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Optical computing has been proven to have the ability to process information with ultra‐high speed. Here, an all‐optical feature extraction system via sparse representation (AFE‐SR) is introduced. The AFE‐SR, which is achieved by multiple diffractive optical elements (DOEs), can realize the recognition of generated physical fields with the speed of light. The sparse representation simplifies the target and improves the recognition accuracy. With the mathematical analysis principle of sparse optical features extraction and optical integration, the identification accuracy of the generation of physical fields is 100% in 2100 frames of the experimental videos. The application field of optical computing systems is extended to state recognition. [ABSTRACT FROM AUTHOR]

This study explores the contribution of glass phase and rubber phase to polymer failure, and establishes a theoretical model of temperature‐dependent tensile strength (TDTS) considering the effect of two‐phase transition based on the Force‐heat Equivalence Energy Density Principle (FHEEDP). The model achieves good verification by comparison with the TDTS experimental data of various polymer materials, including epoxy‐based shape memory polymer (SMP), PEEK‐based SMP and CdS/PMMA. The results demonstrate that the model can perform an accurate prediction for the tensile strength of polymer at different temperatures by easily obtainable material parameters. In conclusion, the proposed theoretical model deepens the understanding on the two‐phase transition and their effect on the TDTS, as well as supplies a practical predicted method on the TDTS of polymer, which is crucial for polymer applied in extreme condition. [ABSTRACT FROM AUTHOR]

We study the impact of environmental regulation on the transfer of a clean technology where bureaucrats are needed for government intervention. In the absence of corruption, when environmental taxes are low, a technology transfer always takes place and it increases total outputs, but may lead to higher pollution levels. However, when corruption is possible, a firm with a dirty technology may choose to bribe a corruptible bureaucrat who will underreport the actual level of emissions, thereby hindering the transfer of clean technology. We show that a less strict anticorruption policy may lead to more bribing, but encourage technology transfers. Moreover, an environment‐oriented government would set a deterrent environmental tax to reduce pollution, while an output‐oriented government would set a minimum tax rate to eliminate corruption and induce technology transfers. However, a balanced government would tolerate corruption when the cost of bribing is low and the clean technology is sufficiently efficient. [ABSTRACT FROM AUTHOR]

Trend prediction of greenhouse microclimate is crucial, as greenhouse crops are vulnerable to potential losses resulting from dramatic changes in greenhouse microclimate. Consequently, a precise greenhouse microclimate predictive model is required that can predict trends in greenhouse microclimates several weeks in advance to avoid financial losses. In the present study, we proposed a hybrid ensemble approach to predict greenhouse microclimate based on an Informer model that is optimized using improved empirical mode decomposition (IEMD). The dataset was decomposed using IEMD, and then all the decomposed datasets were predicted using the Informer model. Afterward, the predictions were combined. In the present study, five different environmental factor datasets of CO2 concentration, atmospheric pressure, light intensity, temperature, and humidity were predicted. The performance of the IEMD-Informer model was compared with other modeling approaches. The results demonstrate that the proposed method has outstanding performance and can predict the greenhouse microclimate environmental factors more accurately. [ABSTRACT FROM AUTHOR]

The first matrix cracking stress is a crucial indicator to appraise the mechanical properties of ceramic‐matrix composites, which is the starting point of permanent damage. Based on the classic energy balance method and stress intensity method, two temperature‐dependent first matrix cracking stress models of fiber‐reinforced ceramic matrix composites are established, respectively. The model established by the energy balance method considers the evolution of interfacial fracture energy with temperature, and the model established by the stress intensity method takes into account the evolution of stress intensity factor with temperature. The predictions of the above models in a wide temperature range are verified using experimental data available in the literature, which shows the rationality and accuracy of the above models. Moreover, on the basis of the energy balance method model, the main factors controlling the first matrix cracking stress at different temperatures are analyzed by the numbers. Finally, in view of the analysis results, some suggestions on how to optimize and enhance the first matrix cracking stress at different temperatures are put forward. [ABSTRACT FROM AUTHOR]

