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We study the boundary-dissipated transverse field Ising model described by a Lindblad Master equation and exactly solve its Liouvillian spectrum in the whole parameter space. By mapping the Liouvillian into a Su-Schrieffer-Heeger model with imaginary boundary potentials under a parity constraint, we solve the rapidity spectrum analytically and thus construct the Liouvillian spectrum strictly with a parity constraint condition. Our results demonstrate that the Liouvillian spectrum displays four different structures, which are characterized by different numbers of segments. By analyzing the properties of rapidity spectrum, we can determine the phase boundaries between different spectrum structures analytically and prove the Liouvillian gap fulfilling a duality relation in the weak and strong dissipation region. Furthermore, we unveil the existence of a dynamical duality, i.e., the long-time relaxation dynamics exhibits almost the same dynamical behavior in the weak and strong dissipation region as long as the duality relation holds true., Comment: 15 pages, 10 figures

Few-shot classification aims to learn a model that can generalize well to new tasks when only a few labeled samples are available. To make use of unlabeled data that are more abundantly available in real applications, Ren et al. \shortcite{ren2018meta} propose a semi-supervised few-shot classification method that assigns an appropriate label to each unlabeled sample by a manually defined metric. However, the manually defined metric fails to capture the intrinsic property in data. In this paper, we propose a \textbf{S}elf-\textbf{A}daptive \textbf{L}abel \textbf{A}ugmentation approach, called \textbf{SALA}, for semi-supervised few-shot classification. A major novelty of SALA is the task-adaptive metric, which can learn the metric adaptively for different tasks in an end-to-end fashion. Another appealing feature of SALA is a progressive neighbor selection strategy, which selects unlabeled data with high confidence progressively through the training phase. Experiments demonstrate that SALA outperforms several state-of-the-art methods for semi-supervised few-shot classification on benchmark datasets., Comment: 9 pages

The anti-inflammatory activities of agaro-oligosaccharide (AOS) fractions with different degrees of polymerization (DPs) were compared, and their anti-inflammatory mechanisms were investigated. Total AOS (F0) was prepared from the agar of Gracilaria lemaneiformis, and its three separated fractions of high DP (F1), medium DP (F2), and low DP (F3) were obtained using Bio-Gel P2 chromatography. F2 showed a high anti-inflammatory activity but also a potential cytotoxicity, while F1 and F3 showed no cytotoxicity but weak anti-inflammatory activities. The total AOS fractions of F0 exhibited a higher anti-inflammatory activity than the summarized activities of the separated fractions; moreover, the combination of the three fractions significantly alleviated the potential cytotoxicity of F2. Thus, the synergistic anti-inflammatory effects of the AOS fractions were revealed. Furthermore, the anti-inflammatory mechanisms of F0 were investigated both in lipopolysaccharide (LPS)-induced RAW 264.7 cells in vitro and LPS-induced zebrafish embryos in vivo. F0 inhibited NO production and PGE2 expression via the downregulation of iNOS and COX-2 expression, and it suppressed TNF-α, IL-1β, and IL-6 productions at the protein and mRNA levels in RAW 264.7 cells. It is the first time that the zebrafish model was used for the determination of anti-inflammatory activities of AOS, and F0 showed to suppress the productions of NO and ROS by exerting a protective effect against the phenotypic changes and the cell damage caused by LPS. This is the first report of the synergistic anti-inflammatory activities of AOS fractions. The result revealed that AOS without separation and purification showed a favorable anti-inflammatory activity, which was easy to be produced and had potential application in the food, pharmaceutical, and cosmetic industries.

In this paper, we study sensor-Base Station grouping management and power allocation problem for heterogeneous wireless sensor networks. We develop a stochastic optimization problem to maximize the long-term average energy efficiency. The developed optimization problem belongs to a non-convex mixed-integer program. By exploiting the fractional program, the continuity relaxation and Lagrange dual methods, the optimal solution is derived via the developed EE-based resource allocation algorithm. Simulation results validate the advantages of the proposed algorithm.

Power line communications (PLC) is one of the communication methods which have been deployed and attracted considerable attention on supporting smart grid applications. Furthermore, link failures will have a great impact on the normal operation of PLC network and the causes of link failures are diverse. Therefore, rapid fault location is extremely important for PLC. Fault localization generally requires complete knowledge of the network topology which is usually unknown and needs to be learned by topology inference algorithms. However, it is difficult for routers to collect complete topology information for topology inference. We propose an algorithm based on partial information for topology inference to help the PLC to detect and locate faults normally. The inference algorithm first builds a virtual topology, overestimates the number of network components, and then repeatedly merges the links in this topology to infer the structure of the real network. We conducted simulations and compared our algorithm with the most advanced inference algorithms. The results show that compared with other methods, the topology structure of our inference algorithm significantly improves the performance of the fault location.

