Sustainable disassembly line balancing model based on triple bottom line

End of life (EOL) phase of a product is receiving more attention due to increase in environmental concerns, and many studies have been conducted for value creation in EOL, focusing on concepts as remanufacturing, reuse and recycling in sustainable production manner. This study especially focuses on one of global problem, e-waste. To minimise the amount of wastes and maximise recovered materials from EOL, disassembly is one of the most important concept, associated with reuse, and balancing disassembly line in an optimal way is essential for organisations. In disassembly line balancing (DLB), not only precedence of tasks, but also risk criteria related to environment and human safety should be considered for sustainability. The aim of this study is to propose a model based on triple bottom line (TBL) dimensions, i.e. human safety, environmental safety and business criteria. To achieve sustainability in DLB, and for risk assessment in sustainable DLB, it had been decided to use a multi-criteria method, i.e. TODIM, acronym in Portuguese of ‘Tomada de Decisão Iterativa Multicritério’. The proposed model included 22 disassembly criteria categorised under TBL dimensions, which are derived from the literature. Implementation of the study was conducted for computer disassembly processes, and as a result of the study approximately 12% an improvement in cycle time was succeeded. In the long run, the integration of sustainability in disassembly operations may contribute to the competitive advantage of the company in terms of differentiation and corporate image by achieving business, environment and human targets simultaneously.     

Characterisation of interfaces in nanocrystalline palladium

Structures of grain boundaries and triple line junctions in nanocrystalline materials are of interest owing to large fractions of atoms in nanocrystalline materials being at these interfacial positions. Grain boundary and triple line junction structures in nanocrystalline palladium have been studied using high-resolution transmission electron microscopy (HRTEM). The main micro structural features observed include the varying atomic structures of grain boundaries and the presence of disordered regions at triple line junctions. Also, there is variation in lattice parameters in different nanocrystalline grains. Geometric phase analysis is used to quantify atomic displacements within nanocrystalline grains. Displacement fields thus detected indicate links to the interface structures.     

X射线三轴晶衍射法测量半绝缘GaAs单晶的化学配比

采用X射线三轴晶衍射法,根据As间隙原子对作为过量As在GaAs单晶材料中存在的主要形式的模型,可以无损、高精度测量半绝缘GaAs单晶的化学配比.并探讨了引起晶格变化的原因及其与熔体组分的关系,对于制备高质量GaAs单晶及其光电器件具有重要的意义.     

Influence of numerical and viscous dissipation on shock wave reflections in supersonic steady flows

Numerical simulations are investigated to describe precisely the shock wave reflections in supersonic steady air flow field. The main objectives are to study the influence of the wedge trailing edge corner angle, of the numerical methods and of the viscous effects on the shock wave reflections and on the hysteresis behavior. The computations are done with different MUSCL-TVD finite volume schemes and the corresponding results are compared. The flow viscosity is also taken into account and comparisons are made between inviscid and viscous flow simulations. The results display the non-negligible influence of the numerical scheme accuracy on the results, mainly on the position and height of the Mach stem, and the relatively weak influence of the flow viscosity on these parameters. Comparisons between numerical results and experimental data have also been done and a good agreement is only observed for small wedge angles mainly due to the three-dimensional effects in the experimental setup.     

PVT Measurements on tetrafluoroethane (R134a) along the vapor-liquid equilibrium boundary between 288 and 373 K and in the liquid state from the triple point to 265 K

For the investigations of the gas-liquid phase equilibria, a new apparatus has been developed capable of simultaneously determining the pressure and the liquid and vapor densities using Archimedes' principle. The relative measurement uncertainties of the liquid and vapor densities of R134a (purity, 99.999%) at 313 K are 2×10^–4 and 7×10^–4, respectively (95% confidence level). For the measurements in the liquid region along nine quasi-isochores at pressures up to 5 MPa, an isochoric apparatus was used. The relative measurement uncertainty ofpv/(RT) is less than 1×10^–3. In addition to the investigation of the (p, v, T) properties, the temperature and pressure at the triple point and the vapor pressure between the triple point and 265 K were measured. On the basis of these data, a vapor pressure correlation has been developed that reproduces the measured vapor pressures within the uncertainty of measurement. The results of our measurements are compared with a fundamental equation for R134a, which is based on the measurements of other research groups.Paper presented at the Twelfth Symposium on Thermophysical Properties, June 19–24, 1994, Boulder, Colorado, U.S.A.     

