Double-layer Network Research Articles

2D double-layered dibenzoyl-tartrate chiral coordination polymer containing [Mn4L2(bpp)4] tetrahedral cage

The solution reactions of metal salts with (+)-dibenzoyl-tartaric acid (H2L) and 1,3-bis(4-pyridyl)propane (bpp) or 4,4′-bipyridine (4,4′-bipy) afford three two-dimensional (2D) coordination polymers, [Mn2L2(bpp)2(H2O)4]n·nH2O (1), [CuL(bpp)]n·nH2O (2) and [CoL(4,4′-bipy)(CH3OH)(H2O)]n (3). Dibenzoyl-tartrate ligand displays cis- or trans-conformation, and acts as a 1,4-dicarboxylate linker. Complex 1 features a beautiful 2D double-layered (4,4) network containing [Mn4L2(bpp)4] tetrahedral cage. The flexible bpp ligand links Mn(II) to form an interesting 64-membered saddle-shaped macrocycle [Mn4(bpp)4]. Complex 2 displays a 2D wave-like network assembled by 1D [CuL]n linear chain and 1D [Cu(bpp)]n zigzag chain. Complex 3 is a 2D layered network constructing from [CoL(CH3OH)(H2O)]n chain and [Co(4,4′-bipy)]n chain.

Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks.

Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

Impact of Topology on the Scalability of Mach–Zehnder-Based Multistage Silicon Photonic Switch Networks

We analyze the scalability of electro-optic Mach–Zehnder-based silicon photonic switch networks. We describe a simulation framework based on the transfer matrix method that enable to model any type of multistage networks. We simulate three common network topologies – Benes, path-independent loss, and double-layer – and analyze their scalability by performing optical link numerical simulations for 50 Gbps non-return-to-zero signals. Our study shows that for a radix-16, the double-layer network performs better with a link power penalty smaller than 1 dB thanks to its dilated arrangement. For equivalent radix, the Benes and path-independent loss networks have link power penalties larger than 4 dB. Our simulations also show stringent requirements for the waveguide crossing crosstalk, whose value should be smaller than −35 dB to close any realistic link budget.

Solvomorphism of Double-Layered Networks through Single-Crystal-to-Single-Crystal Transformation

Self-assembly of Hg(CF3SO3)2 with benzene-1,3,5-triyltris(methylene)tripicolinate (L) as a C3-symmetric tridentate ligand gives rise to a unique double-layered honeycomb two-dimensional (2D) structure of [Hg3L4](CF3SO3)6 with an hcb, net/(6,3) topology. In this communication, a unique 2D double-layered network’s four unprecedented polymorph patterns formed under various temperature, time, and solvent conditions are described. The double-layered 2D structure with π···π interaction affords two solvent-dependent morphs via its flexible conformation and sliding nature. Of the two morphs, a morph from acetone/dioxane changes to two different morphs according to time and temperature in single-crystal-to-single-crystal (SCSC) fashion.

Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents

Considering dynamical disease spreading network consisting of moving individuals, a new double-layer network is constructed, one where the information dissemination process takes place and the other where the dynamics of dise... | Find, read and cite all the research you need on Tech Science Press

High Gain, Broadband and Dual-Polarized Substrate Integrated Waveguide Cavity-Backed Slot Antenna Array for 60 GHz Band

In this paper, a compact substrate-integrated waveguide (SIW) cavity-backed slot antenna array with high gain, broadband, and dual-polarization performances is proposed for 60-GHz applications. An enhanced 17.1% impedance bandwidth was achieved by cutting semi-circle edges on the conventional slot radiator. A simplified SIW feed network is aperture-coupled vertically and constructed on a double-layered structure to implement the dual-polarization operation. By adopting innovative techniques on both radiating element and double-layered SIW feed networks, a high-gain, broadband, and dual-polarized $8\times8$ antenna array was designed on three-layered printed circuit board that allows for mass production. This configuration also resolves the trade-off between the bandwidth and gain of the existing 60-GHz dual-polarized antenna array. Its feasibility is proved by obtaining a measured gain in the range of 19.7–22.3 dB and an enhanced impedance bandwidth of 17.1% over 55.7–66.1 GHz for both horizontal and vertical polarizations. With advantages of high-gain, broadband, and dual-polarization performances in a low-cost low-profile structure, the proposed antenna array is a promising candidate for millimeter-wave wireless systems.

