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In the network function virtualization environment, aiming at the load imbalance of network, a topology and resource-aware virtual network function migration method (TRA-VNFM) is proposed. Firstly, according to the computing, storage and forwarding resource occupancy of the underlying network, the two-level dynamic threshold is set to classify the overload degree of physical nodes, and at the same time, the corresponding migration judgment conditions are formulated and the set of destination nodes to be migrated is calculated. Among them, high-overload nodes have priority to implement migration and have lower migration success conditions. Secondly, for the virtual network function deployed on the overload node, the resource-aware algorithm is used to set its migration weight.The more overload resources the virtual network function occupies, the larger its migration weight, combining the migration weight and resource demand to select the virtual network function to be migrated. Finally, the topology-aware algorithm of extreme value interaction is used to evaluate the nodes in the migration destination node set, taking the node with the highest evaluation as the migration destination node by considering all kinds of resource occupancy, processing delay and topological properties. Simulation experiments show that compared with the previous virtual network function migration methods, this method not only reduces the migration time, but also has better performance in the average delay of the service function chain, the revenue to expense ratio of network and the degree of load balancing.

Combining metal–organic frameworks (MOFs) with other functional materials can effectively improve the third‐order nonlinear optical (NLO) performances of MOFs. In this study, two distinct functional materials are selected and a PANI@MIL‐101(Cr)@CeO2 composite is successfully synthesized. The test results of third‐order NLO indicate that introducing PANI regulates the distribution of π electron clouds within the structure of the composite. Additionally, the core@shell structure formed by PANI@MIL‐101(Cr) and CeO2 promotes charge transfer and improves charge transfer efficiency under the weak heterojunction interaction, thereby enhancing nonlinear absorption and refractive signals. Under the double synergistic action of interior and exterior, a new charge transfer occurs between the components of the composite, resulting in excellent third‐order NLO performances. This study indicates that encapsulating polymer and loading metal oxides can effectively improve the NLO response of MOFs, which offers a new idea for more research on multiphase NLO materials. [ABSTRACT FROM AUTHOR]

In view of problems of low reliability, poor moisture resistance and short service life existed in electronic sensor applied in steel wire rope tension measurement of mine hoist, a fiber grating sensor was designed. The sensor uses dual-gate structure, and adopts differential compensation method to eliminate impact of temperature; it uses grating detection device to detect center wavelength offsets of fiber grating, so as to calculate pressure of the sensor according to linear relationship between the center wavelength offsets and pressure, namely the tension of the steel wire rope. The experimental and test results verify reliability of the sensor.

Designing an effective photoactive heterojunction having dual benefits towards photoenergy conversion and pollutant adsorption is regarded as an affordable, green method for eliminating tetracycline (TC) from wastewater. In this regard, a series of BiOBr@NU-1000 (BNU-X, X = 1, 2 and 3) heterojunction photocatalysts are constructed. BNU-X preserves the original skeleton structure of the parent NU-1000, and its high porosity and specific surface area enable superior TC adsorption. At the same time, BNU-X is an effective Z-scheme photocatalyst that improves light trapping, promotes photoelectron–hole separation, and shows excellent photocatalytic degradation efficiency towards TC with the value of the photodegradation kinetic rate constant k being 2.2 and 24.8 times those of NU-1000 and BiOBr, respectively. The significant increase in the photocatalytic activity is ascribed to the construction of an efficient Z-scheme photocatalyst, which promotes the formation of superoxide radicals (˙O2−) and singlet oxygen (1O2) as the main oxidative species in the oxidation system. This research has the advantage of possibilities for the development of porous Z-scheme photocatalysts based on photoactive MOF materials and inorganic semiconductors for the self-purification and photodegradation of organic contaminants. [ABSTRACT FROM AUTHOR]

The operation and management mode of “Internet+ Logistics Park” ecosphere has long-term and stable core competitiveness. This paper studies how to obtain the corresponding economic benefits from the perspective of the operators of the logistics park. The logistics park chooses the appropriate logistics service and the public service function to obtain the corresponding economic benefit. The development of the logistics park will finally be implemented to the profit of the park. The paper puts forward the profit model of “Internet+ Logistics Park” ecosphere; This paper mainly analyzes five modes: logistics integration mode, platform operation mode, resource integration mode, service delivery mode and chain replication mode; This paper makes a comparative analysis of different profit models from the aspects of model characteristics and profit thinking.

