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Abstract Background Wheat (Triticum aestivum L.) is an important grain crops in the world, and its growth and development in different stages is seriously affected by saline-alkali stress, especially in seedling stage. Therefore, nondestructive detection of wheat seedlings under saline-alkali stress can provide more comprehensive technical support for wheat breeding, cultivation and management. Results This research focused on moisture signal prediction and classification of saline-alkali stress in wheat seedlings using fusion techniques. After collecting and analyzing transverse relaxation time and Multispectral imaging (MSI) information of wheat seedlings, four regression models were used to predict the moisture signal. K-Nearest Neighbor (KNN) and Gaussian-Naïve Bayes (GNB) models were combined with fivefold cross validation to classify the prediction of wheat seedling stress. The results showed that wheat seedlings would increase the bound water content through a certain mechanism to enhance their saline-alkali stress. Under the same Na concentration, the effect of alkali stress on moisture, growth and spectrum of wheat seedlings is stronger than salt stress. The Gradient Boosting Decision Regression Tree model performs the best in predicting wheat moisture signals, with a coefficient of determination (R2P) of 0.98 and a root mean square error of 109.60. It also had a short training time (1.48 s) and an efficient prediction speed (1300 obs/s). The KNN and GNB demonstrated significantly enhanced predictive performance when classifying the fused dataset, compared to using single datasets individually. In particular, the GNB model performing best on the fused dataset, with Precision, Recall, Accuracy, and F1-score of 90.30, 88.89%, 88.90%, and 0.90, respectively. Conclusions Under the same Na concentration, the effects of alkali stress on water content, spectrum, and growth of wheat were stronger than that of salt stress, which was more unfavorable to the growth of wheat. The fusion of low-field nuclear magnetic resonance and MSI technology can improve the classification of wheat stress, and provide an effective technical method for rapid and accurate monitoring of wheat seedlings under saline-alkali stress. Graphical Abstract

The liquefied natural gas (LNG) fuel tank in a large container ship is loaded with liquid LNG at an ultra-low temperature (-163°C), there is a significant temperature difference in the cargo hold area where the entire fuel tank is located, which will have an important impact on the steel grade design and structural safety of the cargo tank in container ship. This paper develops two heat transfer models using Computational Fluid Dynamics method (CFD method) and an analytical method to analyze the temperature distribution in a large container ship equipped with Type-B LNG fuel tank. These models incorporate the arrangement and heat transfer characteristics of LNG fuel tanks. The temperature field analysis is conducted under typical the environmental conditions specified in the Code for the Construction and Equipment of Ships Transporting Liquefied Gas in Bulk (IGC Code) and the United States Coast Guard Code (USCG Code), based on the CFD method and the analytical method, and the results of temperature field distribution are compared. Additionally, a parametric analysis of the hull temperature field is further carried out, the results show that the thermal conductivity of the insulation layer in LNG storage tanks and the types of the loaded liquid cargo have a limited impact on the final temperature field distribution in hull structure. However, the selection of steel grade in the local structure of the cargo hold, especially in the inner hull part, may lead to significant changes.

ObjectiveAs polar exploration develops, hull structure designs for ice routes are no longer limited to the traditional empirical formula method as more attention is paid to the actual ice load and structural response acting on the structure. The study of structural response calculation under ice load is crucial for the structural design of polar ships. MethodsFirst, the finite element method is used to numerically simulate the ice load cases of a polar navigation ship, such as crushed ice, floating ice and layered ice. Considering the influence of the material strain rate, the dynamic response of the structure under ice load is calculated. Second, based on the structural response equivalence, the static transformation of the dynamic response is completed, and the concept of the dynamic static transformation coefficient is proposed. Finally, the range of the dynamic static conversion coefficient under different ice load cases is obtained.ResultThe results show that the conversion coefficient of the dynamic-static equivalent conversion of the bow structure under different ice load cases is between 1.0 and 1.4.ConclusionThe quasi-static equivalent method of the ice-induced dynamic response of a bow structure is verified as reasonable and feasible.

Fusarium head blight (FHB) is a major threat to global wheat production. Recent reviews of wheat FHB focused on pathology or comprehensive prevention and lacked a summary of advanced detection techniques. Unlike traditional detection and management methods, wheat FHB detection based on various imaging technologies has the obvious advantages of a high degree of automation and efficiency. With the rapid development of computer vision and deep learning technology, the number of related research has grown explosively in recent years. This review begins with an overview of wheat FHB epidemic mechanisms and changes in the characteristics of infected wheat. On this basis, the imaging scales are divided into microscopic, medium, submacroscopic, and macroscopic scales. Then, we outline the recent relevant articles, algorithms, and methodologies about wheat FHB from disease detection to qualitative analysis and summarize the potential difficulties in the practicalization of the corresponding technology. This paper could provide researchers with more targeted technical support and breakthrough directions. Additionally, this paper provides an overview of the ideal application mode of the FHB detection technologies based on multi-scale imaging and then examines the development trend of the all-scale detection system, which paved the way for the fusion of non-destructive detection technologies of wheat FHB based on multi-scale imaging.