A Communication Network Robustness Estimation Method Based on an Improved ELM

The communication network robustness is becoming increasingly important because of its wider applications on higher reliability requirement systems, such as UAV, CBTC, etc. But communication network robustness estimation is becoming more difficult due to related various factors such as attacks, EMI, errors, mobility, fault-tolerant strategies, etc. With the purpose of estimating the robustness of communication network, most existing network robustness estimation researches mainly focus on failures in network physical layer and take complex network methods to estimate network robustness; recently, others have used Monte Carlo method to consider nodes mobility and several researches have summed up whole factors with weights to estimate the network robustness by AHP methods. Though these methods have largely been exploited to estimate the robustness of networks approximately, there is still no proper method to estimate the robustness of real communication network with consideration of nonlinear relationships among multiple factors. In this study, firstly, a double-layer network robustness model has been constructed; secondly, in order to take more robustness related factors into consideration, we have constructed a simulation platform based on NS-3; finally, wehave proposed a novel robustness estimation method based on improved ELM (extreme learning machine), which is powerful to estimate the nonlinear relationships. The novel robustness estimation method has been formed by four steps: simulation and data collection, improved EML, model training, and estimation. In the end, contrast analyzes have been made to illustrate three facts: (1) fault-tolerant strategies can improve the robustness obviously;(2) our double-layer network robustness model is better than the previous model; (3) the improved ELM has a better cross-validation accuracy which is above 95%.

Structural Diversity and Vibrational Spectra of Nine Cu(I)-Cyanide Metal–Organic Frameworks with in Situ Generated N-Heterocyclic Ligands

Nine Cu(I)-cyanide metal–organic frameworks (MOFs), namely, [Cu4(CN)2(4-bpt)2]n (1), {[Cu3(CN)2(4-bpt)]·H2O}n (2), [Cu2(CN)(3-bpt)]n (3), [Cu2(CN)2(3-Hptz)]n (4), [Cu3(CN)2(3-ptz)]n (5), [Cu7(CN)7(3-tpt)2]n (6), {[Cu9(CN)9(btb)2]·btb}n (7), [Cu2(CN)2(4-azpy)]n (8), and [Cu3(CN)3(bpp)]n (9) (4/3-Hbpt = 3,5-bis(4/3-pyridyl)-1,2,4-triazole; 3-Hptz = 3-pyridyl-tetrazole; 3-tpt = 2,4,6-tris(3-pyridyl)-1,3,5-triazine; btb = 1,4-bis(1,2,4-triazol-4-yl)benzene; 4-azpy = 4,4′-azobispyridine; bpp = 1,3-bis(4-pyridyl)propane), were synthesized under hydrothermal conditions and structurally characterized. The 4-bpt, 3-bpt, and 3-Hptz ligands in 1–4 were in situ generated by cycloaddition reactions. Their structural features vary from two-dimensional (2D) (3), three-dimensional (3D) (4, 5, 6), 3D 2-fold interpenetration (1, 2, 8), to 3D 3-fold interpenetration (7, 9). Complex 1 is an intriguing 3D metal–organic framework (MOF) with a nanosized rectangular channel. Complex 3 exhibits a chiral 2D double-layered network ...

