromagnetic interference. This study designed an undercoupled silica optical waveguide resonator (OWR) with a 2% refractive index contrast. Mode spot converters were introduced at both ends of the straight waveguide to achieve efficient optical transmission between the fiber and the waveguide. The resonator was fabricated using plasma-enhanced chemical vapor deposition (PECVD) and inductively coupled plasma (ICP) etching technologies. The results show that the quality factor (Q-factor) of the resonator reached 2.75 × 10⁶. Compared with a resonator with a refractive index difference of 0.75%, the Q-factor remained at the same order of magnitude while the sensor size was significantly reduced. To achieve high-sensitivity acoustic wave detection, this study employed an intensity demodulation method to realize acoustic wave detection with the resonator. Test results demonstrate that the OWR can detect acoustic signals in the frequency range of 25 Hz to 20 kHz, with a minimum detectable sound pressure of 1.58 μPa/Hz^1/2 @20 kHz and a sensitivity of 1.492 V/Pa @20 kHz. The sensor exhibits a good signal-to-noise ratio and stability. The proposed method shows broad application prospects in the field of acoustic sensing and is expected to enable large-scale applications in scenarios such as communication, biomedical monitoring, and precision industrial sensing. Full article

Shellfish aquaculture is considered a major pillar of the seafood industry for its high market value, which increases the value for global food security and sustainability, often constrained in terms of conventional, labor-intensive practices. This review outlines the importance of automation and its advances in the shellfish value chain, starting from the hatchery operations to harvesting, processing, traceability, and logistics. Emerging technologies such as imaging, computer vision, artificial intelligence, robotics, IoT, blockchain, and RFID provide a major impact in transforming the shellfish sector by improving the efficiency, reducing the labor costs and environmental impacts, enhancing the food safety, and providing transparency throughout the supply chain. The studies involving the bivalves and crustaceans on their automated feeding, harvesting, grading, depuration, non-destructive quality assessments, and smart monitoring in transportation are highlighted in this review to address concerns involved with conventional practices. The review puts forth the need for integrating automated technologies into farm management and post-harvest operations to scale shellfish aquaculture sustainably, meeting the rising global demand while aligning with the Sustainability Development Goals (SDGs). Full article

Equines play a crucial role in global food security, economic development, and recreation, particularly in regions such as Central Asia, parts of Africa, and South America. However, parasitic infections significantly impact their health, productivity, and reproductive performance, leading to economic losses and reduced animal welfare. This review synthesizes the effects of parasitic infections, including protozoan, helminthic, and ectoparasitic species, on equines. These infections cause hematological alterations like anemia, leukocytosis, leukopenia, and thrombocytopenia, compromising overall health and resilience. Protozoan parasites, such as Trypanosoma spp., Theileria equi, and Babesia caballi, directly affect semen quality and fertility by causing testicular lesions, orchitis, and hormonal disruptions. Helminths like Cyathostomins and Strongyles reduce nutrient absorption, impairing productivity, while some protozoan species can cause abortion through transplacental transmission. Zoonotic parasites, including Sarcocystis spp. and Toxoplasma gondii, pose a human health risk through contaminated meat and milk consumption. Despite the effectiveness of conventional anthelmintics, emerging biological control methods like Duddingtonia flagrans (BioWorma^® and Bioverm^®) show promise. However, the development of standardized herbal anthelmintics and vaccines is hindered by limited efficacy validation, complex parasite biology, and inadequate funding. The need for better diagnostic tools and sustainable treatments remains critical for the long-term sustainability of the equine industry. Full article

Prediction models for polymer injection molding quality often degrade due to shifts in operating conditions caused by variations in melting temperature, cooling efficiency, or machine conditions. To address this challenge, this study proposes a drift-aware dynamic quality-monitoring framework that integrates hybrid-feature autoencoder (HFAE) drift detection, sliding-window reconstruction error analysis, and a mixed-feature artificial neural network (ANN) for online quality prediction. First, shifts in processing parameters are rigorously quantified to uncover continuous drifts in both input and conditional output distributions. A HFAE monitors reconstruction errors within a sliding window to promptly detect anomalous deviations. Once the drift index exceeds a predefined threshold, the system automatically triggers a drift-event response, including the collection and labeling of a small batch of new samples. In benchmark tests, this adaptive scheme outperforms static models, achieving a 35.4% increase in overall accuracy. After two incremental updates, the root-mean-squared error decreases by 42.3% across different production intervals. The anomaly detection rate falls from 0.86 to 0.09, effectively narrowing the distribution gap between training and testing sets. By tightly coupling drift detection with online model adaptation, the proposed method not only maintains high-fidelity quality predictions under dynamically evolving injection molding conditions but also demonstrates practical relevance for large-scale industrial production, enabling reduced rework, improved process stability, and lower sampling frequency. Full article

