Development and characterisation of microporous biomimetic scaffolds loaded with magnetic nanoparticles as bone repairing material

Fine-tuning of the scaffolds structural features for bone tissue engineering can be an efficient approach to regulate the specific response of the osteoblasts. Here, we loaded magnetic nanoparticles aka superparamagnetic iron oxide nanoparticles (SPIONs) into 3D composite scaffolds based on biological macromolecules (chitosan, collagen, hyaluronic acid) and calcium phosphates for potential applications in bone regeneration, using a biomimetic approach. We assessed the effects of organic (chitosan/collagen/hyaluronic acid) and inorganic (calcium phosphates, SPIONs) phase over the final features of the magnetic scaffolds (MS). Mechanical properties, magnetic susceptibility and biological fluids retention are strongly dependent on the final composition of MS and within the recommended range for application in bone regeneration. The MS architecture/pore size can be made bespoken through changes of the final organic/inorganic ratio. The scaffolds undertake mild degradation as the presence of inorganic components hinders the enzyme catalytic activity. In vitro studies indicated that osteoblasts (SaOS-2) on MS9 had similar cell behaviour activity in comparison with the TCP control. In vivo data showed an evident development of integration and resorption of the MS composites with low inflammation activity. Current findings suggest that the combination of SPIONs into 3D composite scaffolds can be a promising toolkit for bone regeneration.     

A Logic for Conditional Local Strategic Reasoning

Journal of Logic, Language and Information - We consider systems of rational agents who act and interact in pursuit of their individual and collective objectives. We study and formalise the...     

Mechanics-aided digital image correlation for the investigation of piezoelectric and ferroelectric behaviour of a soft PZT

The strain response of a polarised PZT was characterised using Digital Image Correlation (DIC). The DIC algorithm is based on a global approach and regularises the displacement field using the balance equations of solid mechanics. The measurement error is reduced by correcting the displacements that are mechanically not admissible. A ferroelectric test showed that the standard deviations of strain fields remain mostly under 1.2 × 10^?4 for an element size of 64 px. The standard deviation on the average value is 3 × 10^?6. The strain field is homogeneous and its average value is consistent with the strain obtained from a CCD laser measurement device. The longitudinal strain, transverse strain and polarisation response of the PZT were measured for bipolar and unipolar loadings ranging from 50 to 5000 V/mm. Material properties were extracted from these measurements. This work shows the advantages of a novel 2D-DIC algorithm for piezoelectric strain characterisation.     

LSMAT Least Squares Medial Axis Transform

The medial axis transform has applications in numerous fields including visualization, computer graphics, and computer vision. Unfortunately, traditional medial axis transformations are usually brittle in the presence of outliers, perturbations and/or noise along the boundary of objects. To overcome this limitation, we introduce a new formulation of the medial axis transform which is naturally robust in the presence of these artefacts. Unlike previous work which has approached the medial axis from a computational geometry angle, we consider it from a numerical optimization perspective. In this work, we follow the definition of the medial axis transform as ‘the set of maximally inscribed spheres’. We show how this definition can be formulated as a least squares relaxation where the transform is obtained by minimizing a continuous optimization problem. The proposed approach is inherently parallelizable by performing independent optimization of each sphere using Gauss–Newton, and its least‐squares form allows it to be significantly more robust compared to traditional computational geometry approaches. Extensive experiments on 2D and 3D objects demonstrate that our method provides superior results to the state of the art on both synthetic and real‐data.     

Distribution Update of Deformable Patches for Texture Synthesis on the Free Surface of Fluids

We propose an approach for temporally coherent patch‐based texture synthesis on the free surface of fluids. Our approach is applied as a post‐process, using the surface and velocity field from any fluid simulator. We apply the texture from the exemplar through multiple local mesh patches fitted to the surface and mapped to the exemplar. Our patches are constructed from the fluid free surface by taking a subsection of the free surface mesh. As such, they are initially very well adapted to the fluid's surface, and can later deform according to the free surface velocity field, allowing a greater ability to represent surface motion than rigid or 2D grid‐based patches. From one frame to the next, the patch centers and surrounding patch vertices are advected according to the velocity field. We seek to maintain a Poisson disk distribution of patches, and following advection, the Poisson disk criterion determines where to add new patches and which patches should e flagged for removal. The removal considers the local number of patches: in regions containing too many patches, we accelerate the temporal removal. This reduces the number of patches while still meeting the Poisson disk criterion. Reducing areas with too many patches speeds up the computation and avoids patch‐blending artifacts. The final step of our approach creates the overall texture in an atlas where each texel is computed from the patches using a contrast‐preserving blending function. Our tests show that the approach works well on free surfaces undergoing significant deformation and topological changes. Furthermore, we show that our approach provides good results for many fluid simulation scenarios, and with many texture exemplars. We also confirm that the optical flow from the resulting texture matches the fluid velocity field. Overall, our approach compares favorably against recent work in this area.     

Spatial Charge Separation as the Origin of Anomalous Stark Effect in Fluorous 2D Hybrid Perovskites

2D hybrid perovskites (2DP) are versatile materials, whose electronic and optical properties can be tuned through the nature of the organic cations (even when those are seemingly electronically inert). Here, it is demonstrated that fluorination of the organic ligands yields glassy 2DP materials featuring long‐lived correlated electron–hole pairs. Such states have a marked charge‐transfer character, as revealed by the persistent Stark effect in the form of a second derivative in electroabsorption. Modeling shows that electrostatic effects associated with fluorination, combined with the steric hindrance due to the bulky side groups, drive the formation of spatially dislocated charge pairs with reduced recombination rates. This work enriches and broadens the current knowledge of the photophysics of 2DP, which will hopefully guide synthesis efforts toward novel materials with improved functionalities.     

Volume-based large dynamic graph analysis supported by evolution provenance

We present an approach for the visualization and interactive analysis of dynamic graphs that contain a large number of time steps. A specific focus is put on the support of analyzing temporal aspects in the data. Central to our approach is a static, volumetric representation of the dynamic graph based on the concept of space-time cubes that we create by stacking the adjacency matrices of all time steps. The use of GPU-accelerated volume rendering techniques allows us to render this representation interactively. We identified four classes of analytics methods as being important for the analysis of large and complex graph data, which we discuss in detail: data views, aggregation and filtering, comparison, and evolution provenance. Implementations of the respective methods are presented in an integrated application, enabling interactive exploration and analysis of large graphs. We demonstrate the applicability, usefulness, and scalability of our approach by presenting two examples for analyzing dynamic graphs. Furthermore, we let visualization experts evaluate our analytics approach.

     

Usage metrics vs classical metrics: analysis of Russia’s research output

This paper discusses the results of a pilot project investigating Russian scholarly publications using the altmetric indicators “Usage Count Last 180 days” (U1) and “Usage Count Since 2013” (U2) introduced by Web of Science. We explored the relationship between citation impact and both types of usage counts. The data set consisted of 37,281 records (publications) indexed by SCI-E in 2015. Seven broad research areas were selected to observe citation patterns and usage counts. A significant difference was found between mean citations and mean usage counts (U2) in a few research areas. We discovered a significant Kendall rank correlation between the citation metrics and usage metrics at the article level. This correlation is particularly strong for the longer period usage metric (U2). We also analyzed the relationship between usage metrics and traditional journal-level citation metrics. Very weak correlation was observed.