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Since traditional matrix factorization algorithms are mostly based on shallow linear models,it is difficult to learn latent factors of users and items at a deep level.When the dataset is sparse,it is inclined to overfitting.To deal with the problem,this paper proposes a biased deep distance factorization algorithm,which can not only solve the data sparse problem,but also learn the distance feature vectors with stronger characterization capabilities.Firstly,the interaction matrix is constructed through the explicit and implicit data of the user and the item.Then the interaction matrix is converted into the corresponding distance matrix.Secondly,the distance matrix is input into the depth of the bias layer by row and column respectively.The neural network learns the distance feature vectors of users and items with non-linear features.Finally,the distance between the user and the item is calculated according to the distance feature vectors.Top-N item recommended list is generated according to the distance value.The experimental results show that Precision,Recall,MAP,MRR and NDCG of this algorithm are significantly improved compared to other mainstream recommendation algorithms on four different datasets.

The previously proposed short comparable encryption (SCE) scheme can infer the plaintext relationship by comparing the ciphertexts relationship as well as ensuring data security in Internet of things.Unfortunately,it will incur high storage and computational burden during the process of comparing ciphertexts and generating tokens.To this end,an efficient short comparable encryption scheme called SCESW was proposed,which was utilizing the sliding window method with the same size window.Formal security analysis shows that the scheme can guarantee weak indistinguishability in standard model as well as data security and integrity.The experimental results demonstrate that the storage of the SCESW scheme is 1 t (t＞1) times shorter than that of the SCE scheme and the efficiency of the SCESW scheme is superior to that of the SCE scheme.

When a VM migrates among hosts residing in two IP subnets,the network attachment point of VM changed,which causes the IP mobility problem.It was meaningful to design and evaluate VM migration performance under the future internet architecture.XIA (expressive Internet architecture)was focused,a novel future internet architecture,sup-port for VM live migration.Motivated by the natural f res of ID/location decoupling,versatile routing with DAG (di-rected acyclic graphs) in XIA,The design and implementation of rendezvous agent based migration (RABM) approach was given.In demonstrate that XIA supported VM migration can achieve fast network re-connection between VM and correspondent node,while keeping the network control plane simplicity and data plane efficiency.

Hydroponic cultures were conducted to investigate the difference of cadmium (Cd) on tolerance and response to abscisic acid (ABA) between two varieties of Nicotiana tabacum, 'MS yunyan87' and 'MSK326'. A significant decrease in the dry weight, net photosynthetic rate, stomatal conductance, intercellular CO2 concentration and transpiration rate was found in two varieties of N.tabacum. The dry weight of 'MSK326' was higher than that of 'MS yunyan87' when exposed to 50 μmol·L-1 Cd. With the same treatment, net photosynthetic rate, stomatal conductance, intercellular CO2 concentration and Cd accumulation in shoots of 'MSK326' were higher than those of 'MS yunyan87'. The Cd concentration in shoots and roots of two varieties of N. tabacum increased with the increasing Cd treatment concentration. In all treatments, Cd concentrations were higher in the roots than those in the shoots. In the presence of 50 μmol·L-1 CdCl2, exogenous ABA treatment increased the Cd concentration in roots and reduced Cd concentration in shoots. The transport of Cd from root to the shoots was also inhibited. The percentage of shoot/total Cd content showed a significant correlation between the transpiration rate. [ABSTRACT FROM AUTHOR]

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Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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This paper studies the influence of government poverty alleviation policy and altruistic preference on supply chain decision-making in a supply chain consisting of one supplier and two manufacturers. The two manufacturers produce poverty alleviation products and non-poverty alleviation products (general products) respectively, which are competing in the same market, and the manufacturer who produces poverty alleviation products chooses a level of investment and receives government subsidies. The dynamic game model is established to analyze the influence of government subsidy rate, supplier altruistic preference and market share of poverty alleviation products on supply chain decision-making. Through numerical analysis, the effectiveness of supply chain in poverty alleviation is analyzed from the perspective of absolute poverty and relative poverty. The results show that enhancing these three factors (government subsidy rate, supplier altruistic preference and market share of poverty alleviation products) can effectively improve the level of poverty alleviation investment, the output of poverty alleviation products, the market price and the profit of poverty alleviation product manufacturers, however the profit of general product manufacturers is decreased. The market share of poverty alleviation products and the intensity of competition between these two products are key factors which are influencing the effect of poverty alleviation. Increasing the market share of government subsidies or poverty-relief products can effectively increase the profit of suppliers and the overall profit of supply chain, which provides a foundation for supply chain members to realize Pareto improvement. The conclusion provides theoretical reference for the stabilization and marketization of poverty-relief products. [ABSTRACT FROM AUTHOR]

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Copyright of Chinese Journal of Preventive Veterinary Medicine / Zhongguo Yufang Shouyi Xuebao is the property of Chinese Journal of Preventive Veterinary Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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In order to understand the emissions of VOCs component characteristics from a large mechanical coking production process, based on the field survey of two typical coking plants in a coking concentrating zone in north China, VOCs sampling was taken at waste gas discharge outlet of coking production facilities, main production facilities unit (unorganized emissions units), and the coking production clusters (regional environment), and the samples were analyzed by using GC/MS analysis. Results indicated that 55 VOCs components were detected at the exhaust outlets of the coking production facilities, including six types such as MACHs, OVOCs, PAHs, alkanes, alkenes and halogenated hydrocarbons, with naphthalene, nines, benzene, toluene and several isomers of xylene and trimethylbenzene as the main components. A total of 27 VOCs components, including MACHs, OVOCs, PAHs and olefin, were detected in the vicinity of the main production units in the plant, with the main components consistent with the organized emission sources. A total of 21 VOCs components, mainly MACHs and PAHs, were detected in the environment of coking production concentration area, with benzene and toluene as the main components. Naphthalene, ninhydrin, benzene, toluene, xylene, toluene, methyl naphthalene are main characteristics pollutants of coking industry. [ABSTRACT FROM AUTHOR]

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Copyright of Progress in Modern Biomedicine is the property of Publishing House of Progress in Modern Biomedicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)