The smart grid is developing in the direction of two-way interaction. As an important platform for two-way interaction between the user side and the power system, the social network plays an important role in the development of the smart grid. The structural parameters of the social network include the total number of users and the network density. The network density is reflected by the number of neighbor nodes of the network node and the strength of the connection. Determining the total number of users in the network is beneficial to the smart grid for power allocation. Power system load peaks, insufficient power supply, etc. Deter-mining network density helps speed up the popularization and promotion of smart grid technology and helps to understand the social influence of users in social networks. Offline social network topologies are usually selected by interviewees and then asked to list their neighbors. This paper proposes an inference technique based on so-called “fixed choice” surveys, which requires the interviewee to enumerate all the strong ties and a fixed number of weak ties(e.g.,two or ten). Then use the method of moments to infer the total number of users and the network density of the social network. Experiments using simulated data show that the proposed inference algor-ithm performs well in various network topo-logies and measurement scenarios, and the est-imates obtained are significantly more accu-rate than the estimates obtained directly using the coarse observation network.

Rapid and large-scale synthesis of metal–organic frameworks (MOFs) materials is of great significance for their practical applications. For the first time, we have electrochemically synthesized IRMOF-3 at room temperature by applying a voltage to a zinc electrode immersed in electrolyte containing 2-aminoterephthalic acid (NH2-H2BDC). The reaction conditions, including the ratio of solvent (electrolyte), the applied voltage, and different reaction times, were investigated and optimized. The degree of crystallinity and nanomorphology of the synthesized IRMOF-3 can be controlled by changing the reaction conditions. More importantly, we demonstrated that the electrochemical synthesis strategy can rapidly obtain nanoscale IRMOF-3 with high crystallinity on a gram scale. In addition, in comparison with the product of solvothermal synthesis, the electrochemically synthesized nanoscale IRMOF-3 exhibits improved fluorescent detection ability to 2,4,6-trinitrophenol (TNP) with a detection limit of about 0.1 ppm.

Elevators have become an indispensable tool for people. If each program is used in practice, it will waste a lot of human resources, material resources and financial resources, so the elevator simulation platform has played its advantages. Among them, the generation of traffic flow is the key factor. In order to realise the reasonable configuration of the elevator, it is necessary to accurately simulate the traffic flow in each period of the building, and the MATLAB program is calling by VC++ to complete the simulation. Through this method, the traffic flow at different times can be simulated by simple operation, and this method can fully play the advantages of the respective programs.

Power line communication is an important alternative to be considered for providing broadband access to remote areas, which can highly reduce the capital expenditures. Since the communication capacity of the power line is generally limited, the resource allocation for the access points should be carefully considered when it serves as a backhaul. In this paper, we aim to address the optimal resource allocation problem for femtocells with the broadband power line backhaul. We first formulate the resource allocation problem as a utility maximization problem, which is a mixed-integer nonlinear programming (MINLP) problem and is shown NP-Hard. To this end, we utilize the continuity relaxation to transform the MINLP problem to a continuous programming problem, and then we take advantage of the Lagrange dual decomposition method to solve it. The complexity of the proposed algorithm is analyzed. Extensive simulations are carried out and show that the proposed algorithm performs much better than the traditional algorithm.

We experimentally demonstrate the formation of salt aggregations with unexpectedly high concentration inside multi-walled carbon nanotubes (CNTs) soaked only in dilute salt solutions and even in solutions containing only traces of salts. This finding suggests the blocking of fluid across CNTs by the salt aggregations when CNTs are soaked in a dilute salt solution with the concentration of seawater or even lower, which may open new avenues for the development of novel CNT-based desalination techniques. The high salt accumulation of CNTs also provides a new CNT-based strategy for the collection/extraction of noble metal salts in solutions containing traces of noble metal salts. Theoretical analyses reveal that this high salt accumulation inside CNTs can be mainly attributed to the strong hydrated cation-pi interactions of hydrated cations and pi electrons in the aromatic rings of CNTs., 10 pages, 4 figures

We show that interface tailoring is an effective approach towards high performance G/Si Schottky-barrier solar cells. Inserting a thin graphene oxide (GO) interfacial layer can improve the efficiency of graphene/silicon solar cells by >100%. The role of the GO interfacial layer is systematically investigated by varying the annealing temperature and thickness of the GO film. It is found that GO cannot be treated as the common thought, i.e., an insulator. In other words, the G/GO/Si solar cell is not suitable to be treated as a “MIS” cell. In contrast, it should be regarded as a p-doped thin layer. The effects of GO film thickness on device response are also studied and there exists an optimal thickness for device performance. A record 12.3% (device size: 3 × 3 mm2) power conversion efficiency is achieved by further performance optimization (chemical doping graphene and antireflection coating).

