Abstract
Turnout system is very important in the safety of railway system. However, the traditional maintenance method of turnouts is mainly based on human experience and basic intelligent model. ...Aiming at the problems existing in the current intelligent fault diagnosis method of turnout equipment, this paper uses the improved group decision-making method to dynamically and iteratively adjust and optimize the authority of each decision-making expert in the group decision-making method, so as to improve the prediction ability of the existing model, reduce the number of cases of prediction errors and further improve the safety of the turnout system.
This paper investigates the automatic exploration problem under the unknown environment, which is the key point of applying the robotic system to some social tasks. The solution to this problem via ...stacking decision rules is impossible to cover various environments and sensor properties. Learning-based control methods are adaptive for these scenarios. However, these methods are damaged by low learning efficiency and awkward transferability from simulation to reality. In this paper, we construct a general exploration framework via decomposing the exploration process into the decision, planning, and mapping modules, which increases the modularity of the robotic system. Based on this framework, we propose a deep reinforcement learning-based decision algorithm that uses a deep neural network to learning exploration strategy from the partial map. The results show that this proposed algorithm has better learning efficiency and adaptability for unknown environments. In addition, we conduct the experiments on the physical robot, and the results suggest that the learned policy can be well transferred from simulation to the real robot.
With the development of globalization, distributed manufacturing has become one of the main modes of manufacturing. The situation in which a number of heterogeneous factories coproduce a batch of ...jobs is ubiquitous in the field of distributed manufacturing. Compared with isomorphic factories, heterogeneous factories bring further difficulty in assigning jobs to factories. This paper considers the heterogeneity between factories in distributed flow-shop scheduling for the first time. This paper addresses a distributed heterogeneous no-wait flowshop scheduling problem (DHNWFSP) to minimize the makespan, where the factories have differences among them, including the number of machines, machine technology, raw material supply, and transportation conditions. In this problem, the numbers and types of machines in each factory are different, and this means that the jobs have to be processed through different processing paths. To effectively solve this DHNWFSP, a discrete artificial bee colony algorithm (DABC) is proposed. Firstly, to obtain a feasible neighborhood solution, four neighborhood search operators based on the characteristics of this problem are presented to search neighborhoods during the employed bee phase and onlooker bee phase. Then, a new method to accelerate the evaluation of the obtained neighborhood is proposed to reduce the computation time. Moreover, an efficient population update method is designed in the onlooker bee phase. Finally, a variable neighborhood descent (VND) algorithm based on four local-search methods is embedded into the scout bee phase to strengthen the local search ability of the overall algorithm. To validate the performance of the proposed algorithm, a series of numerical experiments are executed for small- and large-scale problems to compare the DABC with some state-of-art algorithms in terms of solving the DHNWFSP. The results show that the proposed DABC obtains the highest-quality solutions.
•Distributed heterogeneous no-wait flowshop scheduling problem is studied first.•A speed-up method of neighborhood evaluation is proposed in DHNWFSP.•A discrete artificial bee colony algorithm is Designed for DHNWFSP.
Cervical cancer is one of the most common cancers in women worldwide. The outcome of patients with metastatic cervical cancer is poor. We reviewed the relevant literature concerning the treatment and ...diagnosis of metastatic cervical cancer. There are two types of metastasis related to different treatments and survival rates: hematogenous metastasis and lymphatic metastasis. Patients with hematogenous metastasis have a higher risk of death than those with lymphatic metastasis. In terms of diagnosis, fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) and PET-computed tomography are effective tools for the evaluation of distant metastasis. Concurrent chemoradiotherapy and subsequent chemotherapy are well-tolerated and efficient for lymphatic metastasis. As for lung metastasis, chemotherapy and/or surgery are valuable treatments for resistant, recurrent metastatic cervical cancer and chemoradiotherapy may be the optimal choice for stage IVB cervical cancer. Chemotherapy and bone irradiation are promising for bone metastasis. A better survival is achieved with multimodal therapy. Craniotomy or stereotactic radiosurgery is an optimal choice combined with radiotherapy for solitary brain metastases. Chemotherapy and palliative brain radiation may be considered for multiple brain metastases and other organ metastases.
Cyclohexanone is an important intermediate in the manufacture of polyamides in chemical industry, but direct selective hydrogenation of phenol to cyclohexanone under mild conditions is a challenge. ...We report here a catalyst made of Pd nanoparticles supported on a mesoporous graphitic carbon nitride, Pd@mpg-C3N4, which was shown to be highly active and promoted the selective formation of cyclohexanone under atmospheric pressure of hydrogen in aqueous media without additives. Conversion of 99% and a selectivity higher than 99% were achieved within 2 h at 65 °C. The reaction can be accelerated at higher temperature, but even at room temperature, 99% conversion and 96% selectivity could still be obtained. The generality of the Pd@mpg-C3N4 catalyst for this reaction was demonstrated by selective hydrogenation of other hydroxylated aromatic compounds with similar performance.
