ALBERT

Description: This paper proposes a novel seven-level power topology, that increases the number of output levels by using fewer power switches and capacitors compared to the traditional seven-level topology. Moreover, the working mechanism of the proposed topology and its implementation method are given. Furthermore, a two-stage capacitor-voltage equalization control strategy with overall control and independent control is proposed. Finally, the proposed topology is applied to the active power filter system, and simulations and experimental research of two types of working conditions are performed. The results verify the effectiveness and feasibility of the new topology and control strategy.

Description: The biotite pegmatites in the Shangdan domain of the North Qinling orogenic belt contain economic concentrations of U, constituting a low-grade, large-tonnage pegmatite-hosted uraniferous province. Uraninite is predominant and ubiquitous ore mineral and coffinite is common alteration mineral after initial deposit formation. A comprehensive survey of the uraninite and coffinite assemblage of the Chenjiazhuang, Xiaohuacha, and Guangshigou biotite pegmatites in this uraniferous province reveal the primary magmatic U mineralization and its response during subsequent hydrothermal events. Integrating the ID-TIMS (Isotope Dilution Thermal Ionization Mass Spectrometry) 206Pb/238U ages and U-Th-Pb chemical ages for the uraninites with those reported from previous studies suggests that the timing of U mineralization in the uraniferous province was constrained at 407–415 Ma, confirming an Early Devonian magmatic ore-forming event. Based on microtextural relationships and compositional variation, three generations of uranium minerals can be identified: uaninite-A (high Th-low U-variable Y group), uranite-B (low Th-high U, Y group), and coffinite (high Si, Ca-low U, Pb group). Petrographic and microanalytical observations support a three-stage evolution model of uranium minerals from primary to subsequent generations as follows: (1) during the Early Devonian (stage 1), U derived from the hydrous silicate melt was mainly concentrated in primary magmatic uaninite-A by high-T (450–607 °C) precipitation; (2) during the Late Devonian (stage 2), U was mobilized and dissolved from pre-existing uraninite-A by U-bearing fluids and in situ reprecipitated as uraninite-B under reduced conditions. The in situ transformation of primary uraninite-A to second uraninite-B represent a local medium-T (250–450 °C) hydrothermal U-event; and (3) during the later low-T (100–140 °C) hydrothermal alteration (stage 3), U was remobilized and derived from the dissolution of pre-existing uraninite by CO2- and SiO2-rich fluids and interacted with reducing agent (e.g., pyrite) leading to reprecipitation of coffinite. This process represents a regional and extensive low-T hydrothermal U-event. In view of this, U minerals evolved from magmatic uraninite-A though fluid-induced recrystallized uraninite-B to coffinite, revealing three episodes of U circulation in the magmatic-hydrothermal system.

Description: Aimed at the one-to-one certification problem of unsteady state iris at different shooting times, a multi-algorithm parallel integration general model structure is proposed in this paper. The iris in the lightweight constrained state affected by defocusing, deflection, and illumination is taken as the research object, the existing algorithms are combined into the model structure effectively, and a one-to-one certification algorithm for lightweight constrained state unsteady iris was designed based on multi-algorithm integration and maximum trusted decision. In this algorithm, a sufficient number of iris internal feature points from the unstable state texture were extracted as effective iris information through the image processing layer composed of various filtering processing algorithms, thereby eliminating defocused interference. In the feature recognition layer, iris deflection interference was excluded by the improved methods of Gabor and Hamming and Haar and BP for the stable features extracted by the image processing layer, and two certification results were obtained by means of parallel recognition. The correct number of certifications for an algorithm under a certain lighting condition were counted. The method with the most correct number was set as the maximum trusted method under this lighting condition, and the results of the maximum trusted method were taken as the final decision, thereby eliminating the effect of illumination. Experiments using the JLU and CASIA iris libraries under the prerequisites in this paper show that the correct recognition rate of the algorithm can reach a high level of 98% or more, indicating that the algorithm can effectively improve the accuracy of the one-to-one certification of lightweight constrained state unsteady iris. Compared with the latest architecture algorithms, such as CNN and deep learning, the proposed algorithm is more suitable for the prerequisites presented in this paper, which has good environmental inclusiveness and can better improve existing traditional algorithms’ effectiveness through the design of a parallel integration model structure.