Temperature and solvent controlled syntheses of six hydrous 5-(3-pyridylmethoxy)isophthalate Cd(II) coordination polymers

Six hydrous Cd(II) coordination polymers based on a scorpion-like 5-(3-pyridylmethoxy)isophthalic acid (H2L), namely {[CdL(H2O)]·2H2O}n (1), [Cd4L4(H2O)4]n (2), [CdL(H2O)]n (3), [CdL(H2O)2]n (4), {[CdL(H2O)]·H2O}n (5) and [CdL]n (6), were hydrothermally synthesized and characterized by EA, IR, PXRD, TG-DSC and X-ray structural analysis. Temperature and solvent play crucial roles in the preparation of the coordination polymers. Complexes 1–3 were prepared in a H2O-DMF (6:2) solvent system at slightly different temperature (85, 100 and 120°C). Complexes 4–6 were prepared in different H2O-DMF solvents (6:3 and 8:2) and H2O-MeCN (3:6) solvent. These complexes possess different coordinated and/or lattice water molecules, and exhibit structural diversity and various topology nets. Complex 1 is a 2D double-layered coordination polymer. Complex 2 features a 3D porous framework with irl topology. Complex 3 displays a 2D double-layered network. Complex 4 is a 3D coordination polymer with sra topology. Complex 5 exhibits a 3D wave-like framework with sra topology. Complex 6 is a 3D coordination polymer with self-catenated hxg-d topology. 5-(3-Pyridylmethoxy)isophthalate adopts three types of coordination modes. These complexes exhibit higher thermal stability and emit strong luminescence.

Optimized contraction scheme for tensor-network states

In the tensor-network framework, the expectation values of two-dimensional quantum states are evaluated by contracting a double-layer tensor network constructed from initial and final tensor-network states. The computational cost of carrying out this contraction is generally very high, which limits the largest bond dimension of tensor-network states that can be accurately studied to a relatively small value. We propose an optimized contraction scheme to solve this problem by mapping the double-layer tensor network onto an intersected single-layer tensor network. This reduces greatly the bond dimensions of local tensors to be contracted and improves dramatically the efficiency and accuracy of the evaluation of expectation values of tensor-network states. It almost doubles the largest bond dimension of tensor-network states whose physical properties can be efficiently and reliably calculated, and it extends significantly the application scope of tensor-network methods.

Design and Analysis of a Cable Network System for a Deployable Reflector

The feasibility of a deployable reflector with a cable network system is investigated. The cable network system comprises a series of planar double-layer cable networks. The geometry and two typical layouts of cable networks are examined. The self-equilibrated stress modes are analyzed with the method of the Moore–Penrose generalized inverse matrix and assembled into a uniform prestress state. The parametric sensitivities of cable networks are studied on account of the temperature effect. The surface error caused by elastic boundary deformation is minimized through the inverse-iteration form finding of the cable network system. Some numerical experiments are carried out to study the reflector properties under the thermal loads in space. The vibration modal analysis is also conducted. Results indicate that the reflector can work with the rms surface error due to thermal distortion less than 0.10 mm.

Syntheses, structures and luminescence of three copper(I) cyanide coordination polymers incorporating flexible N-donor ligands

Three copper(I) cyanide coordination polymers, namely [Cu8(CN)8(btmb)2]n (1), [Cu(CN)(btmb)0.5]n (2) and [Cu2(CN)2(dpa)]n (3) (btmb=1,4-bis(1,2,4-triazol-1-ylmethyl)benzene, dpa=di(4-pyridyl)amine), were synthesized under hydrothermal conditions and characterized by elemental analyses, IR spectra, PXRD and thermogravimetric analyses. Single-crystal X-ray diffraction analyses reveal that complex 1 is an interesting 2D double-layered network constructing from eight distinct Cu(I) centers, eight μ2-cyanides and two tetradentate cis-btmb ligands. Complex 2 is a ladder-like coordination polymer assembled by CuCN linear chain and bidentate trans-btmb linker. Complex 3 has a 2D wave-like network constructing from CuCN zigzag chain and V-shape dpa spacer. These coordination polymers are thermally stable up to 270–300°C. They emit blue luminescence originating from ligand-centered emission.

