Characterization and properties of blended cement matrices containing activated bamboo leaf wastes

The worldwide production of bamboo generates large volumes of leaf wastes, which are deposited in landfills or burned in an uncontrolled manner, with negative effects in the environment. The ash obtained by calcining of the bamboo leaf waste, shows good qualities as supplementary cementing material for the production of blended cements.The current paper shows a detailed scientific study of a Brazilian bamboo leaf ash (BLA) calcined at 600 °C in small scale condition, by using different techniques (XRF, XRD, SEM/EDX, FT–IR, TG/DTG) and technical study in order to analyse the behaviour of this ash in blended cements elaborated with 10% and 20% by mass of BLA. The results stated that this ash shows a very high pozzolanic activity, with a reaction rate constant K of the order of 10^?1/h and type I CSH gel was the main hydrated phase obtained from pozzolanic reaction. The BLA blended cements (10% and 20%) complied with the physical and mechanical requirements of the existing European standards.     

A spatial relation-based framework to perform visual information extraction

The Spatial Relation Query (SRQ) tool is a graphical software environment, supported by a SQL-like language, which enables users to perform information extraction driven by the visual appearance and the spatial arrangement of the information. The tool has been initially customised to work on specific application domains, like web pages and geospatial data. In this paper, we present the theoretical formalisation of the visual information extraction (VIE) task and accordingly the redesign of the SRQ tool, which is now a full-featured, general-purpose information extraction system. Moreover, we show a new application of the VIE framework to the analysis and visual information extraction from PDF files.     

Subspace Procrustes Analysis

Procrustes analysis (PA) has been a popular technique to align and build 2-D statistical models of shapes. Given a set of 2-D shapes PA is applied to remove rigid transformations. Later, a non-rigid 2-D model is computed by modeling the residual (e.g., PCA). Although PA has been widely used, it has several limitations for modeling 2-D shapes: occluded landmarks and missing data can result in local minima solutions, and there is no guarantee that the 2-D shapes provide a uniform sampling of the 3-D space of rotations for the object. To address previous issues, this paper proposes subspace PA (SPA). Given several instances of a 3-D object, SPA computes the mean and a 2-D subspace that can model rigid and non-rigid deformations of the 3-D object. We propose a discrete (DSPA) and continuous (CSPA) formulation for SPA, assuming that 3-D samples of an object are provided. DSPA extends the traditional PA, and produces unbiased 2-D models by uniformly sampling different views of the 3-D object. CSPA provides a continuous approach to uniformly sample the space of 3-D rotations, being more efficient in space and time. We illustrate the benefits of SPA in two different applications. First, SPA is used to learn 2-D face and body models from 3-D datasets. Experiments on the FaceWarehouse and CMU motion capture (MoCap) datasets show the benefits of our 2-D models against the state-of-the-art PA approaches and conventional 3-D models. Second, SPA learns an unbiased 2-D model from CMU MoCap dataset and it is used to estimate the human pose on the Leeds Sports dataset.     

Reversible Fragmentation and Self‐Assembling of Nematic Liquid Crystal Droplets on Functionalized Pyroelectric Substrates

Investigation on the behavior of nematic liquid crystals on functionalized polar dielectric crystal substrates is accomplished. Very interesting effects can be observed in maneuvering liquid crystal droplets on the substrate surface, driven by electric fields generated by pyroelectric effect. Reversible drops fragmentation and self‐assembling in different configurations can be achieved. The dynamics of the observed phenomena is studied and the repeatability of the process is full assessed.     

Postharvest performance of fresh‐cut ‘Big Top’ nectarine as affected by dipping in chemical preservatives and packaging in modified atmosphere

Fresh‐cut ‘Big Top’ nectarines were dipped in 2% (w/v) ascorbic acid–1% (w/v) calcium lactate and stored at 4 °C for up to 12 days in 10 kPa O₂‐ and 10 kPa CO₂‐modified atmosphere packaging (MAP). The used microperforated plastic film allowed O₂ and CO₂ concentrations to reach steady values from the fifth day in storage onwards. Samples stored in MAP after chemical dipping showed the highest visual quality score, slight browning symptoms, increment in firmness and very low ethanol and acetaldehyde content. The chemical dipping also increased antioxidant capacity, probably due to the effect of ascorbic acid. The results suggested that the control of yeasts was mainly exerted by MAP, whereas only a slight effect was achieved by the chemical dipping. Therefore, MAP plus ascorbic acid/calcium lactate dipping was the best combination to preserve phytochemical content, antioxidant capacity and microbiological safety of fresh‐cut nectarines during storage.     

Modeling and Simulation of Large Microstructured Particles in Magnetic‐Shape‐Memory Composites

We study composite materials in which single‐crystalline magnetic shape‐memory particles are embedded in a polymer matrix, in the limit of particles much larger than the typical domain size. We first derive an effective macroscopic model, using the mathematical theory of relaxation, and then solve it numerically for practically relevant parameters, and compare with experimental results.