Estimation of true dihedral angles and relative grain boundary energies in polycrystals using the disector

Relative grain boundary energies can be simply related to true dihedral angles, which are the angles between grain boundary planes meeting at triple edges in polycrystals. Some limited efforts in the measurement of true dihedral angles have used the technique of serial sectioning, which is usually cumbersome and time consuming. In this study the three‐dimensional probe called the ‘disector’ has been employed to evaluate true dihedral angles. This probe, combined with automated image processing, introduces precision as well as efficiency, overcomes the disadvantages of the two‐dimensional probe and is far less tedious and less complicated than serial sectioning. It is shown that the technique is relatively simple and therefore can be applied to obtain a significantly large and accurate statistical sample of true dihedral angles. The application of this method is demonstrated by evaluating the triple junction geometry and the associated relative grain boundary energies in polycrystalline 316L austenitic stainless steel.     

Plasticity of feature-based selection in triple-conjunction search.

Two experiments examined the disruption of feature-based selection in triple-conjunction search at multiple target transfers. In Experiment 1, after 10 training sessions, a new target possessing previous distractor features was introduced. This produced disruption in RT and fixation number, but no disruption in feature-based selection. Specifically, there was a tendency to fixate objects sharing the target's contrast polarity and shape and this did not change even upon transfer to the new target. In Experiment 2, 30 training sessions were provided with three target transfers. At the first transfer, the results replicated Experiment 1. Subsequent transfers did not produce disruption on any measure. These findings are discussed in terms of strength theory, Guided Search, rule-based approaches to perceptual learning, and the area activation model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

重积分计算方法的一个注记

三重积分与三次积分的意义是不相同的。但是在一定条件下三重积分可以转化为三次累次积分来计算,其公式为:■     

Cross lingual speech emotion recognition via triple attentive asymmetric convolutional neural network

The application of cross‐corpus for speech emotion recognition (SER) via domain adaptation methods have gain high acknowledgment for developing good robust emotion recognition systems using different corpora or datasets. However, the issue of cross‐lingual still remains a challenge in SER and needs more attention to resolve the scenario of applying different language types in both training and testing. In this paper, we propose a triple attentive asymmetric convolutional neural network to address the recognition of emotions for cross‐lingual and cross‐corpus speech in an unsupervised approach. The proposed method adopts the joint supervision of softmax loss and center loss to learn high power discriminative feature representations for target domain via the use of high quality pseudo‐labels. The proposed model uses three attentive convolutional neural networks asymmetrically, where two of the networks are used to artificially label unlabeled target samples as a result of their predictions from training on source labeled samples and the other network is used to obtain salient target discriminative features from the pseudo‐labeled target samples. We evaluate our proposed method on three different language types (i.e., English, German, and Italian) data sets. The experimental results indicate that, our proposed method achieves higher prediction accuracy over other state‐of‐the‐art methods.     

Supramolecular Nanofibers from Collagen-Mimetic Peptides Bearing Various Aromatic Groups at N-Termini via Hierarchical Self-Assembly

Self-assembly of artificial peptides has been widely studied for constructing nanostructured materials, with numerous potential applications in the nanobiotechnology field. Herein, we report the synthesis and hierarchical self-assembly of collagen-mimetic peptides (CMPs) bearing various aromatic groups at the N-termini, including 2-naphthyl, 1-naphtyl, anthracenyl, and pyrenyl groups, into nanofibers. The CMPs (R-(GPO)_n: n > 4) formed a triple helix structure in water at 4 °C, as confirmed via CD analyses, and their conformations were more stable with increasing hydrophobicity of the terminal aromatic group and peptide chain length. The resulting pre-organized triple helical CMPs showed diverse self-assembly into highly ordered nanofibers, reflecting their slight differences in hydrophobic/hydrophilic balance and configuration of aromatic templates. TEM analysis demonstrated that 2Np-CMP_n (n = 6 and 7) and Py-CMP₆ provided well-developed natural collagen-like nanofibers and An-CMP_n (n = 5–7) self-assembled into rod-like micelle fibers. On the other hand, 2Np-CMP₅ and 1Np-CMP₆ were unable to form nanofibers under the same conditions. Furthermore, the Py-CMP₆ nanofiber was found to encapsulate a guest hydrophobic molecule, Nile red, and exhibited unique emission behavior based on the specific nanostructure. In addition to the ability of CMPs to bind small molecules, their controlled self-assembly enables their versatile utilization in drug delivery and wavelength-conversion nanomaterials.