Search Results (4,257)

Gas well production prediction is an important means to determine the economic benefits of gas field development, and it is the key to realize the optimization of gas well production. However, with the continuous development of gas fields, the increasing number of low-yield and low-efficiency wells disrupted the original symmetry in the overall well distribution and production structure. Traditional production capacity prediction methods are difficult to adapt to complex geological conditions and dynamic production characteristics and cannot meet the requirements of refined management of gas fields. In this paper, a CNN-LSTM-attention hybrid prediction model incorporating physical constraints (P-C-L-A) is proposed to predict production per well. The P-C-L-A model integrates CNN’s local feature capture capability, LSTM’s time-dependent modeling, and the attention mechanism’s critical state focusing function. Moreover, the gas well decline law is embedded into the loss function to realize the joint drive of physical constraints and data of the decline curve. Compared with the traditional BP neural network, the model in this paper has higher accuracy, and the root mean square error of the proposed method is reduced by 24.41%. Furthermore, this paper proposes a full life cycle intelligent optimization production strategy of “initial static similar production + historical data-driven rolling production”. For wells in the early stage of production, static production allocation is carried out by matching wells with similar geological engineering parameters based on the symmetry of the characteristic parameters of similar production wells through the k-nearest neighbor value algorithm. For stable production wells, a machine learning model is built to predict short-term production and dynamic production optimization is achieved by rolling updates of production data. The proposed method can be extended to the production prediction of other tight gas wells using similar technical processes. Full article

This study investigates the wave-induced vertical mixing mechanism and systematically compares the application of two non-breaking wave parameterization schemes (Bv and Pw) in oceanic numerical simulations of the South China Sea, according to two key physical variables: sea surface temperature (SST) and the vertical mixing coefficient. The goal is to explore the effects of different parameterization methods on the upper-ocean temperature distribution in the South China Sea. The results indicate that although both schemes enhance vertical mixing in the upper ocean, they do so through different mechanisms. The Bv scheme directly increases the vertical mixing coefficient, demonstrating significantly stronger mixing intensity, while the Pw scheme impacts mixing indirectly by modulating turbulent kinetic energy generation, resulting in comparatively weaker mixing. SST simulation results show that the Bv scheme is more effective in reducing SST in both winter and summer, with broader spatial improvements. Further analysis of the mixing coefficient confirms that, compared to the Pw scheme, the Bv scheme not only strengthens surface mixing but also penetrates deeper into the water column. Full article

This study systematically investigates the effects of demineralization on the pyrolysis characteristics, kinetics, and thermodynamics of three biomass types (eucalyptus, straw, and miscanthus) using thermogravimetric analysis (TGA) combined with multiple kinetic approaches. The Coats–Redfern integral model was employed to determine the reaction mechanisms. The results indicate that the primary weight-loss temperature ranges for eucalyptus, straw, and miscanthus were 222.02~500.23 °C, 205.43~500.13 °C, and 202.30~490.52 °C, respectively. Demineralization increased the initial pyrolysis temperature and significantly enhanced the reaction rates. Kinetics analysis revealed that the ash content significantly influences the activation energy of the pyrolysis reaction. The average activation energies follow the trend eucalyptus (193.48 kJ/mol) < miscanthus (245.66 kJ/mol) < straw (290.13 kJ/mol). After demineralization, the activation energies of both straw and miscanthus pyrolysis decreased, with the largest reduction observed in straw, which dropped by 77.53 kJ/mol. However, the activation energy for eucalyptus pyrolysis increased by 12.52 kJ/mol after demineralization. The Coats–Redfern model and thermodynamic analysis demonstrated that each type of biomass followed distinct reaction mechanisms at different stages, which were altered after demineralization. Additionally, demineralization leads to higher ΔH and Gibbs free energy ΔG for eucalyptus, but lower values for straw and miscanthus, which indicate that the ash content has a significant impact on the biomass pyrolysis reaction. These findings provide fundamental insights into the role of ash in biomass pyrolysis kinetics and offer theoretical support for the design of pyrolysis reactors. Full article