This paper presents a framework for structural analysis of icebreakers during ramming of first-year ice ridges. The framework links the ice-ridge load and the structural analysis based on the physical characteristics of ship–ice-ridge interactions. A ship–ice-ridge interaction study was conducted to demonstrate the feasibility of the proposed framework. A PC-2 icebreaker was chosen for the ship–ice interaction study, and the geometrical and physical properties of the ice ridge were determined based on empirical data. The ice ridge was modeled by solid elements equipped with the continuous surface cap model (CSCM). To validate the approach, the simulated ice resistance was computed using the Lindqvist solution and in situ tests of R/V Xuelong 2. First, the local ice-induced pressure on the hull shell was determined based on numerical simulations. Subsequently, the local ice pressure was applied to local deformable sub-structural models of the PC-2 icebreaker hull by means of triangular impulse loads. Finally, the structural response of sub-structural models with refined meshes was computed. This case study demonstrates that the proposed framework is suitable for structural analysis of ice-induced stresses in local hull components. The results show that the ice load and the structural response obtained based on the four first-year ice-ridge models show obvious differences. Furthermore, the ice load and corresponding structural response increases with the width of the ridge and with increasing ship speed.

Crop lodging is an important cause of direct economic losses and secondary disease transmission in agricultural production. Most existing methods for segmenting wheat lodging areas use a large-volume network, which poses great difficulties for annotation and crop monitoring in real time. Therefore, an ultra-lightweight model, Lodging-U2NetP (L-U2NetP), based on a novel annotation strategy which crops the images before annotating them (Crop-annotation), was proposed and applied to RGB images of wheat captured with an unmanned aerial vehicle (UAV) at a height of 30 m during the maturity stage. In the L-U2NetP, the Dual Cross-Attention (DCA) module was firstly introduced into each small U-structure effectively to address semantic gaps. Then, Crisscross Attention (CCA) was used to replace several bulky modules for a stronger feature extraction ability. Finally, the model was compared with several classic networks. The results showed that the L-U2NetP yielded an accuracy, F1 score, and IoU (Intersection over Union) for segmenting of 95.45%, 93.11%, 89.15% and 89.72%, 79.95%, 70.24% on the simple and difficult sub-sets of the dataset (CA set) obtained using the Crop-annotation strategy, respectively. Additionally, the L-U2NetP also demonstrated strong robustness in the real-time detection simulations and the dataset (AC set) obtained using the mainstream annotation strategy, which annotates images before cropping (Annotation-crop). The results indicated that L-U2NetP could effectively extract wheat lodging and the Crop-annotation strategy provided a reliable performance which is comparable with that of the mainstream one.

Reactive oxygen species (ROS) - induced oxidative stress damage of dopaminergic neurons is the principal etiology of Parkinson's disease (PD). While most nanoenzymes can catalyze the breakdown of ROS present in the brain, they cannot eradicate the source of ROS production attributed to damaged mitochondria. Herein, we introduce a Co-doped Prussian blue (PB/Co) nanozyme that demonstrates multi-enzyme-like coordinated activity for scavenging present ROS and triggers mitophagy to remove damaged mitochondria. To further augment the brain entry efficiency of PB/Co nanozyme, we encapsulated it in 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and 2,3-bis (palmitoyloxy)propyl-2-(trimethylammonio)ethylphosphate (DPPC) cationic liposomes and developed a non-invasive inhalable nanospray ((PB/Co)@DD) that permeates the brain via the olfactory bulb. In the PD mice model, (PB/Co)@DD nanospray induced mitophagy in the striatum to eliminate the ROS production source, preventing excessive ROS-induced sustained damage to dopaminergic neurons and averting the buildup of α-synuclein deposits, thereby ultimately restoring motor function in PD mice. Our research lays the foundation for catalytic therapy to eliminate abnormal mitochondria via the induction of mitophagy in PD mice models and highlights the potential of inhalable nanoenzymes as a non-invasive therapeutic strategy for the treatment of neuroinflammatory diseases.