A Double-Layer Neural Network Framework for High-Frequency Forecasting

Nowadays, machine trading contributes significantly to activities in the equity market, and forecasting market movement under high-frequency scenario has become an important topic in finance. A key challenge in high-frequency market forecasting is modeling the dependency structure among stocks and business sectors, with their high dimensionality and the requirement of computational efficiency. As a group of powerful models, neural networks (NNs) have been used to capture the complex structure in many studies. However, most existing applications of NNs only focus on forecasting with daily or monthly data, not with minute-level data that usually contains more noises. In this article, we propose a novel double-layer neural (DNN) network for high-frequency forecasting, with links specially designed to capture dependence structures among stock returns within different business sectors. Various important technical indicators are also included at different layers of the DNN framework. Our model framework allows update over time to achieve the best goodness-of-fit with the most recent data. The model performance is tested based on 100 stocks with the largest capitals from the S8P 500. The results show that the proposed framework outperforms benchmark methods in terms of the prediction accuracy and returns. Our method will help in financial analysis and trading strategy designs.

Study on evolution characteristics of air traffic situation complexity based on complex network theory

This study proposed a new method to describe air traffic situations based on the theory of complex networks and elaborate its evolutionary laws, expecting to reveal the basic characteristics of air traffic complexity. Based on 2D complexity and 3D complexity, a double-layer multistage dynamic network model was built and an air traffic complexity vector was proposed. The real flight data from four traffic control sectors were used to characterize statistically the evolution of air traffic situations. Results show that the complexity vector helps to describe the structural characteristics of air traffic situations and identify the evolutionary characteristics of different traffic situations. Based on k-means, air traffic situations were classified into three complexity patterns. The frequency of occurrence, life cycle, and transition probability of complexity patterns were statistically calculated. Results show that the traffic situations of high-altitude sectors bring more 2D complexity and less 3D complexity than those of low-altitude sectors. In most cases, the four sectors belong to medium complexity or below, and a specific complexity pattern appears in a certain period with a specific probability. The life cycle of air traffic complexity patterns is usually on the order of seconds or minutes and differs slightly among patterns. Transition probabilities of patterns indicate that the air traffic situation is evolving stably on the whole, but will probably runs into severe change.

Field-Induced Relaxation of Magnetization in a Three-Dimensional LnMOF with the Second Bridging Ligand Squarate.

A three-dimensional (3D) dysprosium(III) metal-organic framework with nicotinate N-oxide (NNO–) and squarate (C4O42–) mixed bridging ligands, [Dy(NNO)(C4O4)(H2O)]n (1), has been hydrothermally synthesized. The dysprosium(III) ions are linked to each other by the squarate anions to form a unique dysprosium(III) squarate double-layered network; the NNO– anions then bridge such layers to complete the 3D framework. Complex 1 exhibits a two-step relaxation of magnetization under a dc field of 1000 Oe, with effective energy barrier values of 8.5 and 14.3 K, respectively.

Hydrothermal Crystallization of Uranyl Coordination Polymers Involving an Imidazolium Dicarboxylate Ligand: Effect of pH on the Nuclearity of Uranyl-Centered Subunits.

Four uranyl-bearing coordination polymers (1-4) have been hydrothermally synthesized in the presence of the zwitterionic 1,3-bis(carboxymethyl)imidazolium (= imdc) anion as organic linkers after reaction at 150 °C. At low pH (0.8-3.1), the form 1 ((UO2)2(imdc)2(ox)·3H2O; ox stands for oxalate group) has been identified. Its crystal structure (XRD analysis) consists of the 8-fold-coordinated uranyl centers linked to each other through the imdc ligand together with oxalate species coming from the partial decomposition of the imdc molecule. The resulting structure is based on one-dimensional infinite ribbons intercalated by free water molecules. By adding NaOH solution, a second form 2 is observed for pH 1.9-3.9 but in a mixture with phase 1. The pure phase of 2 is obtained after a hydrothermal treatment at 120 °C. It corresponds to a double-layered network (UO2(imdc)2) composed of 7-fold-coordinated uranyl cations linked via the imdc ligands. In the same pH range, a third phase ((UO2)3O2(H2O)(imdc)·H2O, 3) is formed: it is composed of hexanuclear units of 7-fold- and 8-fold-coordinated uranyl cations, connected via the imdc molecules in a layered assembly. At higher pH, the chain-like solid (UO2)3O(OH)3(imdc)·2H2O (4) is observed and composed of the infinite edge-sharing uranyl-centered pentagonal bipyramidal polyhedra. As a function of pH, uranyl nuclearity increases from discrete 8- or 7-fold uranyl centers (1, 2) to hexanuclear bricks (3) and then infinite chains in 4 (built up from the hexameric fragments found in 3). This observation emphasized the influence of the hydrolysis reaction occurring between uranyl centers. The compounds have been further characterized by thermogravimetric analysis, infrared, and luminescence spectroscopy.

