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The wide occurrence of natural phytotoxins renders many crops unfit for human consumption. To overcome this problem and produce detoxified crop varieties, we propose the use of biotechnological strategies that can enhance the harvest index without the need to increase crop biomass or alter whole plant architecture. [ABSTRACT FROM AUTHOR]

Addressing the complexities of modern Air Traffic Management (ATM), this paper introduces a novel framework for dynamic airspace sectorization, tailored to enhance efficiency and safety in congested airspaces. Central to this framework is the WP-ConvLSTM model, an innovative deep learning approach equipped with attention mechanisms. This model excels in accurately predicting workload dynamics, a critical factor in managing air traffic flow. To implement sectorization, we adopt a constrained K-means clustering technique for spatial division, followed by a refinement process involving Support Vector Machine (SVM) algorithms for precise boundary generation. Further optimization of sector boundaries is achieved through an evolutionary algorithm, ensuring both flexibility and stability in airspace divisions. Our methodology was thoroughly evaluated using real-world data from one of the busiest airspaces, demonstrating significant improvements in workload prediction accuracy and airspace sector management. The findings highlight the model's robustness in practical scenarios, offering a scalable solution for ATM challenges. We conclude with a recognition of the study's limitations and propose avenues for future research to build upon our findings, particularly in enhancing real-time data integration and adapting to evolving air traffic patterns. • Data-driven predictive airspace sectorization for ATM efficiency. • Advanced deep learning models for complex workload pattern prediction. • Constrained airspace configuration optimization for balanced efficiency and fairness. • Performance validation demonstration with real-world data. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jmacro.2008.12.003 Byline: Jingyuan Li (a), Yongming Liu (b), Guoqiang Tian (c)(d) Keywords: Monetary policy; Time consistency problem; Reputation; Continuous model Abstract: This paper develops a reputation strategic model of monetary policy with a continuous finite or infinite time horizon. By using the optimal stopping theory and introducing the notions of sequentially weak and strong rational expectation equilibria, we show that the time inconsistency problem may be solved with trigger reputation strategies not only for stochastic but also for non-stochastic settings even with a finite horizon. We show the existence of stationary sequentially strong rational expectation equilibrium under some condition, and there always exists a stationary sequentially weak rational expectation equilibrium. Moreover, we investigate the robustness of the sequentially strong rational expectation equilibrium behavior solution by showing that the imposed assumption is reasonable. Author Affiliation: (a) School of Management, Huazhong University of Science and Technology, Hubei 400732, China (b) School of Finance, Shanghai University of Finance and Economics, Shanghai 200433, China (c) Department of Economics, Texas A&M University, TAMU 4228, College Station, TX 77843, USA (d) School of Economics, Shanghai University of Finance and Economics, Shanghai 200433, China Article History: Received 25 April 2007; Accepted 18 December 2008

Structural system identification (ID) is an important tool for many structural and infrastructure applications, such as structural health monitoring and structural model updating. A novel physics-guided generative adversarial network (PG-GAN) is proposed in this study for probabilistic structural parameter ID. The PG-GAN leverages the powerful distribution learning ability of GANs while also enabling physical awareness by incorporating additional generators for physical parameters and developing a physics-based loss function that links the data generator with the parameter generators through existing physics knowledge to guide the training of generative models. Two experiments are performed to validate the effectiveness of the PG-GAN for structural parameter ID and demonstrate its application in structural damage detection. The PG-GAN is shown to successfully capture the uncertainty inherent in structural parameter estimation and accurately locate and quantify structural damages in terms of probabilistic distributions of the damage extent. The main contributions of this study are threefold: (1) compared with traditional methods for structural parameter ID, the proposed PG-GAN provides an intelligent framework for probabilistic identification of structural parameters without the need for any assumption on the data distribution and does not require an initial guess of parameters; (2) unlike traditional data-driven GANs, the proposed PG-GAN provides a linkage between GAN and physics knowledge to enables physical awareness in generative model training; and (3) the proposed PG-GAN can serve as an intelligent diagnostic system to better inform the decision-making on structural health management as it can quantify the uncertainty in the structural damage extent. [ABSTRACT FROM AUTHOR]

• Innovative framework to construct GP model for fatigue life prediction is developed. • Fatigue-based physics constraints were incorporated into the GP model. • GP trained on one-dimensional cyclic loading cases outperformed parametric models. • Fatigue-based physics constraints imposed on GP reduce the overfitting risk. Under multiaxial fatigue loading, the superposed static components are additional factors for life prediction models to be considered. The increased dimension in fatigue data imposes difficulties in pattern recognition using existing functional form models. A framework to build a Gaussian process (GP) model for lifetime prediction under multiaxial loading was developed to solve this problem. Physically consistent constraints were imposed by applying a novel technique on the GP model to control its behavior and to decrease an overfitting risk. The model consistency with the rotationally invariant principle of damage was provided by the application of the critical plane concept. The framework was demonstrated to have excellent prediction capability on S355 steel and 7075-T651 aluminum alloy. Five well-known fatigue models of functional forms were also implemented for comparison. Detailed parametric studies were presented for the training sample effect, GP kernel effect, and model predictability. [ABSTRACT FROM AUTHOR]