Objective: This study systematically examined the effects of recreational football on body composition and cardiometabolic health in overweight or obese individuals via subgroup analyses of potential moderators. Methods: A systematic search was conducted across six databases (PubMed, Web of Science, the Cochrane Library, CNKI, VIP, and Wanfang Data) in May and July 2025 to identify controlled trials evaluating recreational football among overweight or obese individuals. A meta-analysis was performed to pool the effect estimates, reported as standardized mean differences (SMDs), with heterogeneity explored through subgroup analyses. Results: Recreational football interventions across 32 studies (1126 participants, aged 11–68) led to significant improvements in body composition and cardiometabolic health. The training programs ranged from 4 to 48 weeks, with sessions lasting 4 to 30 min. Key body composition outcomes included reductions in body weight (SMD = −0.51), body mass index (SMD = −0.41), body fat percentage (SMD = −0.53), fat mass (SMD = −0.40), and waist circumference (SMD = −1.43), along with increases in lean body mass (SMD = 0.18). The effects were more pronounced in females and younger participants (≤18 years). Cardiometabolic benefits included reductions in systolic blood pressure (SMD = −0.59), diastolic blood pressure (SMD = −0.75), and mean arterial pressure (SMD = −0.91), as well as resting heart rates (SMD = −0.85), especially among females, obese males, and those subject to shorter rest intervals. Participants’ peak oxygen uptake also improved (SMD = 0.81). Concerning lipid metabolism, participants’ total cholesterol, low-density lipoprotein cholesterol, and triglycerides decreased significantly, particularly in females, younger and obese individuals, and those who trained more than twice per week. High-density lipoprotein cholesterol increased significantly only in females and those involved in frequent training. In regard to glucose metabolism, participants’ fasting insulin declined (SMD = −0.47), especially in regard to programs exceeding 12 weeks, whereas no significant changes were observed in fasting blood glucose, glycated hemoglobin, or the homeostatic model assessment of insulin resistance. According to the GRADE assessments, the certainty of the evidence ranged from very low to moderate across these outcomes. Conclusions: Recreational football improves the body composition and cardiometabolic health in overweight or obese individuals, resulting in reductions in adiposity, blood pressure, lipids, and insulin, with greater benefits observed in females, younger individuals, and those engaging in more frequent training. These findings support its potential as a practical intervention for weight and cardiometabolic risk management, in both clinical and community settings. Full article

This paper addresses the issue of reduced lifespan of coastal concrete piles due to chloride ion corrosion. A combination of concrete mix optimization and pile geometry improvement measures is proposed. Based on the diffusion coefficient optimization of Fick’s second law, the service life prediction of concrete piles in corrosive environments is completed. The results show that, compared to single slag incorporation and the “slag-fly ash” dual-component mix, the “slag-fly ash-corrosion inhibitor” triple-component concrete achieves a 28-day compressive strength of 67.4 MPa, and the chloride ion diffusion coefficient is reduced to 1.14 × 10⁻¹² m²/s, significantly improving overall performance. Finite element simulations reveal that, compared to ordinary square piles, cut-corner square piles can effectively alleviate stress concentration at the pile tip and reduce settlement. The maximum stress is 3.94 MPa, and the settlement is 22.64 mm, representing reductions of about 16.3% and 15.5%, respectively, compared to ordinary square piles. Concrete service life prediction confirms that the concrete with corrosion inhibitors has a predicted service life of 31.5 years, extending 7.4 years and 13.3 years longer than the single slag and the “slag-fly ash” dual-component groups, respectively. The “material-structure” optimization theory proposed in this study provides a theoretical basis and technical path for the long-life design of coastal engineering pile foundations. Full article

As wireless systems evolve toward multiband, multifunctional convergence and high-throughput services, the demand for ultra-wideband circularly polarized (CP) antennas for multi-standard terrestrial–satellite terminals continues to grow; however, because of the dispersive nature of the three-quarter-ring phase shifter, the relative bandwidth achievable with conventional crossed-dipole antennas rarely exceeds 100%. This paper presents a compact left-hand circularly polarized (LHCP) crossed-dipole antenna that combines a cavity-backed ground, ground-slot perturbations, and parasitic patches to simultaneously broaden the impedance and axial-ratio bandwidths. The fabricated prototype achieves an impedance bandwidth (IMBW) of 0.71–3.89 GHz (138%) and a 3 dB axial-ratio bandwidth (ARBW) of 0.98–3.27 GHz (108%), while maintaining gains above 3.5 dBic across most of the frequency range. The good agreement validates the multi-technique co-design and shows that the compact architecture (0.302 λ × 0.302 λ × 0.129 λ) breaks classical crossed-dipole limits. The antenna provides a scalable building block for wideband conformal arrays in next-generation integrated GNSS–SatCom systems. Full article

In the measurement process of cold atomic gravimeters, Raman laser plays an important role both in the state preparation stage and in the atomic interference stage. This paper discusses Raman laser generation techniques. The optical phase-locked loop (OPLL) method and the electro-optical modulation (EOM) method are compared from a theoretical point of view. An OPLL system and an EOM system were constructed separately. The two schemes were tested in terms of linewidth, phase noise and long-term stability. The experimental results were analyzed and discussed. Based on the results, recommendations are given for the selection of Raman laser schemes under different scenarios. Full article