Description: With the rapid development of marine IoT (Internet of Things), ocean MDTN (Mobile Delay Tolerant Network) has become a research hot spot. Long-term trajectory prediction is a key issue in MDTN. There are no long-term fine-grained trajectory prediction methods proposed for ocean vessels because a vessel’s mobility pattern lacks map topology support and can be easily influenced by the fish moratorium, sunshine duration, etc. A traditional on-land trajectory prediction algorithm cannot be directly utilized in this field because trajectory characteristics of ocean vessels are far different from that on land. To address the problem above, we propose a novel long-term trajectory prediction algorithm for ocean vessels, called L-VTP, by utilizing multiple sailing related parameters and K-order multivariate Markov Chain. L-VTP utilizes multiple sailing related parameters to build multiple state-transition matrices for trajectory prediction based on quantitative uncertainty analysis of trajectories. Trajectories’ sparsity of ocean vessels results in a critical state missing problem of a high-order state-transition matrix. L-VTP automatically traverses other matrices in a specific sequence in terms of quantitative uncertainty results to overcome this problem. Furthermore, the different mobility models of the same vessel during the day and the night are also exploited to improve the prediction accuracy. Privacy issues have been taken into consideration in this paper. A quantitative model considering Markov order, training metadata and privacy leak degree is proposed to help the participant make the trade-off based on their customized requirements. We have performed extensive experiments on two years of real-world trajectory data that include more than two thousand vessels. The experiment results demonstrate that L-VTP can realize fine-grained long-term trajectory prediction with the consideration of privacy issues. The average error of 4.5-hour fine-grained prediction is less than 500 m. In addition, the proposed method can be extended to 10-hour prediction with an average error of 2.16 km, which is also far less than the communication range of ocean vessel communication devices.

Description: Underwater sensor networks have wide application prospects, but the large-scale sensing node deployment is severely hindered by problems like energy constraints, long delays, local disconnections, and heavy energy consumption. These problems can be solved effectively by optimizing sensing node deployment with a genetic algorithm. However, the genetic algorithm (GA) needs many iterations in solving the best location of underwater sensor deployment, which results in long running time delays and limited practical application when dealing with large-scale data. The classical parallel framework Hadoop can improve the GA running efficiency to some extent while the state-of-the-art parallel framework Spark can release much more parallel potential of GA by realizing parallel crossover, mutation, and other operations on each computing node. Giving full allowance for the working environment of the underwater sensor network and the characteristics of sensors, this paper proposes a Spark-based parallel GA to calculate the extremum of the Shubert multi-peak function, through which the optimal deployment of the underwater sensor network can be obtained. Experimental results show that while faced with a large-scale underwater sensor network, compared with single node and Hadoop framework, the Spark-based implementation not only significantly reduces the running time but also effectively avoids the problem of premature convergence because of its powerful randomness.

Description: Overloading of IP address semantics appeals for a new network architecture based on Identifier (ID)/Locator separation. The challenge of Identifier (ID)/Locator separation is how to solve the scalability and efficiency challenges of identity-to-location resolution. By analyzing the requirements of the Identifier (ID)/Locator separation protocol, this paper proposes a hierarchical mapping architecture on active-degree (HMAA). This HMAA was divided into three levels: active local level, neutral transfer level, and inert global level. Each mapping item is dynamically allocated to different levels to ensure minimizing delay according to its activity characteristics. The top layer CHORD is constructed by the Markov Decision Process, which can keep consistency between the physical topology and the logical topology. The simulation results on delay time show that HMAA can satisfy the scalability and efficiency requirements of an Identifier (ID)/Locator separation network.