Welding defects are known to cause crack propagation and reduce structural fatigue performance. Based on the Paris theory of fracture mechanics, research is conducted on evaluation methods for analyzing fatigue crack propagation by adopting random loads with long-term distribution that follows the Weibull distribution for the stress ranges of fatigue loads. This approach is combined with the corrective stress intensity factor (SIF) equation and the method for calculating the reference stress and failure criterion. A large container ship is selected for a simulation, and fatigue crack propagation analysis is conducted on typical critical locations. A detailed comparison of the forecasted fatigue life is carried out between fracture mechanics theory and the S-N curve. The results indicate that the fatigue life values obtained using the two methods are of the same magnitude. In general, for the welded structure, the fatigue life value obtained via the fracture mechanics method is shorter than that obtained via the S-N curve method, while, for the free edge of the structure and the unwelded structure, the predicted fatigue life value is closer than that predicted via the S-N curve method. Moreover, the influence of initial crack defects on the fatigue life is investigated, and the results show that the depth of the initial crack will greatly affect the fatigue life of the target ship in typical locations, but the influence of the shape ratio on the fatigue life is limited. Therefore, in the actual ship construction process, controlling the initial crack depth of components is effective for limiting crack propagation and improving fatigue life. The above conclusions and suggestions can serve as a reference for the structural design and fatigue life evaluation of large container ships.

To address global challenges, research on the safety of polar navigation is indispensable. However, most of studies focus on traditional surface vessels, with few research studies on submarine. The dynamic response of submarine during surface navigation in floating ice channels under special conditions is studied in this work. Firstly, a model of the submarine incorporating an intact internal frame was established. Subsequently, the FEM-ALE coupled method was employed to simulate the structure-ice interaction, and the obtained results was verified by the Colbourne method. Then, the parametric study (navigation speed, ice thickness, and floating ice size) were analyzed from the perspectives of ice resistance, stress and plastic strain. Finally, an empirical equation suitable for the interaction between submarine and floating ice during surface navigation is improved based on the Colbourne method.

The purity of circulating hydrogen after desulfurization is mainly affected by the content of inert component methane. Based on this, the prediction method of methane content in circulating hydrogen after desulfurization is studied. From the process of hydrogen facing system, it can be seen that the methane content in circulating hydrogen after desulfurization is mainly affected by methane solubility, feed oil density, new hydrogen components, reaction temperature, hydrogen consumption per ton of oil and catalyst components. In the process of predicting the change of methane content in circulating hydrogen after desulfurization, the methane content in circulating hydrogen after desulfurization was detected under different working conditions (different influencing factors) by means of spectral absorption method and methane content detection device. According to the real-time test results, the influence of different working conditions on methane content in circulating hydrogen after desulfurization was obtained. Based on this, the change of methane content in circulating hydrogen after desulfurization was predicted under the fluctuating conditions of various influencing factors. The results show that the methane content in recycled hydrogen after desulfurization increases with the increase of methane content, reaction temperature and the addition of higher active catalyst in the reactor. When the density of feed oil is 892–909 kg/m3, the change of composition is small, which has little effect on the circulating hydrogen methane content after desulfurization. Keywords: Desulfurization, Circulating hydrogen, Methane content, Prediction, Hydrogen system, Spectral absorption method

Abstract WO3 nanorods were synthesized via a simple hydrothermal approach. Their microstructure and morphology were analyzed with x-ray diffraction, scanning electron microscope and x-ray photoelectron spectroscopy. The effects of reaction temperature, reaction time, and citric acid concentration, on the gas-sensing performance of WO3 nanorods were investigated. The optimized response value of WO3 sensor to ethanol gas (100 ppm) was 26.48, with a response time of 1 s under a low operating temperature (160 °C). The recovery capability and stability of the gas sensor were tested and discussed. Additionally, the working principle of WO3 sensor was proposed. In comparison to the sensors published by previous researchers, the WO3 sensor has shown great potential.

Carbon dioxide (CO2)-enhanced oil recovery (EOR) has great potential and opportunity for further development, and it is one of the vital carbon capture, utilization, and storage (CCUS) technologies. However, strong heterogeneity is one of the several challenges in developing reservoirs, especially for China’s continental tight oil reserves. This study investigates the effects of heterogeneous porosity and permeability on CO2 flooding evolution in low-permeable tight formation. We simulated CO2-EOR using a numerical model developed on the platform of TOUGH2MP-TMVOC to evaluate the effect of different levels of heterogeneity on oil production, gas storage, and flow behaviors in a tight reservoir, controlled by standard deviation and correlation length. A comparison of nine cases reveals that porosity heterogeneity commonly intensifies flow channeling, and there is an oil production decline with higher standard deviation and longer correlation length of porosity field. In addition, the porosity correlation length has a negligible effect on reservoir performance when the standard deviation is relatively low. Furthermore, strong heterogeneity also has a negative impact on the storage capacity of CO2 and oil production. Notably, as the standard deviation was raised to 0.1, a small sweep region arose with the early CO2 breakthrough, which led to a worse flooding effect. Finally, this study exemplifies that a higher injection/production rate and CO2 alternating N2 injection strategies can improve oil recovery in highly heterogeneous reservoirs.

