•Propose a novel deep convolutional neural network-based method for remaining useful life predictions.•No prior expertise on prognostics and signal processing is required, that facilitates the ...application of the proposed method.•Effects of the key factors on the prognostic performance are widely investigated and the model parameters are optimized.•Experiments on a popular aero-engine degradation dataset (C-MAPSS) and comparisons with the related state-of-the-art results validate the effectiveness and superiority of the proposed method.
Traditionally, system prognostics and health management (PHM) depends on sufficient prior knowledge of critical components degradation process in order to predict the remaining useful life (RUL). However, the accurate physical or expert models are not available in most cases. This paper proposes a new data-driven approach for prognostics using deep convolution neural networks (DCNN). Time window approach is employed for sample preparation in order for better feature extraction by DCNN. Raw collected data with normalization are directly used as inputs to the proposed network, and no prior expertise on prognostics and signal processing is required, that facilitates the application of the proposed method. In order to show the effectiveness of the proposed approach, experiments on the popular C-MAPSS dataset for aero-engine unit prognostics are carried out. High prognostic accuracy on the RUL estimation is achieved. The superiority of the proposed method is demonstrated by comparisons with other popular approaches and the state-of-the-art results on the same dataset. The results of this study suggest that the proposed data-driven prognostic method offers a new and promising approach.
Intelligent machinery fault diagnosis system has been receiving increasing attention recently due to the potential large benefits of maintenance cost reduction, enhanced operation safety and ...reliability. This paper proposes a novel deep learning method for rotating machinery fault diagnosis. Since accurately labeled data are usually difficult to obtain in real industries, data augmentation techniques are proposed to artificially create additional valid samples for model training, and the proposed method manages to achieve high diagnosis accuracy with small original training dataset. Two augmentation methods are investigated including sample-based and dataset-based methods, and five augmentation techniques are considered in general, i.e. additional Gaussian noise, masking noise, signal translation, amplitude shifting and time stretching. The effectiveness of the proposed method is validated by carrying out experiments on two popular rolling bearing datasets. Fairly high diagnosis accuracy up to 99.9% can be obtained using limited training data. By comparing with the latest advanced researches on the same datasets, the superiority of the proposed method is demonstrated. Furthermore, the diagnostic performance of the deep neural network is extensively evaluated with respect to data augmentation strength, network depth and so forth. The results of this study suggest that the proposed intelligent fault diagnosis method offers a new and promising approach.
This paper proposes a multiobjective optimization method for signal control design at intersections in urban traffic network. The cell transmission model is employed for macroscopic simulation of the ...traffic. Additional rules are introduced to model different route choices from origins to destinations. Vehicle turning, merging, and diverging behaviors at intersections are considered. A multiobjective optimization problem (MOP) is formulated considering four measures in network traffic performance, i.e., maximizing system throughputs, minimizing traveling delays, enhancing traffic safety, and avoiding spillovers. The design parameters for an intersection include turning signal type, cycle time, signal offset, and green time in each phase. The resulting high-dimensional MOP is solved with the genetic algorithm (GA). An algorithm is proposed to assist the user to select and implement the optimal designs from the Pareto optimal solution set. A case study in a grid network of nine intersections is carried out to test the optimization algorithm. It is observed that the proposed method is able to achieve the optimal network performance with different traffic demands. The convergence and coefficient selection of GA are discussed. The guidelines for network signal design and operation from the current studies are presented.
Molybdenum disulfide (MoS2) is a promising alternative hydrogen evolution reaction (HER) catalyst to high-cost platinum (Pt) due to its large surface area, low cost, easy preparation, and earth ...abundance. The HER efficiency of MoS2 remains low because only the edge S-sites are active for the HER. In this work, two practical strategies, heteroatom doping (Rh, Pd, and Ag) and strain engineering, are proposed to activate the inert in-plane S-site for the HER. The density functional theory calculations demonstrate that doping MoS2 with heteroatom can trigger the HER activity of the S atoms next to the doping atoms, with a negative hydrogen adsorption free energy (ΔG H* 0). The negative ΔG H* 0 can be further significantly optimized by a small compressive strain. Therefore, the combination of heteroatom doping and a small compressive strain can yield an ideal value of hydrogen-binding free energy (ΔG H* 0 = 0 eV) for HER. These results highlight an innovative avenue to optimize the HER performance of MoS2.
In the light of the recent potentials of deuterated molecules as pharmaceuticals or even in mechanistic understanding, efficient methods for their synthesis are continually desired. CD3-containing ...molecules are prominent amongst these motifs due to the parallel of the “magic methyl effect”: introducing a methyl group into pharmaceuticals could positively affect biological activities. The trideuteromethyl group is bound to molecules either by C, N, O, or S atom. For a long time, the preparation methods of such labeled compounds were underestimated and involved multi-step syntheses. More recently, specific approaches dealing with the direct incorporation of the CD3 group have been developed. This Review gives an overview of the methods for the preparation of CD3-labeled molecules from conventional functional group interconversion techniques to catalytic approaches and include radical strategy. Detailed reaction mechanisms are also discussed.