The large-scale integration of renewable energy and the high penetration of power electronic devices have led to a significant reduction in system inertia and short-circuit capacity. This is particularly manifested in the form of insufficient multiple renewable energy stations short-circuit ratio (MRSCR) and transient overvoltage issues following severe disturbances such as AC and DC faults, which greatly limit the power transfer capability of large renewable energy bases. To effectively mitigate these challenges, this paper proposes an optimal synchronous condenser deployment method tailored for large-scale renewable energy bases. The proposed mathematical model supports a hybrid centralized and distributed configuration of synchronous condensers with various capacities and manufacturers while considering practical engineering constraints such as short-circuit ratio, transient overvoltage, and available bays in renewable energy stations. A practical decomposition and iterative computation strategy is introduced to reduce the computational burden of transient stability simulations. Case studies based on a real-world system verify the effectiveness of the proposed method in determining the optimal configuration of synchronous condensers. The results demonstrate significant improvements in grid strength (MRSCR) and suppression of transient overvoltages, thereby enhancing the stability and transfer capability of renewable energy bases in weak-grid environments. Full article

Biodegradable agricultural films manufactured with straw serve as a viable substitute for plastic films, effectively addressing the issue of white pollution. However, existing biodegradable straw fiber films exhibit insufficient mechanical properties, primarily characterized by their susceptibility to fracture damage. To address this issue, a novel method for the preparation of film raw materials was proposed, which employs the synergistic treatment of bioenzymes and a single screw extruder, with the aim of enhancing the mechanical properties of the film. The method begins with the application of microbial agents to pretreat the straw, for improving its fiber morphology and inducing beneficial physicochemical structural changes. Subsequently, single screw extrusion technology is employed to further enhance the quality of the straw fibers and the mechanical performance of the film. The bio-mechanical pulp produced with this method demonstrated an increase in the crystallinity index (CrI) from 50.33% to 60.78%, while the degree of polymerization (DP) decreased from 866.51 to 749.60. Furthermore, the tensile strength, tear strength, and burst strength of the fiber covering film increased by 35.74%, 16.22%, and 11.65%, respectively, which meet the mechanical durability requirements for farmland mulching. This research effectively mitigates agricultural white pollution by converting agricultural waste straw into biodegradable mulch film, which promotes the recycling of straw resources. This study presents a novel method with significant potential application value for the production of bio-pulping in the paper industry. Full article

To address the challenges of missed and incorrect segmentation in cabbage head detection under complex field conditions using UAV-based low-altitude remote sensing, this study proposes U-MoEMamba, an innovative dynamic state-space framework with a mixture-of-experts (MoE) collaborative segmentation network. The network constructs a dynamic multi-scale expert architecture, integrating three expert paradigms—multi-scale convolution, attention mechanisms, and Mamba pathways—for efficient and accurate segmentation. First, we design the MambaMoEFusion module, a collaborative expert fusion block that employs a lightweight gating network to dynamically integrate outputs from different experts, enabling adaptive selection and optimal feature aggregation. Second, we propose an MSCrossDualAttention module as an attention expert branch, leveraging a dual-path interactive attention mechanism to jointly extract shallow details and deep semantic information, effectively capturing the contextual features of cabbages. Third, the VSSBlock is incorporated as an expert pathway to model long-range dependencies via visual state-space representation. Evaluation on datasets of different cabbage growth stages shows that U-MoEMamba achieves an mIoU of 89.51% on the early-heading dataset, outperforming SegMamba and EfficientPyramidMamba by 3.91% and 1.4%, respectively. On the compact heading dataset, it reaches 91.88%, with improvements of 2.41% and 1.65%. This study provides a novel paradigm for intelligent monitoring of open-field crops. Full article

Aiming at the complex construction environment and autonomous navigation challenges in underground coal mine roadways, this paper proposes a path navigation and deviation correction control method for tracked roadheaders in confined roadway spaces. First, a two-dimensional planar grid model of the working scenario was constructed, with dimensionality reduction in the roadway model achieved through a heading reference influence degree threshold of the tracked roadheaders. Based on the kinematics theory of tracked roadheaders, kinematic and dynamic models for deviation correction in fully mechanized excavation roadways were established. Subsequently, a path planning and tracking correction algorithm was developed, along with a heading deviation correction control algorithm based on fuzzy neural network PID. Online optimization of the particle swarm algorithm was realized through crossover-mutation operations, enabling optimal strategy solving for construction path planning and precise control of travel deviation correction. Finally, simulation experiments evaluating algorithm performance and comparative simulations of control algorithms validated the feasibility and superiority of the proposed method. This research provides strategic guidance and theoretical foundations for rapid precision deployment and intelligent deviation correction control of tracked engineering vehicles in confined underground coal mine spaces. Full article