High-quality AZO thin films were produced on a 4-inch Si substrate using large-area PLD equipment at a substrate temperature of 330 °C, with a ZnO: Al (98:2 wt.%) target. This study aims to enhance the electrical, optical, morphological and structural properties of large-area PLD-grown AZO thin films by tuning the deposition pressures. The samples were prepared under high-vacuum (HV) conditions, as well as in oxygen atmospheres of 0.005 mbar O₂, 0.01 mbar O₂, and 0.1 mbar O₂. Consequently, a bilayer AZO film was prepared in a combination of two deposition pressures (first layer prepared under HV, followed by the second layer prepared at 0.01 mbar O₂). Additionally, morphological and structural characterization revealed that high-quality columnar growth AZO thin films free of droplets, with a strong (002) orientation, were achieved on a 4-inch Si substrate. Moreover, Hall measurements in the Van der Pauw configuration were used to assess the electrical properties. A low electrical resistivity of 3.98 × 10⁻⁴ Ω cm, combined with a high carrier concentration (n) of 1.05 × 10²¹ cm⁻³ and a charge carrier mobility of 17.9 cm²/V s, was achieved at room temperature for the sample prepared under HV conditions. The optical characterization conducted through spectroscopic ellipsometry measurements showed that the large-area AZO sample exhibits an increased optical transparency in the visible (VIS) range with a near-zero extinction coefficient (k) and a wide bandgap of 3.75 eV, fulfilling the standards for materials classified as TCO. In addition, the increased thickness uniformity of the prepared AZO films over a large area represents a significant step in scaling the PLD technique for industrial applications. Full article

Peach firmness is a critical quality attribute, yet conventional destructive measurement methods are unsuitable for batch detection in industrial settings. This study investigated a noncontact method for firmness assessment across multiple peach cultivars based on acoustic vibration technology. Three peach cultivars were mechanically excited via a controlled air jet, and the resulting acoustic vibration responses were captured noninvasively using a laser Doppler vibrometer. The frequency-domain acoustic vibration spectra were used as input for firmness prediction models developed using partial least squares regression (PLSR), support vector regression (SVR), and a one-dimensional convolutional neural network (ISNet-1D) that incorporated Inception and squeeze-and-excitation modules. Comparative analysis demonstrated that the ISNet-1D substantially outperformed the conventional linear and nonlinear methods on an independent test set, achieving superior predictive accuracy, with a coefficient of determination ( $R_P^2)$ of 0.8069, a root mean square error (RMSEP) of 0.9206 N/mm, and a residual prediction deviation ( ${RPD}_P)$ of 2.2879. The good performance of the ISNet-1D can be attributed to the integration of multi-scale convolutional filters with a channel-wise attention mechanism. This integration allows the network to adaptively prioritize discriminative spectral features, thereby enhancing its prediction accuracy. A hierarchical transfer learning strategy was proposed to improve model generalizability, offering a practical and cost-effective means to adapt to diverse cultivars. In summary, the combination of noncontact acoustic vibration and deep learning presents a robust, accurate, and nondestructive methodology for assessing peach firmness, demonstrating considerable potential for cross-cultivar application in industrial sorting and quality control. Full article

PM_2.5 and O₃ are now the primary air pollutants in Chinese cities and pose serious risks to human health. In particular, the two- and three-dimensional patterns of urban buildings and green spaces play a crucial role in governing the dispersion of air pollutants. Using multi-source geospatial data and 2D/3D morphology metrics, this study employs an Extreme Gradient Boosting (XGBoost) model coupled with Shapley Additive Explanations (SHAP) to analyze the nonlinear effects of 2D/3D landscape and green space patterns on PM_2.5 and O₃ concentrations in the central urban area of Guiyang City. The results indicate the following findings: (1) PM_2.5 exhibits a U-shaped seasonal pattern, being higher in winter and spring and lower in summer and autumn, whereas O₃ displays an inverted U-shaped pattern, being higher in spring and summer and lower in autumn and winter. (2) PM_2.5 concentrations are higher in suburban and industrial zones and lower in central residential areas, while O₃ concentrations increase from the urban core toward the suburbs. (3) MV, BSI, BSA, BEL, BD, FAR, and BV show significant positive correlations with both PM_2.5 and O₃ (p < 0.001), whereas TH shows a significant negative correlation with PM_2.5 (p < 0.001). (4) High-density and complex building-edge patterns intensify both PM_2.5 and O₃ pollution by hindering urban ventilation and enhancing pollutant accumulation, whereas moderate vertical heterogeneity and greater tree height effectively reduce PM_2.5 concentrations but simultaneously increase O₃ concentrations due to enhanced VOC emissions. Urban form and vegetation jointly regulate air quality, highlighting the need for integrated urban planning that balances building structures and green infrastructure. The findings of this study provide practical implications for urban design and policymaking aimed at the coordinated control of PM_2.5 and O₃ pollution through the optimization of urban morphology. Full article

