Eumelanin for nature‐inspired UV‐absorption enhancement of plastics

In the human body, the black‐brown biopigment eumelanin blocks harmful ultraviolet (UV) radiation. In the plastics industry, additives are often added to polymers to increase their UV‐absorption properties. We herein report an assessment of the biopigment eumelanin as a nature‐inspired additive for plastics to enhance their UV absorption. Since eumelanin is produced by natural sources and is nontoxic, it is an interesting candidate in the field of sustainable plastic additives. In this work, the eumelanin‐containing films of commercial ethylene–vinyl acetate copolymer, a plastic used for packaging applications, were obtained by melt compounding and compression molding. The biopigment dispersion in the films was improved by means of the melanin free acid treatment. It was observed that eumelanin amounts as low as 0.8 wt% caused an increase of the UV absorption, up to one order of magnitude in the UVA range. We also evaluated the effect of eumelanin on the thermal stability and photostability of the films: the biopigment proved to be double‐edged, working both as UV‐absorption enhancer and photo‐prooxidant, as thermogravimetric analysis and infrared spectroscopy revealed. © 2019 Society of Chemical Industry     

Chitosan impregnated gutta-percha points: antimicrobial in vitro evaluation and mechanical properties

Chitosan-impregnated gutta-percha points (ChitGPP) were tested for their ability to inhibit the growth of microorganisms usually involved in root canal infections. Their mechanical properties were also studied and compared with the commonly used commercial points in endodontics. ChitGPP were more efficient in reducing the microbial load than those without chitosan. ChitGPP also possess better tensile and elastic properties than commercial ones. After six months of storage, ChitGPP’s were still able to reduce the bacterial load by 1 log, suggesting that impregnation of gutta-percha points with chitosan could be a good alternative to obtain gutta-percha points with improved antimicrobial properties.     

Case-base maintenance with multi-objective evolutionary algorithms

Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solving ability of the Case-Base Reasoning system. However, when the case-base has many cases, then performance problems arise due to the time needed to find those similar cases to the input problem. At this point, Case-Base Maintenance algorithms can be used to reduce the number of cases and maintain the accuracy of the Case-Base Reasoning system at the same time. Whereas Case-Base Maintenance algorithms typically use a particular heuristic to remove (or select) cases from the case-base, the resulting maintained case-base relies on the proportion of redundant and noisy cases that are present in the case-base, among other factors. That is, a particular Case-Base Maintenance algorithm is suitable for certain types of case-bases that share some indicators, such as redundancy and noise levels. In the present work, we consider Case-Base Maintenance as a multi-objective optimization problem, which is solved with a Multi-Objective Evolutionary Algorithm. To this end, a fitness function is introduced to measure three different objectives based on the Complexity Profile model. Our hypothesis is that the Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance may be used in a wider set of case-bases, achieving a good balance between the reduction of cases and the problem-solving ability of the Case-Based Reasoning system. Finally, from a set of the experiments, our proposed Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance shows regularly good results with different sets of case-bases with different proportion of redundant and noisy cases.     

Evaluation of alternatives for the broadcast operation in Kademlia under churn

During recent years, considerable effort has been devoted to the enhancement of Distributed Hash Table (DHT) systems with broadcasting capabilities. Such systems typically provide individual node routing but a broadcast primitive is required for functionalities such as information dissemination or data aggregation. Broadcasting can also be used as the basis for partial keyword searches. Little work has however specifically addressed Kademlia, a well known DHT, used in real applications. Our work exposes the particularities of this system, notably its XOR-based distance metrics, and analytically studies what broadcasting techniques can be applied to it. A model that estimates node coverage as a function of the probability that individual messages reach their destination has been also developed. For validation, several broadcasting algorithms have been implemented and comprehensively evaluated, considering node coverage, messages to nodes ratio, latency and imbalance factor. Moreover, several techniques are proposed to enhance the bare protocols when adverse circumstances such as churn and failure rate conditions are present. These include redundancy, resubmissions or flooding, and also combinations of those. All have been implemented and fully tested. An analysis of the strengths and weaknesses of algorithms and additional techniques, and a discussion on the choices and compromises to make, depending on system characteristics or application priorities, is finally presented.     

I-Competere: Using applied intelligence in search of competency gaps in software project managers

People in software development teams are crucial in order to gain and retain strategic advantage inside a highly competitive market. As a result, human factors have gained attention in the software industry. Software Project Managers are decisive to achieve project success. A competent project manager is capable of solving any problem that an organization may encounter, regardless of its complexity. This paper presents I-Competere which is a tool developed to forecast competence gaps in key management personnel by predicting planning and scheduling competence levels. Based on applied intelligence techniques, I-Competere allows the forecast and anticipation of competence needs thus articulating personnel development tools and techniques. The results of the test, using several artificial neural networks, are more than promising and show prediction accuracy.     

Leachability of degradation products from hard chairside reline resins in artificial saliva: Effect of water‐bath post‐polymerization treatment

The effect of a post‐polymerization treatment on the leaching of methacrylic acid (MA) and benzoic acid (BA) from the reline resins [Kooliner (K), New Truliner (N), Ufi Gel hard (U), and Tokuso Rebase Fast (T)] was evaluated. Specimens of each material were divided into two groups: Group C (control) – left untreated; Group WB (water‐bath) – immersion in water at 55 ± 1°C for 10 min. Specimens were placed in artificial saliva at 37 ± 1°C and, after 1‐, 3‐, 5‐, 24‐h and 3‐, 7‐, 14‐, and 30‐day intervals, aliquots were removed and analyzed using high performance liquid chromatography. Data were analyzed by using Wilcoxon, Mann–Whitney or Kruskal–Wallis tests (α = 0.05). At 1 h, the concentration of MA released from U control specimens was higher than those of the other ones, and decreased after 3 h. WB specimens released lower amounts of MA than control specimens only for material U, at the 1‐ and 3‐h periods. For all control specimens, concentrations of leached BA progressively decreased within 5 h and from 24 h to the end. WB specimens released significantly lower amounts of BA than did the control groups. The highest concentration of MA was leached from control specimens of Ufi Gel hard. Water‐bath post‐polymerization treatment caused a significant reduction in elution of BA. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Augmented reality annotations to assist persons with Alzheimers and their caregivers

Persons with Alzheimer’s disease (AD) and their caregivers implement diverse strategies to cope with memory loss. A common strategy involves placing tags on drawers or removing cabinet doors to make their contents visible. This study describes the Ambient aNnotation System (ANS), aimed at assisting people suffering from AD and their caregivers with this task. The system has two main modules: The tagging subsystem allows caregivers to create and manage ambient annotations in order to assist people with memory problems. The second subsystem allows people with AD to use a mobile phone to recognize tags in the environment and to receive relevant information in the form of audio, text, or images. The identification of these tags is performed in real time by uploading images from the mobile phone to a server, which uses the SURF algorithm for object recognition. We describe the design and implementation of the system as well as results of the evaluation of its performance and efficiency. ANS can process query images approximately every 2 s and is able to locate users in their homes with a precision of 0.93. A usability study conducted with six subjects determined that audio notifications are more effective than vibrating notifications to alert the user about tags in the environment.