重新思考包装生产、消费和循环经济:以可分解木薯淀粉作基础材料为例

在主导的工业经济中,包装废物在城市固体废物产生中占有相当大的比例(～20.0%在欧洲和美国),对环境造成负面影响。从主导的线性经济向以意图和设计为基础的循环经济模式的转变,可以为市场经济和包装利用奠定新的基础。本研究探讨包装生产与消费相对于循环经济的关系。为实现这一目标,它包括(i)硬包装产品的生命周期库存分析,讨论原材料和产品的产量,水和能源的使用,以及温室气体的排放;(ii)木薯淀粉基材料的案例研究,以及(iii)石油基包装和木薯淀粉基包装的比较分析。结果表明,木薯淀粉的可降解包装比石油包装具有更好的社会和环境效益。从线性的(获取制造-使用-处理)模式到循环的(增长-制造-使用-恢复)模式的转变为技术之外的创新创造了新的机会,因为它不可避免地重新定义了浪费、产品、服务、市场、自然资本和增长的重要性。解决以石油为基础的包装工业的温室气体排放问题,社会采用以生物为基础的木薯淀粉包装是一项有效和有前途的减缓气候变化战略。     

Tunable Fano Resonance and Plasmon–Exciton Coupling in Single Au Nanotriangles on Monolayer WS2 at Room Temperature

Tunable Fano resonances and plasmon–exciton coupling are demonstrated at room temperature in hybrid systems consisting of single plasmonic nanoparticles deposited on top of the transition metal dichalcogenide monolayers. By using single Au nanotriangles (AuNTs) on monolayer WS₂ as model systems, Fano resonances are observed from the interference between a discrete exciton band of monolayer WS₂ and a broadband plasmonic mode of single AuNTs. The Fano lineshape depends on the exciton binding energy and the localized surface plasmon resonance strength, which can be tuned by the dielectric constant of surrounding solvents and AuNT size, respectively. Moreover, a transition from weak to strong plasmon–exciton coupling with Rabi splitting energies of 100–340 meV is observed by rationally changing the surrounding solvents. With their tunable plasmon–exciton interactions, the proposed WS₂–AuNT hybrids can open new pathways to develop active nanophotonic devices.     

Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem

The problem of merging multiple databases of information about common entities is frequently encountered in KDD and decision support applications in large commercial and government organizations. The problem we study is often called the Merge/Purge problem and is difficult to solve both in scale and accuracy. Large repositories of data typically have numerous duplicate information entries about the same entities that are difficult to cull together without an intelligent equational theory that identifies equivalent items by a complex, domain-dependent matching process. We have developed a system for accomplishing this Data Cleansing task and demonstrate its use for cleansing lists of names of potential customers in a direct marketing-type application. Our results for statistically generated data are shown to be accurate and effective when processing the data multiple times using different keys for sorting on each successive pass. Combing results of individual passes using transitive closure over the independent results, produces far more accurate results at lower cost. The system provides a rule programming module that is easy to program and quite good at finding duplicates especially in an environment with massive amounts of data. This paper details improvements in our system, and reports on the successful implementation for a real-world database that conclusively validates our results previously achieved for statistically generated data.     

Hammerstein system identification through best linear approximation inversion and regularisation

Hammerstein systems are composed by the cascading of a static nonlinearity and a linear system. In this paper, a methodology for identifying such systems using a combination of least squares support vector machines (LS-SVM) and best linear approximation (BLA) techniques is proposed. To do this, a novel method for estimating the intermediate variable is presented allowing a clear separation of the identification steps. First, an approximation to the linear block is obtained through the BLA of the system. Then, an approximation to the intermediate variable is obtained using the inversion of the estimated linear block and the known output. Afterwards, a nonlinear model is calculated through LS-SVM using the estimated intermediate variable and the known input. To do this, the regularisation capabilities of LS-SVM play a crucial role. Finally, a parametric re-estimation of the linear block is made. The method was tested in three examples, two of them with hard nonlinearities, and was compared with four other methods showing very good performance in all cases. The obtained results demonstrate that also in the presence of noise, the method can effectively identify Hammerstein systems. The relevance of these findings lies in the fact that it is shown how the regularisation allows to bypass the usual problems associated with the noise backpropagation when the inversion of the estimated linear block is used to compute the intermediate variable.     

Impulse response constrained LS-SVM modelling for MIMO Hammerstein system identification

In this paper, a new methodology for identifying multiple inputs multiple outputs Hammerstein systems is presented. The proposed method aims at incorporating the impulse response of the system into a least-squares support vector machine (LS-SVM) formulation and therefore the regularisation capabilities of LS-SVM are applied to the system as a whole. One of the main advantages of this method comes from the fact that it is flexible concerning the class of problems it can model and that no previous knowledge about the underlying non-linearities is required except for very mild assumptions. Also, it naturally adapts to handle different numbers of inputs/outputs and performs well in the presence of white Gaussian noise. Finally, the method incorporates information about the structure of the system but still the solution of the model follows from a linear system of equations. The performance of the proposed methodology is shown through three simulation examples and compared with other methods in the literature.     

Parametric study of acoustic focusing of particles in a micro-channel in the perspective to improve micro-PIV measurements

In this study, we propose a new technique to bring most of the particles in a horizontal plane at mid-height of a micro-channel in order to improve the quality of the micro-PIV measurements. The basic principle is to create a stationary acoustic wave along the channel height so that the resulting acoustic force moves the particles toward the pressure node. A parametric study has been carried out without mean flow to characterize the motion of the particles toward the nodal-plane. We found that focusing speed grows with the acoustic pressure amplitude, with the concentration of particles in the suspension and with the particles diameter. We also led a preliminary investigation of acoustic focusing together with a mean stationary flow. We still observed an important focusing of particles for low freestream velocities. Nevertheless, acoustic focusing is inefficient beyond a given critical freestream velocity U ₀ for a given set of acoustic parameters and a given type of particles. It was also shown that other phenomena, like clumps formation, can be observed without mean flow if the acoustic focusing lasts long enough.     

Incentive contrast in domestic dogs (Canis familiaris).

Dogs (Canis familiaris) trained to receive a preferred food (dry beef liver) from an experimenter learned to maintain a longer gaze on the experimenter than dogs receiving a less preferred food (dog pellets). Dogs downshifted from dry liver to pellets rejected food more frequently than nonshifted controls. Gaze duration also decreased in downshifted dogs below the level of a group always reinforced with pellets. In addition, downshifted dogs tended to move away from the experimenter, adopting a lying down posture. This phenomenon, called successive negative contrast, has been described in analogous experiments with a variety of mammalian species, but has failed to occur in similar experiments with nonmammalian vertebrates. Unlike similar previous observations, the present data were obtained in an environment involving interspecific communication. (PsycINFO Database Record (c) 2010 APA, all rights reserved)