Search Results (200)

Black tea is widely consumed worldwide, and its characteristic taste and color result from fermentation, where polyphenols are enzymatically oxidized to generate major pigments, including theaflavins (TFs), thearubigins (TRs), and theabrownins (TBs). This study investigated the effects of increased oxygen treatment during fermentation on the flavor attributes and chemical properties of Congou black tea. Fresh tea leaves (variety “Fuyun 6”) were subjected to four oxygen treatments: 0 h (CK), 1 h (TY-1h), 2 h (TY-2h), and 3 h (TY-3h), with oxygen supplied at 8.0 L/min. Sensory evaluation revealed that oxygen-treated samples exhibited tighter and deeper-colored leaves, a redder liquor, fuller taste, and a sweeter fragrance compared with CK. Chromatic analysis showed significant increases in redness (a*) and luminance (L*), alongside reduced yellowness (b*), indicating enhanced liquor color. Chemical analyses demonstrated elevated levels of TFs, TRs, and TBs in oxygen treatments, with TRs showing the most pronounced increase. Non-targeted metabolomics identified 2318 non-volatile and 761 volatile metabolites, highlighting upregulated flavonoids, phenolic acids, and lipids, and downregulated catechins and tannins, which collectively contributed to improved taste and aroma. Optimal results were achieved with 2–3 h of oxygen treatment, balancing pigment formation and sensory quality. These findings can provide a scientific basis for optimizing oxygen conditions in black tea fermentation to improve product quality. Full article

Research on helicopter stability is essential for the design of flotation systems and serves as a primary basis for evaluating wind and wave resistance. The drainage volume method and fluid–solid coupling method are commonly used for calculating floating characteristics. However, the drainage volume method ignores the flexibility of airbags and their interaction with the helicopter, while the fluid–solid coupling method is computationally intensive. In contrast, the analysis of a helicopter’s hydrostatic floating characteristics is a static problem. It suffices to obtain relevant results when the helicopter reaches a stationary state, without the need to accurately simulate the dynamic process of achieving that state. Therefore, this paper proposes an equivalent calculation method, in which the hydrostatic effect of water on the helicopter is represented by the hydrostatic pressure applied across the entire flotation system. The finite element method (FEM) is then employed to determine the final static state, and the results are compared with those from the drainage volume method and available experimental data to validate the reliability of the proposed approach. To elucidate the influence mechanism of airbags and flexible connecting straps on the lateral static stability of helicopters, this paper analyzes airbag positions at various heeling angles and examines the impact of different internal airbag pressures. The results indicate that the main factor affecting lateral static stability is the displacement of the airbags. This displacement causes variations in the airbag’s buoyancy and center of buoyancy, thereby reducing the lateral heeling moment. Full article

In the aluminum electrolysis production process, the traditional cell control method based on cell voltage and series current can no longer meet the goals of energy conservation, consumption reduction, and digital-intelligent transformation. Therefore, a new digital cell control technology that is centrally dependent on various process parameters has become an urgent demand in the aluminum electrolysis industry. Among them, the real-time online measurement of alumina concentration is one of the key data points for implementing such technology. However, due to the harsh production environment and limitations of current sensor technologies, hardware-based detection of alumina concentration is difficult to achieve. To address this issue, this study proposes a soft-sensing model for alumina concentration based on a long short-term memory (LSTM) neural network optimized by a weighted average algorithm (WAA). The proposed method outperforms BiLSTM, CNN-LSTM, CNN-BiLSTM, CNN-LSTM-Attention, and CNN-BiLSTM-Attention models in terms of predictive accuracy. In comparison to LSTM models optimized using the Grey Wolf Optimizer (GWO), Harris Hawks Optimization (HHO), Optuna, Tornado Optimization Algorithm (TOC), and Whale Migration Algorithm (WMA), the WAA-enhanced LSTM model consistently achieves significantly better performance. This superiority is evidenced by lower MAE and RMSE values, along with higher R² and accuracy scores. The WAA-LSTM model remains stable throughout the training process and achieves the lowest final loss, further confirming the accuracy and superiority of the proposed approach. Full article