A critical plane-based mixed-mode delamination growth model for composite materials under fatigue loadings is proposed in this study. A brief review for mixed-mode delamination is given and the special focus in the study is on a critical plane-based fracture criterion since it can automatically adapt for different local failure modes. An equivalent energy release rate range suitable for fatigue analysis is proposed for the delamination growth rate prediction under general proportional and non-proportional multiaxial loadings. The proposed methodology is validated with extensive experimental data available in the open literature. A general good agreement is observed between model predictions and experimental observations. Finally, some discussion and conclusions are drawn based on the proposed model. [ABSTRACT FROM AUTHOR]

Submersibles and submarines are subject to cyclic compressive sea loading during their service life, which is quite different from the ships and platforms under tensile and bending loading. It is important to study the fatigue crack propagation under cyclic compression in order to assess the fatigue life of the submersible and submarine. An extended McEvily model is proposed for the fatigue crack growth prediction under cyclic compression-compression loading. First, Finite Element Method (FEM) simulation and a simplified stress estimation method are proposed for efficient fatigue crack growth analysis. In the Finite Element Method simulation, the crack opening loads of different crack lengths are calculated individually instead of plastic wake calculation behind crack tip with node releasing technique, which will save a lot of calculating time. Afterwards the fatigue life under cyclic compression is predicted based on new fatigue crack growth rate curve model for cyclic compression. Meanwhile the analytical method is an engineering estimation for fatigue crack growth under constant amplitude compression. In this method, the crack opening load is estimated based on the symmetry of compression and tension. Then the fatigue life under cyclic compression is also predicted based on a new model for cyclic compression. Finally, fatigue life prediction of a double edged specimen under cyclic compressive loading is taken for example to illustrate the analysis procedure of two simplified methods. By comparing the predicted results with the test data, it is found that the a - N curve and final crack length by two methods are in good agreement with the test data, so the Finite Element Method and analytical method are reasonable and feasible for fatigue crack growth prediction of deepwater structure under cyclic compression. [ABSTRACT FROM AUTHOR]

A new fatigue crack growth model at the subcycle scale is proposed for both positive and negative stress ratios. The term “subcycle” refers to the crack growth modeling within a cyclic loading duration rather than the classical cycle averaged crack growth rate (i.e., da/dN). The proposed model includes two major components: a subcycle crack growth rate function and a crack opening stress estimation algorithm for tension–tension and tension–compression cyclic loading. The subcycle crack growth rate function is proposed based on existing in situ scanning electron microscopy testing results. Following this, separation of far field crack contact and near tip crack contact are discussed for both positive and negative stress ratios. A simple linearized model is proposed to estimate the crack opening stress. The developed simplified crack opening stress estimation model is compared with several other models available from open literatures. Next, the proposed subcycle fatigue crack growth methodology is validated with several sets experimental data for various metallic materials under different positive and negative stress ratios. Some discussions and conclusions are drawn based on the proposed model. [ABSTRACT FROM AUTHOR]

A time-based subcycle fatigue crack growth (FCG) formulation and validation are proposed to calculate the fatigue crack growth under general random variable amplitude loadings. The intrinsic difficulties of the classical cycle-based formulation for general random variable loadings are discussed first. Several typical spectrums that are not appropriate for cycle-based FCG are illustrated, such as the “Christmas tree” spectrums. A time-based subcycle formulation is then proposed to address this difficulty. The proposed model includes three major component: (1) a time-based crack growth kinetics function at the subcycle (time) scale; (2) an efficient crack tip opening displacement (CTOD) estimation method; (3) a crack tip plasticity zone tracking algorithms for crack opening level determination of a growing crack. Detailed derivation and calculation procedures are given. Following this, several numerical examples are illustrated for the proposed model under different loading spectrums for the crack growth and CTOD calculation. Randomly generated loading spectrums are used to illustrate the capability of the proposed method under arbitrary loadings. Next, in-house testing for “Christmas tree spectrum” and literature data on several representative variable loading spectrums are used for model validation. Finally, some conclusions and future work are drawn based on the proposed study. [ABSTRACT FROM AUTHOR]

An experimental testing procedure is proposed for generating creep-dominant creep-fatigue interaction in Alloy 617 at 950 °C. Most experimental studies on Alloy 617 at elevated temperatures employ a purely strain-controlled loading waveform with a tensile hold period. Strain-controlled loading can only generate interaction in the fatigue-dominant regime of the damage interaction diagram, due to the saturation effect of increasing hold time on cycle life. This saturation is caused by the rapid stress relaxation of Alloy 617 at high temperatures. Design codes for components undergoing creep-fatigue interaction at high temperatures require creep-fatigue testing data in the creep-dominant regime. This study investigates multiple creep-fatigue loading waveforms with the objective of producing creep-dominant interaction. The custom loading waveforms are implemented on a servo-hydraulic load frame with a furnace. A hybrid-control scheme with strain-controlled ramps and load-controlled hold periods is proposed due to its flexibility in generating varying proportions of creep and fatigue damage. Experimental data is presented and different loading schemes are compared. Special emphasis is on the creep and fatigue damage contributions by the newly proposed testing method. Several conclusions are discussed and an extension of this current work is suggested to improve the damage interaction diagram for design purposes. [ABSTRACT FROM AUTHOR]