Short fiber/polymer composites (SFPCs) are increasingly applied in the field of high‐temperature structures. Its reliability at high temperatures has always been the core issue concerned by researchers. Here, utilizing the Force–Heat Equivalence Energy Density Principle, we developed a physically based model of temperature‐dependent ultimate tensile strength (TDUTS) for SFPCs. This model quantitatively considers the evolution of residual thermal stress, interface, fiber, and matrix performance as temperature increases. Meanwhile, the influence of fiber agglomeration frequently observed in composites and fiber orientation and length distribution is taken into account in the proposed model. The model predictions over a wide temperature range are validated against the experimental data available from the literature, indicating its reasonability and accuracy. The comparison with Kelly–Tyson model and Li's model is also performed. Additionally, the quantitative effects of the fiber agglomeration and interfacial shear strength on the TDUTS are discussed in detail. The present research not only provides an accurate and feasible approach to estimate the TDUTS of SFPCs, but also offers some helpful insights for the fabrication and design of such composites. [ABSTRACT FROM AUTHOR]

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In this study, a temperature‐dependent fracture strength model for whisker‐reinforced ceramic composites was developed. This model considers the strength degradation of both whisker and ceramic matrix at elevated temperatures, as well as the evolution of residual thermal stress with temperature. It was verified by comparison with the available flexural strengths of five types of whisker‐reinforced ceramic composites at different temperatures, and good agreement between the model predictions and the experimental data is obtained. Moreover, based on the established model, we systematically analyzed the effects of six influencing factors, including the volume fraction and the aspect ratio of whisker, the Young's modulus of matrix and whisker, the thermal expansion coefficient difference and the stress‐free temperature, on the temperature‐dependent flexural strengths of whisker‐reinforced ceramic composites. Some new insights which could help optimize and improve the temperature‐dependent fracture strength of whisker‐reinforced ceramic composites are obtained. [ABSTRACT FROM AUTHOR]

In banking and peer‐to‐peer loan applicant firms, customer credit scores have numerous applications in risk control and precision marketing. Numerous credit scoring techniques act as classification methods. In this paper, the main issue is simultaneous and hybrid utilization of the feature selection (FS) algorithm and ensemble learning classification algorithms with respect to their parameter settings to achieve higher performance in the proposed credit scoring model. As a result, this paper reports a hybrid data mining model of generalized fuzzy soft sets (GFSS) theory‐based ensemble learning classification algorithms based on three stages. The first stage addresses data gathering and preprocessing. The second stage uses the adaptive elastic net‐based FS algorithm to eliminate irrelevant or weakly correlated variables. After the appropriate variables are chosen, they are applied to the proposed ensemble model. In the third stage, GFSS theory is exploited to construct a novel weight assignment mechanism for each individual credit scoring model in the ensemble model according to performance. Several comparisons are conducted to validate the proposed model using real world credit datasets. The experimental results, analysis, and statistical tests prove the ability of the proposed approach to improve classification performance against all of the base classifier, hybrid, and combination methods in terms of average accuracy, area under the curve, H‐measure, and Brier score. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a temperature‐dependent model for predicting the tensile strength of 2D woven fiber reinforced ceramic matrix composites. The model takes into account the combined effects of temperature, temperature‐dependent residual thermal stress, temperature‐dependent matrix strength, and fibers strength on the tensile strength of composites. To verify the model, the tensile strengths of 2D woven fiber reinforced ceramic matrix composites available are predicted at different temperatures. The model predictions agree well with the experimental data. This work could provide a practical technical means for predicting the temperature‐dependent tensile strength of 2D woven fiber reinforced ceramic matrix composites and uncovering the dominated mechanisms leading to the change of tensile strength and their evolution with temperature. [ABSTRACT FROM AUTHOR]

A series of 4-anilino-6-phenylpyrimidines containing urea moiety were synthesized and the structures of all products were confirmed by 1H NMR, 13C NMR and HRMS. The antiproliferative activities of these compounds were evaluated against three human tumor cell lines (MGC-803, MCF-7 and EC-109) by applying the MTT assay method. compounds 4a, 4b and 6a showed the most effective activity, among which, 6a was more cytotoxic than 5-fluorouracil against all tested human cancer cell lines with IC50 values ranging from 1.80 to 2.72 µmol·L−1. [ABSTRACT FROM AUTHOR]