The rapid development of science and technology enables technological innovations to change the way of English oral learning. Based on the use of a large language model (LLM), we developed a novel dynamic evaluation system for oral English, LLM-DAELSL, which combines daily oral habits and a textbook outline. The model integrates commonly used vocabulary from everyday social speech and authoritative prior knowledge, such as oral language textbooks. It also combines traditional large-scale semantic models with probabilistic algorithms to serve as an oral assessment tool for undergraduate students majoring in English-related fields in universities. The model provides corrective feedback to effectively enhance the proficiency of English learners through guided training at any time and place. The technological principle of the model involves inputting prior template knowledge into the language model for reverse guidance and utilizing the textbooks provided by China’s Ministry of Education. The model facilitates the practice and evaluation of pronunciation, grammar, vocabulary, and fluency. The six-month tracking results showed that the oral proficiency of the system learners was significantly improved in the four aspects, which provides a reference for other language learning method developments. Full article

To address the common issues of high small object miss rates, frequent false positives, and poor real-time performance in PCB defect detection, this paper proposes a multi-scale fusion algorithm based on the YOLOv12 framework. This algorithm integrates the Global Attention Mechanism (GAM) into the redesigned A2C2f module to enhance feature response strength of complex objects in symmetric regions through global context modeling, replacing conventional convolutions with hybrid weighted downsampling (HWD) modules that preserve copper foil textures in PCB images via hierarchical weight allocation. A bidirectional feature pyramid network (BiFPN) is constructed to reduce bounding box regression errors for micro-defects by fusing shallow localization and deep semantic features, employing a parallel perception attention (PPA) detection head combining dense anchor distribution and context-aware mechanisms to accurately identify tiny defects in high-density areas, and optimizing bounding box regression using a normalized Wasserstein distance (NWD) loss function to enhance overall detection accuracy. The experimental results on the public PCB dataset with symmetrically transformed samples demonstrate 85.3% recall rate and 90.4% mAP@50, with AP values for subtle defects like short circuit and spurious copper reaching 96.2% and 90.8%, respectively. Compared to the YOLOv12n, it shows an 8.7% enhancement in recall, a 5.8% increase in mAP@50, and gains of 16.7% and 11.5% in AP for the short circuit and spurious copper categories. Moreover, with an FPS of 72.8, it outperforms YOLOv5s, YOLOv8s, and YOLOv11n by 12.5%, 22.8%, and 5.7%, respectively, in speed. The improved algorithm meets the requirements for high-precision and real-time detection of multi-category PCB defects and provides an efficient solution for automated PCB quality inspection scenarios. Full article

From 2016 to 2021, a field experiment was conducted in the North China Plain to study the long-term effects of drip irrigation and nitrogen coupling on the growth, biomass allocation, and irrigation water and fertilizer use efficiency of short-rotation triploid Populus tomentosa plantations. The experiment adopted a completely randomized block design, with one control (CK) and six water–nitrogen coupling treatments (IF, two irrigation levels × three nitrogen application levels). Data analysis was conducted using ANOVA, regression models, Spearman’s correlation analysis, and path analysis. The results showed that the effects of water and nitrogen treatments on the annual increment of diameter at breast height (ΔDBH), annual increment of tree height (ΔH), basal area of the stand (BA_S), stand volume (V_S), and annual forest productivity (AFP) in short-rotation forestry exhibited a significant stand age effect. The coupling of water and nitrogen significantly promoted the DBH growth of 2-year-old trees (p < 0.05), but after 3 years of age, the promoting effect of water and nitrogen coupling gradually diminished. In the 6th year, the above-ground biomass of Populus tomentosa was 5.16 to 6.62 times the under-ground biomass under different treatments. Compared to the I45 treatment (irrigation at soil water potential of −45 kPa), the irrigation water use efficiency of the I20 treatment (−20 kPa) decreased by 88.79%. PFP showed a downward trend with the increase in fertilization amount, dropping by 130.95% and 132.86% under the I20 and I45 irrigation levels. Path analysis indicated that irrigation had a significant effect on the BA_S, V_S, AFP, and TGB of 6-year-old Populus tomentosa (p < 0.05), with the universality of irrigation being higher than that of fertilization. It is recommended to implement phased water and fertilizer management for Populus tomentosa plantations in the North China Plain. During 1–3 years of tree age, adequate irrigation should be ensured and nitrogen fertilizer application increased. Between the ages of 4 and 6, irrigation and fertilization should be ceased to reduce resource wastage. This work provides scientific guidance for water and fertilizer management in short-rotation plantations. Full article