Abstract Fuzzy comprehensive evaluation (FCE) is a synthetic appraisement method based on fuzzy mathematics, and evaluation result is practical and reliable, therefore, which is widely used in petroleum, construction and many other fields. This paper applies it to the evaluation of water flooding effect of oilfield. This paper introduces the principle of FCE method and the evaluation steps. The method is applied to the evaluation of water flooding development effect, which is helpful to improve the analysis level of oil and gas field development. Compared with the traditional method, this proposed method can reflect the difference of the evaluation units. Meanwhile, the weight vector is gotten by entropy method and analytic hierarchy process (AHP), which making the evaluation results more convincing. Taking W oilfield as an example, the ten factors (e.g., reserves controlled degree of water flooding, reserves producing degree of water flooding, recovery percent of recoverable reserves, water cut, water storage rate, oil recovery rate of residual recoverable reserves, cumulative water injection, maintenance of formation pressure, comprehensive decline rate, water flooding recovery) were evaluated by proposed FCE method. Then the membership matrix is established, and the weight vector is calculated by the entropy method and the AHP. Finally, the evaluation results of the two methods are obtained by fuzzy transformation and are consistent with the actual water flooding effect. Thus, the FEC method can be used as method to accurately evaluate the effect of oil field water flooding.

Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved, and existing methods tend to have high error rates on the wild data and have the defects of disappearing training gradient and slow convergence. To overcome these problems, we proposed an efficient end-to-end sentence-level lipreading model, using an encoder based on a 3D convolutional network, ResNet50, Temporal Convolutional Network (TCN), and a CTC objective function as the decoder. More importantly, the proposed architecture incorporates TCN as a feature learner to decode feature. It can partly eliminate the defects of RNN (LSTM, GRU) gradient disappearance and insufficient performance, and this yields notable performance improvement as well as faster convergence. Experiments show that the training and convergence speed are 50% faster than the state-of-the-art method, and improved accuracy by 2.4% on the GRID dataset.

As the development of the polar region continues to increase, the fatigue properties of structures at low temperature are increasingly receiving researcher attention. This study aimed to investigate the fatigue properties of T-welded and cruciform welded joints at −60 °C. Logarithmic S–N curves based on the hot-spot stress of the T-welded and cruciform welded joints at 50% and 95% confidence levels were obtained at −60 °C. The test results showed that the fatigue properties of T-welded joints were almost 2–7% better than those of the cruciform welded joints at −60 °C. Factors that affected the fatigue properties of welded joints, such as the stress concentration factor, microstructure, Vickers hardness profiles, and fractography, were also studied and the test results showed that the fatigue properties of cruciform welded joints at −60 °C were 57.215% better than at room temperature.

Pore volume of Cumulative water injection is one of the factors for evaluating water flood effect in a water flood oil field. In previous study, there were limited lab studies for evaluating oil displacement efficiency. A method to characterize the distribution of pore volume of cumulative water injection is proposed in this paper, and it is verified by a five-spot water flooding streamline simulation model. The logarithmic relation between pore volume of cumulative water injection and water saturation is established by regression. An inflection point and limit point of cumulative water injection pore volume are identified. Current simulation model indicates inflection point appears after 2–5 pore volume (PV) injection, and limit point appears after 15–25 PV injection. Both inflection and limit point vary in different regions of reservoir.

Spectral fatigue analysis is performed on the trimaran cross-deck structural detail. A global finite element (FE) model with local fine meshes at hot spot locations is built for the calculation of structural response. Three-dimensional linear potential flow theory and global FE analysis are used for wave load and stress transfer function calculations. Then, the hot spots’ fatigue damage is calculated, considering various factors influencing spectral analysis, which includes cycle counting correction factors, wave scatter diagram, and the distribution coefficient of wave headings. A full-scale model fatigue test is used to investigate the fatigue behavior of the cross-deck structural detail. Using the fatigue test data, the curve characteristic of the cross-deck structural detail is produced. Finally, the trimaran cross-deck structural detail’s fatigue characteristics are summarized and the effects of the factors influencing spectral fatigue analysis are reported.