Maximizing the residual value of retired products and reducing process consumption and resource waste are vital for Generalized Growth-oriented Remanufacturing Services (GGRMS). Under the GGRMS, the traditional product-oriented remanufacturing methods need to be changed: the products in GGRMS should be divided into multiple parts and different parts are treated in different ways to maximize residual value. However, this significantly increases the number of remanufacturing service activities and the complexity of the service activities network. Because a service activity may correspond to multiple service resources, the difficulty of service resources allocating significantly increase as the number of service activities under GGRMS increases. To improve the efficiency of resource matching, we proposed to first merge the redundant service activities in the service activity network, and then allocate the corresponding service resources. Therefore, we first used rough-fuzzy number and structural entropy weighting method to perform a coupling analysis on all service activities in the generalized growth scheme set and to merge redundant service activities. We then considered the interests of both the service providers and integrators and added flexible impact factors to establish a service resource optimization configuration model, and solved it with the Non-Dominated Sorting Genetic Algorithm (NSGA-Ⅱ). Finally, we, taking a retired manual gearbox as an experiment, optimized the service resource allocation for its generalized growth scheme set. The experimental results shown that the overall matching efficiency was increased by 74.56% after merging redundant service activities, showing that the proposed method is effective for the resource allocation of the generalized growth for complex single mechanical products, and can offer guidelines to the development of the RMS.

In real-world search, recommendation, and advertising systems, the multi-stage ranking architecture is commonly adopted. Such architecture usually consists of matching, pre-ranking, ranking, and re-ranking stages. In the pre-ranking stage, vector-product based models with representation-focused architecture are commonly adopted to account for system efficiency. However, it brings a significant loss to the effectiveness of the system. In this paper, a novel pre-ranking approach is proposed which supports complicated models with interaction-focused architecture. It achieves a better tradeoff between effectiveness and efficiency by utilizing the proposed learnable Feature Selection method based on feature Complexity and variational Dropout (FSCD). Evaluations in a realworld e-commerce sponsored search system for a search engine demonstrate that utilizing the proposed pre-ranking, the effectiveness of the system is significantly improved. Moreover, compared to the systems with conventional pre-ranking models, an identical amount of computational resource is consumed. CCS CONCEPTS• Information systems → Learning to rank.

High-resolution (HR) satellite images, due to the technical constraints on spectral and spatial resolutions, usually contain only several broad spectral bands but with a very high spatial resolution. This provides rich spatial details of the objects on the Earth surface, while their spectral discrimination is relatively low. Recently, the increase of the satellite revisit times made it possible to acquire more frequent data coverage for finer classification. In this paper, we proposed a novel multitemporal deep fusion network (MDFN) for short-term multitemporal HR images classification. Specifically, a two-branch structure of MDFN is designed, which includes a long short-term memory (LSTM) and a convolutional neural network (CNN). The LSTM branch is mainly used to learn the joint expression of different temporal-spectral features. For the CNN branch, the 3D convolution is firstly applied along the temporal and spectral dimensions to jointly learn the temporal-spatial and spectral-spatial information, respectively, and then the 2D convolution is performed along the spatial dimension to further extract the spatial context information. Finally, features generated from the two different branches are fused to obtain the discriminative high-level semantic information for classification. Experimental results carried on two real multitemporal HR remote sensing data sets demonstrate that the proposed MDFN provides better classification performance over the state-of-the-art methods, and it also shows the potentiality to use short-term multitemporal HR images for more accurate Land Use/Land Cover (LULC) mapping.

Background: Aberrant expression of microRNAs (miRNAs) has been associated with the pathogenesis of pulmonary hypertension (PH). It is, however, not clear whether miRNAs are involved in estrogen rescue of PH.Methods: Fresh plasma samples were prepared from 12 idiopathic pulmonary arterial hypertension (IPAH) patients and 12 healthy controls undergoing right heart catheterization in Shanghai Pulmonary Hospital. From each sample, 5 μg of total RNA was tagged and hybridized on microRNA microarray chips. Monocrotaline-induced PH (MCT-PH) male rats were treated with 17β-estradiol (E 2 ) or vehicle. Subgroups were cotreated with estrogen receptor (ER) antagonist or with antagonist of miRNA.Results: Many circulating miRNAs, including miR-21-5p and miR-574-5p, were markedly expressed in patients and of interest in predicting mean pulmonary arterial pressure elevation in patients. The expression of miR-21-5p in the lungs was significantly upregulated in MCT-PH rats compared with the controls. However, miR-574-5p showed no difference in the lungs of MCT-PH rats and controls. miR-21-5p was selected for further analysis in rats as E 2 strongly regulated it. E 2 decreased miR-21-5p expression in the lungs of MCT-PH rats by ERβ. E 2 reversed miR-21-5p target gene FilGAP downregulation in the lungs of MCT-PH rats. The abnormal expression of RhoA, ROCK2, Rac1 and c-Jun in the lungs of MCT-PH rats was inhibited by E 2 and miR-21-5p antagonist.Conclusions: miR-21-5p level was remarkably associated with PH severity in patients.Moreover, the miR-21-5p/FilGAP signaling pathway modulated the protective effect of E 2 on MCT-PH through ERβ.

No abstract

No abstract

No abstract

No abstract