17,871 research outputs found

    Can board climate-responsible orientation improve corporate carbon performance? The moderating role of board carbon awareness and firm reputation

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    Overwhelming evidence from prior research suggests the functions of the board of directors have a vital influence on carbon performance. However, very little is known about the moderating effect of board functions. This study attempts to fill this gap by developing and empirically testing a conceptual model that highlights the role of board carbon awareness and firm reputation in the relationship between board climate-responsible orientation (BCO) and carbon performance. Using a fixed effect model to analyze data from 665 US listed firms covering a period of 2010–2019, we find that BCO and carbon performance show a U-shaped non-linear relationship. Increased experience of BCO improves corporate carbon performance. The results also provide evidence of the moderating effect of carbon awareness and firm reputation on the relationship between BCO and carbon performance. Carbon awareness reduces symbolic emission reduction actions in carbon management, while, firm reputation will cause symbolic emission reduction actions. Besides, splitting the sample according to firm size and carbon dependency shows BCO has a better effect on the carbon performance of small or medium-sized and high carbon-dependency firms. The findings have important implications for managers to use firm governance mechanisms to improve carbon performance

    Parametric survey of longitudinal prominence oscillation simulations

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    It is found that both microflare-sized impulsive heating at one leg of the loop and a suddenly imposed velocity perturbation can propel the prominence to oscillate along the magnetic dip. An extensive parameter survey results in a scaling law, showing that the period of the oscillation, which weakly depends on the length and height of the prominence, and the amplitude of the perturbations, scales with R/g\sqrt{R/g_\odot}, where RR represents the curvature radius of the dip, and gg_\odot is the gravitational acceleration of the Sun. This is consistent with the linear theory of a pendulum, which implies that the field-aligned component of gravity is the main restoring force for the prominence longitudinal oscillations, as confirmed by the force analysis. However, the gas pressure gradient becomes non-negligible for short prominences. The oscillation damps with time in the presence of non-adiabatic processes. Compared to heat conduction, the radiative cooling is the dominant factor leading to the damping. A scaling law for the damping timescale is derived, i.e., τl1.63D0.66w1.21v00.30\tau\sim l^{1.63} D^{0.66}w^{-1.21}v_{0}^{-0.30}, showing strong dependence on the prominence length ll, the geometry of the magnetic dip (characterized by the depth DD and the width ww), and the velocity perturbation amplitude v0v_0. The larger the amplitude, the faster the oscillation damps. It is also found that mass drainage significantly reduces the damping timescale when the perturbation is too strong.Comment: 17 PAGES, 8FIGURE

    An effective scheme for QoS estimation via alternating direction method-based matrix factorization

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    Accurately estimating unknown quality-of-service (QoS) data based on historical records of Web-service invocations is vital for automatic service selection. This work presents an effective scheme for addressing this issue via alternating direction method-based matrix factorization. Its main idea consists of a) adopting the principle of the alternating direction method to decompose the task of building a matrix factorization-based QoS-estimator into small subtasks, where each one trains a subset of desired parameters based on the latest status of the whole parameter set; b) building an ensemble of diversified single models with sophisticated diversifying and aggregating mechanism; and c) parallelizing the construction process of the ensemble to drastically reduce the time cost. Experimental results on two industrial QoS datasets demonstrate that with the proposed scheme, more accurate QoS estimates can be achieved than its peers with comparable computing time with the help of its practical parallelization.This work was supported in part by the FDCT (Fundo para o Desenvolvimento das Ciências e da Tecnologia) under Grant119/2014/A3, in part by the National Natu-ral Science Foundation of China under Grant 61370150, and Grant 61433014; in part by the Young Scientist Foun-dation of Chongqing under Grant cstc2014kjrc-qnrc40005; in part by the Chongqing Research Program of Basic Re-search and Frontier Technology under Grant cstc2015jcyjB0244; in part by the Postdoctoral Science Funded Project of Chongqing under Grant Xm2014043; in part by the Fundamental Research Funds for the Central Universities under Grant 106112015CDJXY180005; in part by the Specialized Research Fund for the Doctoral Pro-gram of Higher Education under Grant 20120191120030

