Greenwashing behaviors (GWBs) are positive environmental communications in combination with poor environmental performance. Using fraud triangle theory, this study investigated the effects of three types of factors (pressures, opportunities, and rationalizations) that shape contractor GWBs. Primary data from 586 respondents were analyzed using structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The SEM results indicate positive effects for these factors with the exception of isomorphic pressures and reveal the mediating role of rationalization. The fsQCA results present three configurational models that trigger GWBs. Theoretical and managerial implications are provided that shed new light on facilitating environmental sustainability in projects.
In this study, the effects of rubberwood extractives on the mechanical properties and fungal decay resistance of rubberwood-based wood plastic composites (WPCs) were explored. Three different solvents, benzene-ethanol, methanol, and deionized water, were used to remove the extractives of the rubberwood flour (RWF). The surface topographies of the prepared rubberwood-based WPC and the rubberwood itself were characterized using digital instruments and scanning electron microscopy (SEM). The results indicate that the mechanical properties of the WPC prepared using extracted RWF were higher than those of the WPC prepared with unextracted RWF. The sequences of resistance to the growth of mold on the surface of the WPC were ranked as follows: deionized-water-extracted WPC > methanol-extracted WPC > benzene-ethanol-extracted WPC > unextracted WPC. The WPC made with extracted RWF had better brown-rot resistance and worse white-rot resistance than the unextracted WPC. These results demonstrate that the removal of rubberwood extractives has a positive effect on the mechanical properties and mold and fungal decay resistance of rubberwood-based WPCs.
In this paper, a double nonmonotone quasi-Newton method is proposed for the nonlinear complementarity problem. By using 3-1 piecewise and 4-1 piecewise nonlinear complementarity functions, the nonlinear complementarity problem is reformulated into a smooth equation. By a double nonmonotone line search, a smooth Broyden-like algorithm is proposed, where a single solution of a smooth equation at each iteration is required with the reduction in the scale of the calculation. Under suitable conditions, the global convergence of the algorithm is proved, and numerical results with some practical applications are given to show the efficiency of the algorithm.
As robotics and augmented reality applications increasingly rely on precise and efficient 6D object pose estimation, real-time performance on edge devices is required for more interactive and responsive systems. Our proposed Sparse Color-Code Net (SCCN) embodies a clear and concise pipeline design to effectively address this requirement. SCCN performs pixellevel predictions on the target object in the RGB image, utilizing the sparsity of essential object geometry features to speed up the Perspective-n-Point (PnP) computation process. Additionally, it introduces a novel pixel-level geometry-based object symmetry representation that seamlessly integrates with the initial pose predictions, effectively addressing symmetric object ambiguities. SCCN notably achieves an estimation rate of 19 frames per second (FPS) and 6 FPS on the benchmark LINEMOD dataset and the Occlusion LINEMOD dataset, respectively, for an NVIDIA Jetson AGX Xavier, while consistently maintaining high estimation accuracy at these rates.
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