Rice wine is a beverage rich in flavor, but the flavor difference caused by rice raw materials has received little attention. To determine the key aroma compounds in rice wine, four types of samples were analyzed by gas chromatography–mass spectrometry (GC–MS), gas chromatography–olfactometry (GC-O), and sensory evaluation. Thirty-eight aroma compounds were detected in the experiment, thirteen of which were identified and quantified using the internal standard method. Additionally, multivariate statistical analyses such as partial least squares discriminant analysis (PLS-DA) effectively revealed three major differential aroma components in rice wine (VIP value ≥ 1). Furthermore, by correlation analysis, it was found that starch and fat in the raw material properties of glutinous rice were significantly and positively correlated with the main differential volatile aroma components in rice wine (p < 0.05). Combined with principal component analysis (PCA), the selection of glutinous rice varieties associated with starch and lipid characteristics during the rice wine brewing process is conducive to improving the overall quality of rice wine. Full article

Mitochondria are central to cellular energy metabolism and play a key role in regulating important physiological processes, including apoptosis and oxidative stress. Mitochondrial quality control has recently garnered significant attention, with the underlying mechanisms traditionally considered to be mitophagy and its dynamics. Various studies have demonstrated that extracellular vesicles are crucial for the transmission of mitochondria and their components. These vesicles effectively transport mitochondria to target cells, facilitating intercellular material exchange and signal transmission, thereby enhancing cellular function and viability. This review explores the mechanisms of mitochondrial transfer through mitochondrial extracellular vesicles (MitoEVs), analyzes the novel roles of MitoEVs in mitochondrial quality control, and discusses their applications in disease treatment. We aim to provide new perspectives for future research and support the development of relevant therapeutic strategies. Full article

A series of 6:2 fluorotelomer ethoxylates (FTEOs) has been recently detected in human serum. Whether it has the potential to disrupt lipid metabolism in human populations remains largely unexplored. This study quantified serum concentrations of 6:2 FTEOs in 237 healthy Chinese adults, examined the gender- and age-specific differences in serum levels of 6:2 FTEOs, and investigated the associations between serum levels of 6:2 FTEOs and lipid profiles for the first time. Nine 6:2 FTEO homologues were detected in collected human serum, with detection frequencies of 22–81%. 6:2 FTEO8 and 6:2 FTEO9 were the more abundant 6:2 FTEO homologues in human serum, displaying the mean levels of 0.69 ng/mL (range < LOD–7.36 ng/mL) and 0.71 ng/mL (<LOD–8.12 ng/mL), respectively. Male participants had much higher (p < 0.05) mean serum levels of 6:2 FTEO6 (0.61 vs. 0.31 ng/mL), 6:2 FTEO7 (0.44 vs. 0.21 ng/mL), 6:2 FTEO8 (0.91 vs. 0.38 ng/mL), and 6:2 FTEO11 (0.35 vs. 0.18 ng/mL) than female subjects. Correlation analysis revealed a significantly positive relationship (p < 0.01) between the age of participants and human serum concentrations of 6:2 FTEO6–6:2 FTEO11. Multivariate linear regression identified significant positive associations between specific 6:2 FTEO homologues (e.g., 6:2 FTEO6, 6:2 FTEO8–6:2 FTEO10) and elevated total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride levels. Full article

Accurately predicting patient clinical outcomes is a complex task that requires integrating diverse factors, including individual characteristics, treatment histories, and environmental influences. This challenge is further exacerbated by missing data and inconsistent data quality, which often hinder the effectiveness of traditional single-task learning (STL) models. Multi-Task Learning (MTL) has emerged as a promising paradigm to address these limitations by jointly modeling related prediction tasks and leveraging shared information. In this study, we proposed MTLNFM, a multi-task learning framework built upon Neural Factorization Machines, to jointly predict patient clinical outcomes on a cohort of 2001 ICU patients. We designed a preprocessing strategy in the framework that transforms missing values into informative representations, mitigating the impact of sparsity and noise in clinical data. We leveraged the shared representation layers, composed of a factorization machine and dense neural layers that can capture high-order feature interactions and facilitate knowledge sharing across tasks for the prediction. We conducted extensive comparative experiments, demonstrating that MTLNFM outperforms STL baselines across all three tasks (i.e., frailty status, hospital length of stay and mortality prediction), achieving AUROC scores of 0.7514, 0.6722, and 0.7754, respectively. A detailed case analysis further revealed that MTLNFM effectively integrates both task-specific and shared representations, resulting in more robust and realistic predictions aligned with actual patient outcome distributions. Overall, our findings suggest that MTLNFM is a promising and practical solution for clinical outcome prediction, particularly in settings with limited or incomplete data, and can support more informed clinical decision-making and resource planning. Full article