Reciprocity in spatial evolutionary public goods game on double-layered network.

Spatial evolutionary games have mainly been studied on a single, isolated network. However, in real world systems, many interaction topologies are not isolated but many different types of networks are inter-connected to each other. In this study, we investigate the spatial evolutionary public goods game (SEPGG) on double-layered random networks (DRN). Based on the mean-field type arguments and numerical simulations, we find that SEPGG on DRN shows very rich interesting phenomena, especially, depending on the size of each layer, intra-connectivity, and inter-connected couplings, the network reciprocity of SEPGG on DRN can be drastically enhanced through the inter-connected coupling. Furthermore, SEPGG on DRN can provide a more general framework which includes the evolutionary dynamics on multiplex networks and inter-connected networks at the same time.

Measuring the quality of exercises.

This work explores the problem of exercise quality measurement since it is essential for effective management of diseases like cerebral palsy (CP). This work examines the assessment of quality of large amplitude movement (LAM) exercises designed to treat CP in an automated fashion. Exercise data was collected by trained participants to generate ideal examples to use as a positive samples for machine learning. Following that, subjects were asked to deliberately make subtle errors during the exercise, such as restricting movements, as is commonly seen in cases of patients suffering from CP. The quality measurement problem was then posed as a classification to determine whether an example exercise was either "good" or "bad". Popular machine learning techniques for classification, including support vector machines (SVM), single and double-layered neural networks (NN), boosted decision trees, and dynamic time warping (DTW), were compared. The AdaBoosted tree performed best with an accuracy of 94.68% demonstrating the feasibility of assessing exercise quality.

Two metal-organic frameworks with different configurations constructed from a flexible tripodal triaromatic acid

Two metal-organic frameworks [Ce2(L)2(DMF)4] (1), and [Ni3(HL2−)4(bpe)3(H2O)4]·[H2N(CH3)2+]2(DMF)6(H2O)8 (2) (H3L = 4,4′,4″-{[(2,4,6-trimethylbenzene-1,3,5-triyl)tris-(methylene)] tris(oxy)}tribenzoic acid, bpe = trans-4,4′-bipyridylethylene) have been solvothermally synthesized from a flexible tripodal ligand. Single-crystal X-ray diffraction shows that compound 1 features a 3,6-connected double-layer network which is further connected by weak π-π interactions between benzene rings to form a 3D porous network. Compound 2 exhibits an unprecedented (4,5)-connected (33.42.5.62.72)2(6.84.10) topology based on zigzag chains and straight chains. In addition, thermal stabilities and luminescent properties of 1 and 2 were investigated in the solid state.

Enhancement on thermal properties of paraffin/calcium carbonate phase change microcapsules with carbon network

For latent heat storage with phase change materials (PCM), heat transfer rate and energy storage efficiency are often limited by the low PCM thermal conductivity. Therefore, this paper develops a sort of new phase change composites (PCC) with double-layer network to enhance the thermal conductivity and thermal stability. Different mass fractions of expanded graphite (EG) as heat transfer promoter were added in the spindle microencapsulated phase change materials (MicroPCM). The relationship between the PCC thermal conductivity and carbon network structure was investigated. The thermal conductivity was measured by transient plane source method. The carbon network structure of PCC was detected by energy dispersive spectroscopy. Temperature-regulated property was captured by infrared imager. As a result, distinct carbon network structure in PCC was observed with 20% mass fraction of EG, the corresponding thermal conductivity was increased up to 7.5 times of the pristine paraffin. Negligible change in thermal properties of the PCC was confirmed after 100 times thermal cycling and 7days serving durability tests. The enhancement on thermal properties of the PCC is a promising route to achieve high energy storage efficiency targets of numerous thermal applications.