Development and application starch films: PBAT with additives for evaluating the shelf life of Tommy Atkins mango in the fresh-cut state

In this study, formulations of cassava starch and poly(butylene adipate-co-terephthalate) flexible films were developed, with glycerol, coconut nanocellulose, annatto, and citric acid in different concentrations, as well as the effectiveness of the selected materials in fresh-cut mangoes storage was evaluated. The tensile strength of the different formulations varied from 1.90 (E4) to 6.65 MPa (E3c), and the strain varied from 206.31 (E1c) to 278.41% (E8); this variation was dependent on the percentage of the polymer matrix incorporated. The a_w values of the formulations ranged from 0.396 (E2) to 0.569 (E3c). The Formulations E4 and E7 (with additives) presented good properties and were selected to condition mangoes. The micrographs of these films showed regions of micropores that can facilitate the diffusion of water from the packaged product to the surface, allowing decreases in moisture and a_w, which is associated with higher color maintenance during fruit storage. E7 presented better barrier properties than E4 (lower values of WVP and water solubility) which may have influenced in a positive way to maintain the stability of the package in the studied period. E7 can be considered as a viable alternative for minimally processed mango storage. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48150.     

Complement-Opsonized Nano-Carriers Are Bound by Dendritic Cells (DC) via Complement Receptor (CR)3, and by B Cell Subpopulations via CR-1/2, and Affect the Activation of DC and B-1 Cells

The development of nanocarriers (NC) for biomedical applications has gained large interest due to their potential to co-deliver drugs in a cell-type-targeting manner. However, depending on their surface characteristics, NC accumulate serum factors, termed protein corona, which may affect their cellular binding. We have previously shown that NC coated with carbohydrates to enable biocompatibility triggered the lectin-dependent complement pathway, resulting in enhanced binding to B cells via complement receptor (CR)1/2. Here we show that such NC also engaged all types of splenic leukocytes known to express CR3 at a high rate when NC were pre-incubated with native mouse serum resulting in complement opsonization. By focusing on dendritic cells (DC) as an important antigen-presenting cell type, we show that CR3 was essential for binding/uptake of complement-opsonized NC, whereas CR4, which in mouse is specifically expressed by DC, played no role. Further, a minor B cell subpopulation (B-1), which is important for first-line pathogen responses, and co-expressed CR1/2 and CR3, in general, engaged NC to a much higher extent than normal B cells. Here, we identified CR-1/2 as necessary for binding of complement-opsonized NC, whereas CR3 was dispensable. Interestingly, the binding of complement-opsonized NC to both DC and B-1 cells affected the expression of activation markers. Our findings may have important implications for the design of nano-vaccines against infectious diseases, which codeliver pathogen-specific protein antigen and adjuvant, aimed to induce a broad adaptive cellular and humoral immune response by inducing cytotoxic T lymphocytes that kill infected cells and pathogen-neutralizing antibodies, respectively. Decoration of nano-vaccines either with carbohydrates to trigger complement activation in vivo or with active complement may result in concomitant targeting of DC and B cells and thereby may strongly enhance the extent of dual cellular/humoral immune responses.     

VisualNeuro: A Hypothesis Formation and Reasoning Application for Multi-Variate Brain Cohort Study Data

We present an application, and its development process, for interactive visual analysis of brain imaging data and clinical measurements. The application targets neuroscientists interested in understanding the correlations between active brain regions and physiological or psychological factors. The application has been developed in a participatory design process and has subsequently been released as the free software ‘VisualNeuro’. From initial observations of the neuroscientists' workflow, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration requiring the use of many tools side by side. Consequently, our application has been designed to simplify the workflow combining statistical analysis with interactive visual exploration. The resulting environment comprises parallel coordinates for effective overview and selection, Welch's t-test to filter out brain regions with statistically significant differences and multiple visualizations for comparison between brain regions and clinical parameters. These exploration concepts enable neuroscientists to interactively explore the complex bidirectional interplay between clinical and brain measurements and easily compare different patient groups. A qualitative user study has been performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights and is an effective tool for hypothesis formation.     

Adaptive infill sampling criterion for multi-fidelity optimization based on Gappy-POD

This paper presents a reformulation of the “Gappy Proper Orthogonal Decomposition” (Gappy-POD) multi-fidelity modeling approach and proposes an enrichment criterion associated with an adaptive infill algorithm. The latter is here applied to the study of the flight domain of the RAE-2822 transonic airfoil at two different levels of accuracy to demonstrate its ability to detect areas in a two-dimensional design space where the surrogate model needs improvement to better drive the optimization process.     

Combining formal concept analysis and translation to assign frames and semantic role sets to French verbs

In Natural Language Processing, verb classifications have been shown to be useful both theoretically (to capture syntactic and semantic generalisations about verbs) and practically (to support factorisation and the supervised learning of shallow semantic parsers). Acquiring such classifications manually is both costly and errror prone however. In this paper, we present a novel approach for automatically acquiring verb classifications. The approach uses FCA to build a concept lattice from existing linguistic resources; and stability and separation indices to extract from this lattice those concepts that most closely capture verb classes. The approach is evaluated on an established benchmark and shown to differ from previous approaches and in particular, from clustering approaches, in two main ways. First, it supports polysemy (because a verb may belong to several classes). Second, it naturally provides a syntactic and semantic characterisation of the verb classes produced (by creating concepts which systematically associate verbs with their syntactic and semantic attributes).     

Cross‐talk acceptability in natural still images for different (auto)stereoscopic display technologies

Abstract— One of the most annoying distortions in (auto)stereoscopic displays is probably cross‐talk, visible as double edges, which is mainly caused by an imperfect separation of left‐ and right‐eye images. For different types of three‐dimensional (3‐D) displays, cross‐talk is caused by different origins, which could result in different levels of perceived image distortion. To evaluate the influence of (auto)stereoscopic display technology on cross‐talk perception, optical measurements and subjective assessments were performed with three different types of 3‐D displays. It is shown with natural still images that the 3‐D display technology with the lowest luminance and contrast level tolerates the highest level of cross‐talk, while still maintaining an acceptable image‐quality level.     

Information‐driven robotic sampling in the coastal ocean

Efficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic sampling with ocean models provides an effective approach to adaptively sample such features. We present methods that capitalize on information from ocean models and in situ measurements, using Gaussian process modeling and objective functions, allowing sampling efforts to be concentrated to regions with high scientific interest. We demonstrate how to combine and correlate marine data from autonomous underwater vehicles, model forecasts, remote sensing satellite, buoy, and ship‐based measurements, as a means to cross‐validate and improve ocean model accuracy, in addition to resolving upper water‐column interactions. Our work is focused on the west coast of Mid‐Norway where significant influx of Atlantic Water produces a rich and complex physical–biological coupling, which is hard to measure and characterize due to the harsh environmental conditions. Results from both simulation and full‐scale sea trials are presented.     

Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology

In this work, we propose a controlled simplification strategy for degenerated points in symmetric 2D tensor fields that is based on the topological notion of robustness. Robustness measures the structural stability of the degenerate points with respect to variation in the underlying field. We consider an entire pipeline for generating a hierarchical set of degenerate points based on their robustness values. Such a pipeline includes the following steps: the stable extraction and classification of degenerate points using an edge labeling algorithm, the computation and assignment of robustness values to the degenerate points, and the construction of a simplification hierarchy. We also discuss the challenges that arise from the discretization and interpolation of real world data.