    A Secured Proxy-Based Data Sharing Module in IoT Environments Using Blockchain

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    Access and utilization of data are central to the cloud computing paradigm. With the advent of the Internet of Things (IoT), the tendency of data sharing on the cloud has seen enormous growth. With data sharing comes numerous security and privacy issues. In the process of ensuring data confidentiality and fine-grained access control to data in the cloud, several studies have proposed Attribute-Based Encryption (ABE) schemes, with Key Policy-ABE (KP-ABE) being the prominent one. Recent works have however suggested that the confidentiality of data is violated through collusion attacks between a revoked user and the cloud server. We present a secured and efficient Proxy Re-Encryption (PRE) scheme that incorporates an Inner-Product Encryption (IPE) scheme in which decryption of data is possible if the inner product of the private key, associated with a set of attributes specified by the data owner, and the associated ciphertext is equal to zero 0 . We utilize a blockchain network whose processing node acts as the proxy server and performs re-encryption on the data. In ensuring data confidentiality and preventing collusion attacks, the data are divided into two, with one part stored on the blockchain network and the other part stored on the cloud. Our approach also achieves fine-grained access control

    Probing for cosmological parameters with LAMOST measurement

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    In this paper we study the sensitivity of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) project to the determination of cosmological parameters, employing the Monte Carlo Markov Chains (MCMC) method. For comparison, we first analyze the constraints on cosmological parameters from current observational data, including WMAP, SDSS and SN Ia. We then simulate the 3D matter power spectrum data expected from LAMOST, together with the simulated CMB data for PLANCK and the SN Ia from 5-year Supernovae Legacy Survey (SNLS). With the simulated data, we investigate the future improvement on cosmological parameter constraints, emphasizing the role of LAMOST. Our results show the potential of LAMOST in probing for the cosmological parameters, especially in constraining the equation-of-state (EoS) of the dark energy and the neutrino mass.Comment: 7 pages and 3 figures. Replaced with version accepted for publication in JCA

    Observation of in-gap surface states in the Kondo insulator SmB6 by photoemission

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    Kondo insulators (KIs) are strongly correlated materials in which the interactions between 4f and conduction electrons lead to a hybridization gap opening at low temperature 1-2. SmB6 is a typical KI, but its resistivity does not diverge at low temperatures, which was attributed to some in-gap states 3-10. However after several decades of research, the nature and origin of the in-gap states remain unclear. Recent band calculation and transport measurements suggest that the in-gap states could actually be ascribed to topological surface states. SmB6 thus might be the first realization of topological Kondo insulator (TKI) 13, the strongly correlated version of topological insulator (TI) 11,12. Here by performing angle-resolved photoemission spectroscopy (ARPES), we directly observed several dispersive states within the hybridization gap of SmB6, which cross the Fermi level and show negligible kz dependence, indicative of their surface origin. Furthermore, the circular dichroism (CD) ARPES results of the in-gap states suggest the chirality of orbital momentum, and temperature dependent measurements have shown that the in-gap states vanish simultaneously with the hybridization gap around 150 K. These strongly suggest their possible topological origin.Comment: 18 pages, 8 figure

    New forming method of manufacturing cylindrical parts with nano/ultrafine grained structures by power spinning based on small plastic strains

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    A new spinning method to manufacture the cylindrical parts with nano/ultrafine grained structures is proposed, which consists of quenching, power spinning and recrystallization annealing. The microstructural evolution during the different process stages and macroforming quality of the spun parts made of ASTM 1020 steel are investigated. The results show that the microstructures of the ferrites and pearlites in the ASTM 1020 steel are transformed to the lath martensites after quenching. The martensite laths obtained by quenching are refined to 87 nm and a small amount of nanoscale deformation twins with an average thickness of 20 nm is generated after performing a 3-pass stagger spinning with 55% thinning ratio of wall thickness, where the equivalent strain required is only 0.92. The equiaxial ferritic grains with an average size of 160 nm and nano-carbides are generated by subsequent recrystallization annealing at 480°C for 30 min. The spun parts with high dimensional precision and low surface roughness are obtained by the forming method developed in this work, combining quenching with 3-pass stagger spinning and recrystallization annealing
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