Chitin Nanocomposite Based on Plasticized Poly(lactic acid)/Poly(3-hydroxybutyrate) (PLA/PHB) Blends as Fully Biodegradable Packaging Materials

Fully bio-based poly(lactic acid) (PLA) and poly(3-hydroxybutyrate) (PHB) blends plasticized with tributyrin (TB), and their nanocomposite based on chitin nanoparticles (ChNPs) was developed using melt mixing followed by a compression molding process. The combination of PHB and ChNPs had an impact on the crystallinity of the plasticized PLA matrix, thus improving its oxygen and carbon dioxide barrier properties as well as displaying a UV light-blocking effect. The addition of 2 wt% of ChNP induced an improvement on the initial thermal degradation temperature and the overall migration behavior of blends, which had been compromised by the presence of TB. All processed materials were fully disintegrated under composting conditions, suggesting their potential application as fully biodegradable packaging materials

Argumentation for explainable reasoning with conflicting medical recommendations

Designing a treatment path for a patient suffering from mul- tiple conditions involves merging and applying multiple clin- ical guidelines and is recognised as a difficult task. This is especially relevant in the treatment of patients with multiple chronic diseases, such as chronic obstructive pulmonary dis- ease, because of the high risk of any treatment change having potentially lethal exacerbations. Clinical guidelines are typi- cally designed to assist a clinician in treating a single condi- tion with no general method for integrating them. Addition- ally, guidelines for different conditions may contain mutually conflicting recommendations with certain actions potentially leading to adverse effects. Finally, individual patient prefer- ences need to be respected when making decisions. In this work we present a description of an integrated frame- work and a system to execute conflicting clinical guideline recommendations by taking into account patient specific in- formation and preferences of various parties. Overall, our framework combines a patient’s electronic health record data with clinical guideline representation to obtain personalised recommendations, uses computational argumentation tech- niques to resolve conflicts among recommendations while re- specting preferences of various parties involved, if any, and yields conflict-free recommendations that are inspectable and explainable. The system implementing our framework will allow for continuous learning by taking feedback from the decision makers and integrating it within its pipeline

Influence of organically modified clays on the properties and disintegrability in compost of solution cast poly(3-hydroxybutyrate) films

Polymer nanocomposites, based on a bacterial biodegradable thermoplastic polyester, poly(hydroxybutyrate) (PHB), and unmodified montmorillonite Cloisite Na+ (CNa) and chemically modified Cloisite 15A and 93A (C15A and C93A), were prepared through a solution route. The nanostructure has been established through X-ray diffraction (XRD), while the nanocomposites were characterized by differential scanning calorimetry (DSC), contact angle measurements, and thermogravimetric (TGA) analysis. Disintegrability in composting conditions has been tested at certain times (0, 7, 14, 21, 28 and 35 days at 58 C) and the effect of different nanoclays on the properties of biodegraded films was deeply investigated. XRD results suggest a better dispersion for C15A and C93A based nanocomposites that present also a more surface hydrophobic nature respect to PHB matrix and PHB nanocomposite loaded with unmodified Cloisite. This result is in accord with disintegrability behavior of PHB nanocomposites. Visual observation, chemical, thermal and morphological investigations proved that the disintegration in composting conditions was faster for PHB-4CNa respect to the systems loaded with modified clays suggesting the possibility to modulate the disintegrability capacity of PHB selecting a specific filler. © 2013 Elsevier Ltd. All rights reserved.Peer Reviewe