In recent years, 2D materials and their heterostructures have started to offer an ideal platform for high-performance photodetection devices. In this work, a highly responsive, self-powered ...photodetector based on PtSe2/MoS2 van der Waals heterostructure is demonstrated. The device achieves a noteworthy wide band spectral response from visible (405 nm) range to the near infrared region (980 nm). The remarkable photoresponsivity and external quantum efficiency up to 4.52 A/W, and 1880% are achieved, respectively, at 405 nm illumination with fast response time of 20 ms. In addition, the photodetector exhibits a decent photoresponsivity of 33.4 mA/W at zero bias, revealing the photodetector works well in the self-driven mode. Our work suggests that a PtSe2/MoS2 heterostructure could be a potential candidate for the high-performance photodetection applications.
Radical involved transformations are now considered as extremely important processes in modern organic synthetic chemistry. According to the demand by atom-economic and sustainable chemistry, direct ...C(sp(3))-H functionalization through radical oxidative coupling represents an appealing strategy for C-C bond formations. However, the selectivity control of reactive radical intermediates is still a great challenge in these transformations. Here we show a selective radical oxidative C(sp(3))-H/C(sp)-H cross-coupling of unactivated alkanes with terminal alkynes by using a combined Cu/Ni/Ag catalytic system. It provides a new way to access substituted alkynes from readily available materials. Preliminary mechanistic studies suggest that this reaction proceeds through a radical process and the C(sp(3))-H bond cleavage is the rate-limiting step. This study may have significant implications for controlling selective C-C bond formation of reactive radical intermediates by using multimetallic catalytic systems.
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•The common preparation methods of 2D and mixed-dimensional heterostructures are summarized.•The design, working principles and performance of 2D/nD (n = 0, 1, 2, 3) mid-infrared ...photodetectors are reviewed.•The advantages of 2D and mixed-dimensional heterostructures for mid-infrared photodetection devices are discussed.•The future prospects of 2D/nD heterostructures towards high performance mid-infrared photodetectors are provided.
Mid-infrared (MIR) photodetection plays an important role in a variety of modern technologies, such as biomedical devices, free-space communication and security. In the past decade, 2D materials and heterostructures have been widely utilized in MIR photodetectors because of the tunable bandgaps, high carrier mobility and strong light absorption. Apart from 2D/2D heterostructures, 2D material can also form mixed-dimensional heterostructures with other dimensional materials thanks to the interlayer van der Waals forces, which presents a much broader group and greatly expands the research of MIR photodetectors due to the synergistic advantages. In this review, the recent progress of MIR photodetectors based on van der Waals (vdWs) heterostructures, including all-2D and mixed-dimensional heterostructures is systematically summarized. First, the common synthesis strategies to realize vdWs heterostructures are presented. Then, the motivation, device design, mechanism and performance of MIR photodetectors are presented and discussed in classification of various kinds of vdWs heterostructures. Finally, the current challenges and some future prospects in this research field are suggested.
Beefed up with B,F: A boron‐ and fluorine‐enriched carbon nitride polymeric semiconductor was synthesized by a facile one‐step process using 1‐butyl‐3‐methylimidazolium tetrafluoroborate as a soft ...template. The resulting materials show an advantageous “morel‐like” mesopore structure (see picture) with narrow pore size distribution and good photoactivity under visible light. The materials are also good catalysts for the selective oxidation of cyclohexane.
•Optimal combination of spectrum transformation and model were selected for different heavy metal.•Results showed that the accuracy of RF was higher than that of SVM and PLS.•This study can provide ...technical support for the nondestructive monitoring of soil heavy metal content.
Hyperspectral remote sensing technology has considerable research value in monitoring and evaluating soil heavy metal pollution. In this study, the Three-River Source Region was taken as the study area. The occurrence relationship of six heavy metals in soil, such as Mn, Cu, Zn, Pb, Cr, Ni, with soil organic matter, clay minerals, and iron-manganese oxides, was studied through the determination and analysis of soil samples and the collection of soil reflectance spectrum. Spectral transformation was carried out by first derivative, second derivative, inverse-log, continuum removal and multiple scattering correction of the spectrum. The correlation between soil heavy metal content and soil spectrum was analyzed to select the characteristic band, and partial least squares (PLS) method, support vector machine (SVM) method and random forest (RF) model were used to build inversion model based on characteristic band. Then the best combination of spectral transformation and inversion model were explored. The results showed that Pb contents were the twice of the background in Qinghai province. The combination spectrum processing method can improve the correlation between spectrum and heavy metals. The location and quantity of characteristic bands of six heavy metals are different. The accuracy of RF was significantly better than that of SVM and PLS for all six heavy metal (i.e. pb: R2RF = 0.83, R2SVM = 0.62, R2PLS = 0.18), and the model effective of soil properties in non-polluted sites were reliable (i.e. clay: R2RF = 0.93, R2SVM = 0.87, R2PLS = 0.74). This study can provide technical support for the larger-scale monitoring of soil heavy metal content and heavy metal pollution assessment.
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