This study focuses on addressing the reflectivity reduction issue in La_1–xSr_xTiO_3+δ during high-temperature preparation, which is caused by oxygen vacancy generation. Bulk samples of CeO₂-doped La_1–xSr_xTiO_3+δ with varying doping contents as a second phase and sintering temperatures were prepared. The phase composition, reflectivity, and valence states were thoroughly investigated. Introducing 10 wt.%CeO₂ significantly suppressed the formation of oxygen vacancies. Thus, the occurrence of impurity levels caused by oxygen vacancies was reduced. This can further mitigate the reflection decrease caused by impurity levels as photon absorption traps. Additionally, the reduced pore structure achieved at 1450 °C contributed to improved reflectivity compared to pure La_1–xSr_xTiO_3+δ. The findings suggest that this approach has great potential for reducing oxygen vacancies sensitivity in high-reflection ceramics under high-temperature conditions and preserving their optical properties. Full article

This study investigates the identification of artificial irradiation in thermoluminescence (TL) pre-dose dating of ancient Chinese porcelain to address the challenges posed by sophisticated counterfeiting techniques. While TL pre-dose dating is effective for authenticating ceramics, modern imitations artificially irradiated to mimic ancient doses complicate accurate age determination. By analyzing the TL characteristics of five historical porcelain samples (Song, Yuan, Ming, and Qing Dynasties) and artificially irradiated modern replicas, distinct differences were observed. Natural irradiation samples exhibited lower TL sensitivity, less smooth glow curves, and reduced linear regression fit (R² < 0.97) compared to artificial counterparts, which showed higher sensitivity, smoother curves, and superior linearity (R² > 0.97). The following methodology was proposed: annealing samples to erase natural signals, applying equivalent artificial doses, and comparing TL responses. The results demonstrated significant disparities in TL behavior between ancient and irradiated samples, enabling discrimination. This approach enhances the reliability of TL pre-dose dating for porcelain authentication, offering a practical solution to combat forgery in cultural heritage preservation. Full article

Using multi-power supply units to power large-area electrothermal films can achieve high electrothermal power under low voltage. However, this method may result in poor contact between the electrodes and the electrothermal film, especially for films with large areas and curved surfaces, as well as for power supply units with small electrode spacing. This study found that the relative deviation between the measured value (R_M) and the theoretical value (R_P) of the parallel resistance, ${\displaystyle \frac{R_M-R_P}{R_P}}$, exceeds 12.8% when powering a planar Indium Tin Oxide (ITO) electrothermal film with an area of 5 cm × 5 cm and electrode spacing of less than 0.5 cm using four or more power supply units. This deviation is significantly higher than that observed for power supply units with electrode spacing ≥0.8 cm, where ${\displaystyle \frac{R_M-R_P}{R_P}}$ is 1.4% and 0.3% for spacings of 0.8 cm and 1.1 cm, respectively. By using fine sand, springs, and airbags as power supply pedestals, close contact between the electrodes and the electrothermal film can be achieved for large-area and curved-surface films due to the deformation of the sand, springs, or airbags under the heater’s weight. When an airbag power supply pedestal with twelve power supply units is used to power the bottom of an electrothermal ceramic teacup with a 20 cm² curved ITO transparent electrothermal film, the ${\displaystyle \frac{R_M-R_P}{R_P}}$ is 13.3% and the heating temperature reaches 83.1 °C. Full article

To improve the accuracy and scientific of science and technology project management, a fuzzy decision support system was developed in this study. We designed the overall deployment architecture of the system, which consists of the system access layer, system core layer, system service layer, and basic platform layer. A Web server was used to reduce the response time of the system. The indices of science and technology projects were sorted by using the fuzzy decision support process and the expert’s weight matrix. To improve evaluation accuracy, a program and the storage process of the results were established at each stage of the evaluation. The developed system spent less time querying evaluation results. The query error rate was low, indicating improved efficiency of science and technology project management. Full article

This literature review focuses on titanium alloys, which are crucial in modern manufacturing due to their excellent properties. The review covers their classification, machining challenges, and advanced cutting methods. Different alloy types (α-Ti, β-Ti, and α+β-Ti) have distinct characteristics and applications; their machining challenges include low thermal conductivity and pronounced chemical reactivity. Nowadays, advanced cutting methods of titanium alloys involve innovated tool design, efficient coolant techniques, and ultrasonic vibration cutting. The impact of these methods on cost, quality, and efficiency is analyzed, considering both positive and negative aspects. Lastly, strategies for cost reduction, efficiency improvement, and quality enhancement are explored, highlighting the complex relationship between these factors in titanium alloy processing. Full article

