2,598 research outputs found

    A hybrid LSTM neural network for energy consumption forecasting of individual households

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    Irregular human behaviors and univariate datasets remain as two main obstacles of data-driven energy consumption predictions for individual households. In this study, a hybrid deep learning model is proposed combining an ensemble long short term memory (LSTM) neural network with the stationary wavelet transform (SWT) technique. The SWT alleviates the volatility and increases the data dimensions, which potentially help improve the LSTM forecasting accuracy. Moreover, the ensemble LSTM neural network further enhances the forecasting performance of the proposed method. Verification experiments were performed based on a real-world household energy consumption dataset collected by the 'UK-DALEat project. The results show that, with a competitive training efficiency, the proposed method outperforms all compared state-of-art methods, including the persistent method, support vector regression (SVR), long short term memory (LSTM) neural network and convolutional neural network combining long short term memory (CNN-LSTM), with different step sizes at 5, 10, 20 and 30 minutes, using three error metrics

    The unified description of the QsqˉqˉQs \bar q \bar q molecular bound states, molecular resonances and compact tetraquark states in the quark potential model

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    We calculate the mass spectrum of the QsqˉqˉQs\bar q \bar q (Q=c,b)(Q=c, b) tetraquark states with JP=(0,1,2)+J^P=(0,1,2)^+ using the AL1 quark potential model, which successfully describes the conventional hadron spectrum. We employ the Gaussian expansion method to solve the four-body Schr\"odinger equation, and use the complex scaling method to identify the resonances. With the notation TQs,I(J)Theo. (M)T_{Q s, I(J)}^{\text {Theo. }}(M), we find several near-threshold bound states and resonances, including Tcs,0(0)Theo.(2350)T_{cs,0(0)}^{\mathrm{Theo.}}(2350), Tcs,0(0)Theo.(2906)T_{cs,0(0)}^{\mathrm{Theo.}}(2906), Tbs,0(0)Theo.(5781)T_{bs,0(0)}^{\mathrm{Theo.}}(5781), Tbs,0(1)Theo.(5840)T_{bs,0(1)}^{\mathrm{Theo.}}(5840), and Tbs,0(0)Theo.(6240)T_{bs,0(0)}^{\mathrm{Theo.}}(6240) which are close to the DKˉD\bar{K}, DKˉD^*\bar{K}^*, BˉKˉ\bar{B}\bar{K}, BˉKˉ\bar{B}^*\bar{K} and BˉKˉ\bar{B}^*\bar{K}^* thresholds, respectively. Furthermore, their spatial structures clearly support their molecular natures. The resonance Tcs,0(0)Theo.(2906)T_{cs,0(0)}^{\mathrm{Theo.}}(2906) has a mass of 29062906 MeV, a width of 2020 MeV, and quantum numbers I(JP)=0(0+)I(J^P)=0(0^+), which may serve as a good candidate for the experimental Tcs0(2900)T_{cs0}(2900) state. We strongly urge the experimental search of the predicted states.Comment: 9 pages, 4 figures, 3 table

    Empirical study on clique-degree distribution of networks

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    The community structure and motif-modular-network hierarchy are of great importance for understanding the relationship between structures and functions. In this paper, we investigate the distribution of clique-degree, which is an extension of degree and can be used to measure the density of cliques in networks. The empirical studies indicate the extensive existence of power-law clique-degree distributions in various real networks, and the power-law exponent decreases with the increasing of clique size.Comment: 9 figures, 4 page

    Electronic Structures of Graphene Layers on Metal Foil: Effect of Point Defects

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    Here we report a facile method to generate a high density of point defects in graphene on metal foil and show how the point defects affect the electronic structures of graphene layers. Our scanning tunneling microscopy (STM) measurements, complemented by first principle calculations, reveal that the point defects result in both the intervalley and intravalley scattering of graphene. The Fermi velocity is reduced in the vicinity area of the defect due to the enhanced scattering. Additionally, our analysis further points out that periodic point defects can tailor the electronic properties of graphene by introducing a significant bandgap, which opens an avenue towards all-graphene electronics.Comment: 4 figure

    Src-family protein tyrosine kinases: a promising target for treating chronic pain

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    Abstract Despite growing knowledge of the mechanisms of chronic pain, it remains a major challenge facing clinical practice. Src-family protein tyrosine kinases (SFKs), a group of non-receptor protein tyrosine kinases, have been implicated in neuronal development and synaptic plasticity. SFKs are critically central to various transmembrane receptors e.g. G-protein coupled receptor (GPCR), EphB receptor (EphBR), increased intracellular calcium, epidermal growth factor (EGF) and other growth factors that regulate the phosphorylation of N-methyl-D-aspartic acid receptor (NMDAR) 2B subunit, thus contributing to the development of chronic pain. SFKs have also been regarded as an important point of convergence of intracellular signaling components that regulate microglia functions and the immune response. Additionally, intrathecal administration of SFKs inhibitors significantly alleviates mechanical allodynia in different chronic pain models. Thus, here we reviewed the current evidence of the role of SFKs in the development of chronic pain caused by complete Freund's adjuvant (CFA) injection, peripheral nerve injury (PNI), streptozotocin (STZ) injection and bone metastasis. Moreover, the role of SFKs on the development of morphine tolerance has also been discussed. Management of SFKs therefore emerged as a potential therapeutic target for the treatment of chronic pain in terms of safety and efficacy. Key words Chronic pain; Src-family protein tyrosine kinases; N-methyl-D-aspartic acid receptor; Microglia

    Concentration Polarization of High-Density Lipoprotein and Its Relation with Shear Stress in an In Vitro Model

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    The purpose of this study was to determine the concentration polarization of high-density lipoprotein (HDL) at the surface of the carotid artery under conditions of steady flow and to establish its relationship with shear stress using an in vitro vascular simulation model of carotid bifurcation. Shear stress, HDL concentration at the surface, and the ratio of HDL concentration at the surface to concentration in bulk flow were measured at different locations within the model under high-speed (1.451 m/s) and low-speed (0.559 m/s) flow. HDL showed concentration polarization at the surface of the carotid artery model, particularly in the internal carotid artery sinus. With decreasing flow velocity, the shear stress at the surface also decreased, and HDL concentration polarization increased. The concentration polarization of HDL was negatively and strongly correlated with shear stress at both low- (r = −0.872, P < .001) and high-speed flow (r = −0.592, P = .0018)

    Ethyl 2-amino-6-benzyl-4,5,6,7-tetra­hydro­thieno[2,3-c]pyridine-3-carboxyl­ate

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    In the title compound, C17H20N2O2S, the tetra­hydro­pyridine ring adopts an envelope conformation with the N atom at the flap position; the phenyl ring makes a dihedral angle of 81.06 (10)° with the thio­phene ring. The amino group links with the carbonyl O atom via intra­molecular N—H⋯O hydrogen bonding, forming a six-membered ring. In the crystal, inter­molecular N—H⋯O hydrogen bonds link the mol­ecules into infinite chains running along the b axis

    N-Phenyl­morpholine-4-carboxamide

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    In the title compound, C11H14N2O2, the urea-type NC=ON moiety [planar to within 0.0002 (13) Å] is inclined to the phenyl ring by 42.88 (8) Å, and the morpholine ring has a chair conformation. In the crystal, inter­molecular N—H⋯O hydrogen bonds link the mol­ecules into infinite chains in [001]
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