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In this study, blends of poly(lactic acid) (PLA)/linear medium density polyethylene (LMDPE) at different weight ratios were prepared by rotational molding. Two mixing strategies were used to evaluate the effect of phase dispersion on the physical and mechanical properties (i) Dry-blending (DB) using a high shear mixer, and (ii) melt-blending (MB) using a twin-screw extruder. Thermal, morphological, and mechanical analyses were performed on the neat polymers and their blends. The thermal analysis was completed by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), and the blends prepared by MB had lower thermal stability than the ones prepared via DB due to some thermo-oxidative degradation through the double thermal process (extrusion and rotomolding). The morphology of the rotomolded parts showed that DB generated larger particle sizes (around 500 µm) compared to MB (around 5 µm) due to the shear and elongational stresses applied during extrusion. The tensile and flexural properties of the rotomolded parts combined the PLA stiffness with the LMDPE toughness independent of the blending technique. Neat PLA presented increments in tensile strength (54%) and flexural strength (111%) for DB compared with MB. A synergistic effect in impact strength was observed in blends with 12 and 25 wt. % of PLA prepared by DB.The particle filter was popularized in the early 1990s and has been used for solving estimation problems ever since. The standard algorithm can be understood and implemented with limited effort due to the widespread availability of tutorial material and code examples. Extensive research has advanced the standard particle filter algorithm to improve its performance and applicability in various ways in the years after. 1-Methylnicotinamide As a result, selecting and implementing an advanced version of the particle filter that goes beyond the standard algorithm and fits a specific estimation problem requires either a thorough understanding or reviewing large amounts of the literature. The latter can be heavily time consuming especially for those with limited hands-on experience. Lack of implementation details in theory-oriented papers complicates this task even further. The goal of this tutorial is facilitating the reader to familiarize themselves with the key concepts of advanced particle filter algorithms and to select and implement the right particle filter for the estimation problem at hand. It acts as a single entry point that provides a theoretical overview of the filter, its assumptions and solutions for various challenges encountered when applying particle filters. Besides that, it includes a running example that demonstrates and implements many of the challenges and solutions.As modern data analysis pushes the boundaries of classical statistics, it is timely to reexamine alternate approaches to dealing with outliers in multiple regression. As sample sizes and the number of predictors increase, interactive methodology becomes less effective. Likewise, with limited understanding of the underlying contamination process, diagnostics are likely to fail as well. In this article, we advocate for a non-likelihood procedure that attempts to quantify the fraction of bad data as a part of the estimation step. These ideas also allow for the selection of important predictors under some assumptions. As there are many robust algorithms available, running several and looking for interesting differences is a sensible strategy for understanding the nature of the outliers.Myosins play a key role in many cellular processes such as cell migration, adhesion, intracellular trafficking and internalization processes, making them ideal targets for bacteria. Through selected examples, such as enteropathogenic E. coli (EPEC), Neisseria, Salmonella, Shigella, Listeria or Chlamydia, this review aims to illustrate how bacteria target and hijack host cell myosins in order to adhere to the cell, to enter the cell by triggering their internalization, to evade from the cytosolic autonomous cell defense, to promote the biogenesis of intracellular replicative niche, to disseminate in tissues by cell-to-cell spreading, to exit out the host cell, and also to evade from macrophage phagocytosis. It highlights the diversity and sophistication of the strategy evolved by bacteria to manipulate one of their privileged targets, the actin cytoskeleton.It is well known that the need for more environmentally friendly materials concerns, among other fields, the food packaging industry. This regards also, for instance, nets used for agricultural product (e.g., citrus fruits, potatoes) packaging. These nets are typically manufactured by film blowing technique, with subsequent slicing of the films and cold drawing of the obtained strips, made from traditional, non-biodegradable polymer systems. In this work, two biodegradable polymer systems were characterized from rheological, processability, and mechanical points of view, in order to evaluate their suitability to replace polyethylene-based polymer systems typically used for agricultural product net manufacturing. Furthermore, laboratory simulation of the above-mentioned processing operation paths was performed. The results indicated a good potential for biodegradable polymer systems to replace polyethylene-based systems for agricultural product packaging.Detection of traversable areas is essential to navigation of autonomous personal mobility systems in unknown pedestrian environments. However, traffic rules may recommend or require driving in specified areas, such as sidewalks, in environments where roadways and sidewalks coexist. Therefore, it is necessary for such autonomous mobility systems to estimate the areas that are mechanically traversable and recommended by traffic rules and to navigate based on this estimation. In this paper, we propose a method for weakly-supervised recommended traversable area segmentation in environments with no edges using automatically labeled images based on paths selected by humans. This approach is based on the idea that a human-selected driving path more accurately reflects both mechanical traversability and human understanding of traffic rules and visual information. In addition, we propose a data augmentation method and a loss weighting method for detecting the appropriate recommended traversable area from a single human-selected path.