Disintegrability under composting conditions of plasticized PLA–PHB blends

The disintegration under composting conditions of films based on poly(lactic acid)–poly(hydroxybutyrate) (PLA–PHB) blends and intended for food packaging was studied. Two different plasticizers, poly(ethylene glycol) (PEG) and acetyl-tri-n-butyl citrate (ATBC), were used to limit the inherent brittleness of both biopolymers. Neat PLA, plasticized PLA and PLA–PHB films were processed by melt-blending and compression molding and they were further treated under composting conditions in a laboratory-scale test at 58 ± 2 °C. Disintegration levels were evaluated by monitoring their weight loss at different times: 0, 7, 14, 21 and 28 days. Morphological changes in all formulations were followed by optical and scanning electron microscopy (SEM). The influence of plasticizers on the disintegration of PLA and PLA–PHB blends was studied by evaluating their thermal and nanomechanical properties by thermogravimetric analysis (TGA) and the nanoindentation technique, respectively. Meanwhile, structural changes were followed by Fourier transformed infrared spectroscopy (FTIR). The ability of PHB to act as nucleating agent in PLA–PHB blends slowed down the PLA disintegration, while plasticizers speeded it up. The relationship between the mesolactide to lactide forms of PLA was calculated with a Pyrolysis–Gas Chromatography–Mass Spectrometry device (Py–GC/MS), revealing that the mesolactide form increased during composting.

Geometric 3D point cloud compression

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment but usually the huge amount of 3D information is unmanageable by the robot storage and computing capabilities. A data compression is necessary to store and manage this information but preserving as much information as possible. In this paper, we propose a 3D lossy compression system based on plane extraction which represent the points of each scene plane as a Delaunay triangulation and a set of points/area information. The compression system can be customized to achieve different data compression or accuracy ratios. It also supports a color segmentation stage to preserve original scene color information and provides a realistic scene reconstruction. The design of the method provides a fast scene reconstruction useful for further visualization or processing tasks.

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.

3DCOMET: 3D compression methods test dataset

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment. However usually the huge amount of 3D information is difficult to manage due to the fact that the robot storage system and computing capabilities are insufficient. Therefore, a data compression method is necessary to store and process this information while preserving as much information as possible. A few methods have been proposed to compress 3D information. Nevertheless, there does not exist a consistent public benchmark for comparing the results (compression level, distance reconstructed error, etc.) obtained with different methods. In this paper, we propose a dataset composed of a set of 3D point clouds with different structure and texture variability to evaluate the results obtained from 3D data compression methods. We also provide useful tools for comparing compression methods, using as a baseline the results obtained by existing relevant compression methods.