Since the State Council issued the “Plan for the Adjustment and Revitalization of the Logistics Industry” in 2009, the logistics industry, as the basic and strategic industry in the development of the national economy, has played an increasingly important role in promoting industrial transformation and upgrading and promoting economic development. In order to promote the development of logistics industry, a large number of logistics parks have been built all over the country under the guidance of policies and the promotion of the market. However, after the construction of these logistics parks has been put into operation, There are a series of problems in its development and profit. This paper analyzes the present situation and profit of logistics park in China, and briefly analyzes the main business characteristics of freight hub, production service, port service, trade service and comprehensive service. On this basis, the main problems existing in the existing profit model of logistics park in China are summarized.

Herein, a series of crystalline Z-scheme photocatalytic heterojunctions BiOI@PCN-222 (BP-X, X donates Zr6 : Bi, X = 1, 3 and 5) are constructed by highly dispersed integration of BiOI into the channel of a porphyrin-based Zr-MOF PCN-222 through surface site engineering. BP-X exhibits stronger visible light absorption (400–800 nm) than that of PCN-222, while retaining the mesoporous nature with a surface area of ∼650 m2 g−1 and large pore volume ∼15 Å in diameter. A set of characterization measurements reveal the formation of an internal interface electric field in the composite and the electron transfer from BiOI to PCN-222. In addition, their photocatalytic activity toward the degradation of tetracycline (TC) under visible light irradiation is investigated to illustrate the advantages of self-decontaminating photocatalysts capable of both adsorption and photodegradation. BP-X shows superior TC adsorption and photodegradation activity. Specially, the photodegradation kinetic rate constant k of BP-3 is 1.5 and 10 times higher than that of PCN-222 and BiOI, respectively. The improved photocatalytic performance of BP-3 is attributed to its strong TC adsorption capacity and highly dispersed Z-scheme heterojunction, which is beneficial to photogenerated charge separation and electron transfer. This work explored the opportunities to develop heterojunction mesoporous materials based on MOFs for self-purification and photodegradation of organic pollutants. [ABSTRACT FROM AUTHOR]

The performance of the neighborhood rough set model in feature selection is limited by nonobjective parameter selection method, the uncertainty measures considered only from a single view, and high time cost caused by processing high‐dimensional data. To solve the above problems, this study first defines the interclass boundary to granulate the samples in different classes, and three types of neighborhood concepts—negative perspective, neutral perspective, and positive perspective—are put forward based on different cognitive perspectives. Then, the concept of the multiperspective rough set model is developed. The most prominent feature of this model is the discovery of differences between classes from the given data, without any parameters. Second, by integrating the information theory and algebraic views under the multiperspective rough set model, multiview entropy measures are proposed to effectively measure the uncertainty in data. Moreover, a nonmonotonic feature selection algorithm based on the mutual information in the multiview entropy measures under the neutral perspective as the evaluation function of feature importance is designed to resolve the disadvantages of the algorithms based on the monotone evaluation function. Finally, Information Gain is introduced to preliminarily decrease the dimension of high‐dimensional data sets to promote classification accuracy and reduce time consumption. The experimental results confirm that the proposed algorithm is efficient in eliminating noise and increasing classification accuracy. [ABSTRACT FROM AUTHOR]

The rapid growth of digital information has produced massive amounts of time series data on rich features and most time series data are noisy and contain some outlier samples, which leads to a decline in the clustering effect. To efficiently discover the hidden statistical information about the data, a fast weighted fuzzy C-medoids clustering algorithm based on P-splines (PS-WFCMdd) is proposed for time series datasets in this study. Specifically, the P-spline method is used to fit the functional data related to the original time series data, and the obtained smooth-fitting data is used as the input of the clustering algorithm to enhance the ability to process the data set during the clustering process. Then, we define a new weighted method to further avoid the influence of outlier sample points in the weighted fuzzy C-medoids clustering process, to improve the robustness of our algorithm. We propose using the third version of mueen's algorithm for similarity search (MASS 3) to measure the similarity between time series quickly and accurately, to further improve the clustering efficiency. Our new algorithm is compared with several other time series clustering algorithms, and the performance of the algorithm is evaluated experimentally on different types of time series examples. The experimental results show that our new method can speed up data processing and the comprehensive performance of each clustering evaluation index are relatively good. [ABSTRACT FROM AUTHOR]