California is the world's biggest producer and exporter of almonds. Currently, the sweeping of almonds during the harvest creates a significant amount of dust, causing air pollution in the ...neighboring urban areas. A low-dust sweeping system was designed to reduce the dust during the sweeping of almonds in the orchard. The system includes a feedback control system to control the sweeper brushes' height and their angular velocity by adjusting the forward velocity of the harvester and the brushes' rotational speeds to avoid any extra overlapping sweeping, which increases dust generation. The governing kinematic equations for sweepers' angular velocity and vehicle forward speed were derived. The feedback controllers for synchronizing these speeds were designed to optimize brush/dust contact to minimize dust generation. The sweepers' height controller was also designed to stabilize the gap between the brushes and the orchard floor and track the road trajectory. Controllers were simulated and tuned for a fast response for agricultural applications with less than a second response delay. Results showed that the designed system has acceptable performance and generates low amounts of dust within the acceptable range of California ambient air quality standards.
A novel high-nuclearity silver sulfide nanocluster Ag
50
S
7
(SC
6
H
4
F)
36
(dppp)
6
·4DMI, (hereafter abbreviated as
1⋅4DMI
) was synthesised. Solvent-free crystals of 1 displayed a completely ...reversible narrowing and broadening of the optical band gap that was accompanied by visual thermochromism and piezochromism changeovers, when stimulated by varying temperatures between 113 and 413 K or by changing the pressure from 1 atm to 7.5 GPa.
A novel high-nuclearity silver chalcogenolate nanocluster Ag
50
S
7
(SPhF)
36
(dppp)
6
have been obtained, which shows reversible color changes in response to temperature and pressure.
Ultrasmall PEGylated Cu2–xSe nanoparticles with strong near‐infrared absorption have been prepared by an ambient aqueous method. The resultant water‐soluble and biocompatible nanoparticles are ...demonstrated to be a novel nanotheranostic agent for effective deep‐tissue photoacoustic imaging, computed tomography imaging, single‐photon emission computed tomography imaging, and photothermal therapy of cancer.
Squamous cell carcinomas (SCCs) are aggressive malignancies. Previous report demonstrated that master transcription factors (TFs) TP63 and SOX2 exhibited overlapping genomic occupancy in SCCs. ...However, functional consequence of their frequent co-localization at super-enhancers remains incompletely understood. Here, epigenomic profilings of different types of SCCs reveal that TP63 and SOX2 cooperatively and lineage-specifically regulate long non-coding RNA (lncRNA) CCAT1 expression, through activation of its super-enhancers and promoter. Silencing of CCAT1 substantially reduces cellular growth both in vitro and in vivo, phenotyping the effect of inhibiting either TP63 or SOX2. ChIRP analysis shows that CCAT1 forms a complex with TP63 and SOX2, which regulates EGFR expression by binding to the super-enhancers of EGFR, thereby activating both MEK/ERK1/2 and PI3K/AKT signaling pathways. These results together identify a SCC-specific DNA/RNA/protein complex which activates TP63/SOX2-CCAT1-EGFR cascade and promotes SCC tumorigenesis, advancing our understanding of transcription dysregulation in cancer biology mediated by master TFs and super-enhancers.
•O2O development strategies are adopted to sustain WEEE collection business in China.•Three typical cases of O2O WEEE collection are analyzed using Business Model Canvas.•O2O model develops proper ...systems and channels to support the three flows.•Mechanisms of participation, cooperation and profit are built in O2O model.•O2O model reduces transaction costs, expands collection scope and scale, and is eco-friendlier.
WEEE has become a global focus because of its environmental pollution and human health risk and the valuable resources contained. China’s ban on solid waste imports reconstructs the global WEEE flow, leading to a more complicated situation for global WEEE recycling that asks for innovative development. The advanced development of the Internet opens new doors to WEEE collection-the first step of recycling, O2O (integrating online platform and offline collection) development strategies are adopted by many companies in China. The exploration of the new model and experiences of WEEE collection in China can provide lessons for other countries. In this study, we decode the business model of three typical cases in China using Business Model Canvas, and discuss and summarize the types, structure characteristics, operating mechanisms and effects of O2O WEEE collection model. The results show that: there are three typical types of O2O WEEE collection model in China, first one derived from internet corporate, second one derived from recycling corporate and third one served as a third-party platform. To ensure the fluency and sustaining of information flow, material flow, and fund flow, O2O WEEE collection model builds information support platforms with user-friendly interfaces, various distribution channels, and accurate pricing systems. To operate the business smoothly, attractive participation mechanism, cooperation mechanism, and multi-level profit mechanism have been constructed. The O2O WEEE collection model enjoys popularity in the capital market and customers for reducing the transaction costs, expanding the collection scope and scale and contributing to efficient and effective WEEE recycling.
PDF