Traditional methods have limitations regarding efficient collaboration and dynamic response in complex dynamic environments. Although existing swarm intelligence control methods possess certain adaptive optimization capabilities, they still face challenges in individual and global collaborative optimization and adaptability. To address this challenge, a swarm intelligence control design method based on double-layer deep reinforcement learning (D-DRL) is proposed. This method uses a double architecture where the inner layer is responsible for dynamic decision-making and behavior optimization, and the outer layer manages resource allocation and strategy optimization. The dynamic interaction between the inner and outer layers, coupled with multi-level collaborative optimization, enhances the system’s adaptability and operating performance. The results of the unmanned aerial vehicle (UAV) swarm case study show that our method achieves effective convergence and outperforms existing swarm intelligence control approaches. Specifically, it simultaneously optimizes energy efficiency and task completion amount with a superior performance. This improvement significantly enhances the comprehensive task effectiveness of the swarm. Full article

In modern naval confrontation systems, adversarial underwater unmanned vehicles (UUVs) pose significant challenges, which are deployed on unmanned aerial vehicles (UAVs) due to their inherent mobility and positional uncertainty. Effective neutralization threats demand sophisticated coordination strategies between distributed agents under partial observability. This paper proposes a novel Knowledge-Enhanced Multi-Agent Deep Reinforcement Learning (MADRL) framework for coordinating UAV swarms against adversarial UUVs in asymmetric confrontation scenarios, specifically addressing three operational modes: area surveillance, summoned interception, and coordinated countermeasures. Our framework introduces three key innovations: (1) a probabilistic adversarial model integrating prior intelligence and real-time UAV sensor data to predict underwater trajectories; (2) a Multi-Agent Double Soft Actor–Critic (MADSAC) algorithm, addressing Red team coordination challenges. Experimental validation demonstrates superior performance over baseline methods in Blue target detection efficiency (38.7% improvement) and successful neutralization rate (52.1% increase), validated across escalating confrontation scenarios. Full article

In this paper, the effects of laying angle on the stress distribution and stiffness degradation of glass epoxy laminates with symmetrical cracks are systematically studied by variational analysis and numerical simulation. Based on the principle of minimum complementary energy, the control equation was established and solved using MATLAB programming. The stress field and stiffness attenuation characteristics of 90°-layer crack density (CD = 0.5 cr/mm) and laminates with different angles ${[{\theta }_m/{90}_n]}_s$ were analyzed. The results show that the crack significantly aggravates the stress concentration effect, and when the laying angle exceeds 45°, the crack growth rate and stiffness degradation rate are significantly improved. Specifically, when the laying angle is 30° and L₁/t₁ = 50, the stiffness degradation rate (E_x/E_x0) of the laminates only decreases to 0.987, while when the laying angle increases to 60° and L₁/t₁ = 3, the stiffness degradation rate suddenly decreases to 0.754 under the same conditions, indicating that small-angle laying (<45°) can effectively alleviate local stress concentration and delay stiffness degradation. By comparing the experimental data of existing references, the model error is verified to be less than 1%, and the reliability of the method is confirmed. It is further proposed that in the design of symmetrical laminated plates, the crack propagation resistance can be significantly optimized by controlling the laying angle of the main bearing layer in the range of 30°~45°, which provides a quantitative basis for crack suppression and structural life improvement in engineering. Full article

Electromagnetic induction heating, which converts electromagnetic energy into thermal energy via electron-lattice collisions, and heat conduction heating, which transfers thermal energy through lattice vibrations, both have significant impacts on the solid-state precipitation behavior caused by atomic diffusion. This paper proposes a creep method based on heat conduction heating, which utilizes the turning point of negative creep to measure the isothermal transformation start curve of the γ′ phase in the alloy. The results are compared with the thermal expansion experiments under electromagnetic induction heating and simulations from the thermodynamic analysis software JMatPro. The results indicate that the nucleation incubation period of the γ′ phase in the creep experiment is longer, excluding the non-thermal effects of electricity, and more consistent with actual heat treatment conditions. The overlapping precipitation of other phases, such as M₂₃C₆ carbides at grain boundaries, reduces the γ′ phase’s fastest precipitation temperature determined by the creep and thermal expansion methods, thereby lowering the accuracy of the isothermal transformation curve. This study provides a reference for optimizing production processes and evaluating the service performance of precipitation-strengthened iron–nickel-based alloys. Full article