Phosphate tailings (PTs) are typical industrial byproducts that can rapidly neutralize soil acidity. However, their acid-neutralizing efficacy, long-term application optimization mechanisms, and high-yield regulation pathways for crops remain unclear. This study conducted a corn-potato crop rotation field trial on acidic soils, investigating the effect of different PT application rates (T: CK, 0 t·ha⁻¹; PTs-1, 6 t·ha⁻¹; PTs-2, 9 t·ha⁻¹; PTs-3, 15 t·ha⁻¹) in a multiple cropping system (C: late autumn potatoes (LAP)-early spring potatoes (ESP)-summer maize (SM)). The results showed that two consecutive applications of 9 t·ha⁻¹ of PTs produced optimal results, increasing the LAP yield by 12.82% and the soil quality by 76.51%, while improving the ESP soil quality by 46.21%. The higher yield was mainly attributed to a significant increase in the soil pH (0.72–1.58 units) and enhanced chemical and biological properties (higher exchangeable calcium (ExCa), exchangeable magnesium (ExMg), the total exchangeable salt base ion (TEB), and catalase (CAT) and urease (UE) content and lower soil exchangeable acidity (EA), exchangeable hydrogen ion (ExH), and exchangeable aluminum (ExAl) levels). Notably, a synchronized increase in the total phosphorus (TP) and total potassium (TK) during LAP cultivation, combined with simultaneous growth of TP, available nitrogen (AN), and available phosphorus (AP) during ESP cultivation, and a significant increase in TP and AP during SM cultivation, effectively promoted crop yield. Furthermore, continuous PT application significantly enriched phosphorus (P)-soluble functional bacteria, such as Actinomycetes and Chloroflexota, and enhanced the stability of bacterial-fungal cross-boundary networks. In summary, optimal acidity levels and favorable soil texture improved soil quality, consequently increasing corn and potato yields. This study reveals for the first time that PTs can substantially increase crop production via a synergistic mechanism involving acid-base balance, structural improvement, and microbial activation. Not only does this provide a novel strategy for rapidly improving acidic soils, but it also establishes a solid theoretical and technical foundation for utilizing PT resources. Full article

A multi-factor analysis of cultivar, biofertiliser, and growing season was conducted to optimise lettuce agronomic and quality traits in diverse soil conditions. The goal was to identify soil differences and offer practical recommendations to improve lettuce traits and quality for farmers and the processing industry. The study employed a complete block design with four treatments, three involving biofertilisers, applied to six lettuce cultivars grown in two contrasting soil types- Mollic Gleysol (Calcaric)-GL and Hortic Anthrosol (Terric, Transportic)-AT, across three consecutive greenhouse seasons (autumn, winter, and spring). Biofertilisers were applied to the soil before transplanting and foliarly during the growing cycle, with four of the following treatments: control (no fertilisation), a fertiliser containing beneficial microorganisms, a Trichoderma-based fertiliser, and a combination of both. In GL soil, all biofertiliser treatments increased rosette height, leaf number, and stem length, whereas in AT soil, all morphological parameters declined significantly. The green cultivars ‘Aquino’ and ‘Kiribati’ showed superior morphological performance, particularly in spring and winter. Rosette fresh weight, a key indicator of plant biomass, reached 236.4 g in ‘Aquino’ grown in GL soil, and 208.6 g in ‘Kiribati’ grown in AT soil. Dualex™ leaf sensor measurement indicated that ‘Aquino’ exhibited the highest nitrogen balance index (NBI), while the red cultivar ‘Gaugin’ recorded the highest chlorophyll, flavonoid, and anthocyanin contents. Combined fertilisers increased NBI by 6.3% and chlorophyll by 6.8% in GL soil. Trichoderma fertiliser alone raised NBI by 6.8% in GL soil, whereas in AT soil, plants accumulated more flavonoids and anthocyanins (by 9.2% and 8.5%). Optical parameters were highest in autumn. The three-factor experiment demonstrated that cultivar, biofertiliser, and growing season significantly influenced the majority of measured traits. Correlation analysis revealed that rosette fresh weight was positively associated with NBI but negatively correlated with quality-related traits. Based on these findings, cultivars ‘Aquino’, ‘Kiribati’, and ‘Gaugin’ are recommended for both farmers and the processing industry to improve lettuce production quantity and quality. Overall, cultivar, biofertiliser, and season strongly influenced the measured parameters, underscoring the importance of tailoring biofertiliser application to soil type and season to achieve optimal production outcomes. Full article