Description: Numerous global-scale land-cover datasets have greatly contributed to the study of global environmental change and the sustainable management of natural resources. However, land-cover datasets inevitably experience information loss because of the nature of the uncertainty in the interpretation of remote-sensing images. Therefore, analyzing the spatial consistency of multi-source land-cover datasets on the global scale is important to maintain the consistency of time and consider the effects of land-cover changes on spatial consistency. In this study, we assess the spatial consistency of five land-cover datasets, namely, GLC2000, CCI LC, MCD12, GLOBCOVER and GLCNMO, at the global and continental scales through climate and elevation partitions. The influencing factors of surface conditions and data producers on the spatial inconsistency are discussed. The results show that the global overall consistency of the five datasets ranges from 49.2% to 67.63%. The spatial consistency of Europe is high, and the multi-year value is 66.57%. In addition, the overall consistency in the EF climatic zone is very high, around 95%. The surface conditions and data producers affect the spatial consistency of land-cover datasets to different degrees. CCI LC and GLCNMO (2013) have the highest overall consistencies on the global scale, reaching 67.63%. Generally, the consistency of these five global land-cover datasets is relatively low, increasing the difficulty of satisfying the needs of high-precision land-surface-process simulations.

Description: Phenylalanine ammonia-lyase (PAL) is the crucial enzyme of the phenylpropanoid pathway, which plays an important role in plant disease resistance. To understand the function of PAL in Picea asperata, in this study, the full-length cDNA sequence of the PAL gene from this species was isolated and named PaPAL. The gene contains a 2160-bp open reading frame (ORF) encoding 720 amino acids with a calculated molecular weight of 78.7 kDa and a theoretical isoelectric point of 5.88. The deduced PaPAL protein possesses the specific signature motif (GTITASGDLVPLSYIA) of phenylalanine ammonia-lyases. Multiple alignment analysis revealed that PaPAL has high identity with other plant PALs. The tertiary structure of PaPAL was predicted using PcPAL from Petroselinum crispum as a template, and the results suggested that PaPAL may have a similar function to that of PcPAL. Furthermore, phylogenetic analysis indicated that PaPAL has a close relationship with other PALs from the Pinaceae species. The optimal expression condition of recombinant PaPAL in Escherichia coli BL21 (DE3) was 0.2 mM IPTG (isopropyl β-D-thiogalactoside) at 16 °C for 4 h, and the molecular weight of recombinant PaPAL was found to be approximately 82 kDa. Recombinant PaPAL was purified and exhibited high PAL activity at optimal conditions of pH 8.6 and 60 °C. Quantitative real-time PCR (qRT-PCR) showed the PaPAL gene to be expressed in all tissues of P. asperata tested, with the highest expression level in the needles. The PaPAL gene was induced by the pathogen (Lophodermium piceae), which caused needle cast disease, indicating that it might be involved in defense against needle cast disease. These results provide a basis for understanding the molecular mechanisms of the PAL gene in the process of P. asperata disease resistance.

Description: Experimental overall performances on a double helix screw pump are presented and discussed, focusing on the leakage flow for two different rotational speeds. A comparison between experimental and URANS CFD approaches is performed in order to check the CFD closure models’ validity. Some specific local flow characteristics are extracted from the numerical results which give explanations about leakage backflows inside the screws and local distortion at the pump inlet section.

Description: In this study, the series temperature Charpy impact and drop-weight tear test (DWTT) were investigated, the misorientation angles among structural boundaries where the cleavage crack propagated were identified, and angles of {100} cleavage planes between adjacent grains along the cleavage crack propagated path were calculated in five directions (0°, 30°, 45°, 60°, and 90° to the rolling direction) of high-grade pipeline steel. Furthermore, the effective grain size (grain with misorientation angles greater than 15°) was redefined, and the quantitative influences of the redefined effective grain size on Charpy impact and DWTT is also discussed synthetically. The results showed that the microstructure presented a typical acicular ferrite characteristic with some polygonal ferrite and M-A islands (composed of martensite and retained austenite), and the distribution of the high-angle grain boundaries were mainly distributed in the range of 45°–65° in different directions. The Charpy impact energy and percent shear area of DWTT in the five directions increased with refinement of the redefined effective grain size, composed of grains with {100} cleavage planes less than 35° between grain boundaries. The ductile-to-brittle transition temperature also decreased with the refining of the redefined effective grain size. The redefined effective grain boundaries can strongly hinder fracture propagation through electron backscattered diffraction analysis of the cleavage crack path, and thus redefined effective grain can act as the effective microstructure unit for cleavage.