Two luminescent functionalised supramolecular coordination polymers, namely, [Zn(TPDC-2CH3)(H2O)2]·H2O (1) and [Cd(TPDC-2CH3)(H2O)4]·H2O (2), were successfully synthesised by the reaction of 2′,5′-dimethyl-[1,1′:4′,1″-terphenyl]-4,4″-dicarboxylic acid (H2TPDC-2CH3) with Zn2+ and Cd2+ ions, respectively. X-Ray crystallographic analysis reveals that both compounds 1 and 2 exhibit fascinating 3D supramolecular networks, in which metal ions are linked by ligands to form a 1D chain which further extends to a 3D structure through the interaction of hydrogen bonding. The use of 1 and 2 as luminescent sensors for the optical detection of metal ions: Na+, K+, Hg2+, Ag+, Ca2+, Co2+, Ni2+, Mn2+, Cu2+, Zn2+, Cd2+, Pb2+, Mg2+, Al3+, Fe3+, Fe2+, In3+, Bi3+, and Cr3+ was carried out in aqueous solution, and the results indicated that compound 1 could effectively detect Hg2+ ions among various cations at room temperature, with a detection limit of 3.6 × 10−15 M.

On the large scale the commercial ship development trend indicates that the length of ship becomes longer and longer whilst its hull girder turns into much more flexible than that of small and medium-sized ships. This results in a ship sustaining both springing and slamming responses when travelling at sea. A VLCC is introduced in this paper to study its low and high frequency wave load responses in both full loaded and ballast condition. Experimental and theoretical methods were used to investigate the characteristic of this VLCC’s wave loads. A segmental model with its length more than six meters being connected by two non-uniform beams was used to get the vertical bending moments at each measured cut. A 2D nonlinear theory and a 3D hydroelastic theory were both employed to predict the wave loads responses. The results had been compared between experimental and theoretical methods. It was shown that springing phenomenon was prone to appear when wave amplitude was low and its period was short, especially when wave encounter frequency was an integral multiple of the basic vibration frequency of the ship hull girder. Slamming happened when the wave amplitude was high. However, it was difficult to distinguish slamming or springing or their combination from the wave-induced vibrations because of the small damping ratio in total vibrations. Loading condition has a great influence on wave loads responses especially on the springing behavior. It was found that springing behavior is much more severe in ballast condition than in full loaded condition. The mechanism of it which mentioned in other reference was reconfirmed in this paper.Copyright © 2014 by ASME

Background: Hepatitis C virus (HCV) infection rates in drug users vary among different regions of China. Drug users who are unaware of their HCV serostatus tend to engage in more risky behaviors. Objectives: This prospective study aimed to assess risk factors of HCV infection in drug users among 11 methadone maintenance treatment (MMT) clinics in Xi’an, China. Patients and Methods: Baseline characteristics and drug use information of patients were collected upon enrollment in the study and anti-HCV tests were performed within one month after the enrollment. Data on daily medication, monthly random urine morphine test results, illicit drug use and MMT retention time were recorded during a 5-year follow-up. Results: Of 10243 patients, 58.0% had positive results for anti-HCV. Injection drug use, longer duration of drug abuse, older age, female gender, unmarried status and unemployment were independent risk factors of HCV infection. Urine test positivity rate was lower (14.8% vs. 16.7%, χ2 = 100.235, P < 0.05), but MMT retention rate was higher (log-rank χ2 = 4.397, P < 0.05) in the anti-HCV positive group than anti-HCV negative one. However, multivariate regression revealed no significant association between anti-HCV serostatus and either MMT retention time or illicit drug use. Conclusions: The major risk factor of HCV infection was injection drug use. The patient’s awareness of his or her HCV status had a minor effect in reduction of illicit drug use and improvement in MMT retention. Therefore, adequate counseling is necessary for drug users in MMT clinics in Xi’an.