Herein, a facile approach toward transforming a 2D polypropylene flexible mesh material into a 4D dynamic system is presented. The versatile platform, composed by a substrate of knitted fibers of isotactic polypropylene (iPP) mesh and a coating of thermosensitive poly(N‐isopropylacrylamide‐co‐N,N’‐methylene bis(acrylamide) (PNIPAAm‐co‐MBA) hydrogel, covalently bonded to the mesh surface, after cold‐plasma surface treatment and radical polymerization, is intended to undergo variations in its geometry via its reversible folding/unfolding behavior. The study is the first to trace the 3D movement of a flat surgical mesh, intended to repair hernia defects, under temperature and humidity control. An infrared thermographic camera and an optical microscope are used to evaluate the macroscopic and microscopic structure stimulus response. The presence of the PP substrate and the distribution of the gel surrounding the PP threads, affect both the PNIPAAM gel expansion/contraction as well as the time of folding/unfolding response. Furthermore, PP‐g‐PNIPAAm meshes show an increase in the bursting strength of ≈16% with respect to the uncoated mesh, offering a strongest and adaptable system for its future implantation in human body. The findings reported offer unprecedented application possibilities in the biomedical field.

Fires can be an important hazard for the safety of chemical and process industries. Particularly, pool fires are the most frequent fire scenarios in such facilities and can affect other equipment of the plant with severe consequences due to the domino effect. During the last decades, simplified fire modelling tools were used to predict some of the harmful effects that hydrocarbon pool fires may entail. Although these can be applied to limited number of scenarios, they cannot cover the overall characteristics governing the fire behaviour. Computational Fluid Dynamics (CFD) modelling may provide more detailed insights of the related fire effects, may consider complex geometries and may represent from small to large-scale fires. However, simulation results should be firstly compared to experimental measurements in order to assess the predictive capabilities of these tools. This paper investigates the predictive capabilities of CFD modelling when performing a priori simulations of large-scale hydrocarbon pool fires. The main objective is to assess the fire effects prediction performance of two CFD codes that may be used to evaluate the hazard of hydrocarbon pool fires. FLACS-Fire and FDS codes have been used to simulate large-scale pool fires (1.5, 3, 4, 5 and 6 m-diameter) of diesel and gasoline fuels in unconfined environments. Given the notable differences between the mathematical methods applied to solve the CFD sub-models, the mesh resolution and the boundary conditions in each investigated tool, this study is not aimed at directly comparing both codes (i.e. using identical sub-models choices). However, the present CFD analysis is intended to reveal the potential of each software separately by applying the most appropriate modelling options for each tool. Based on a qualitative assessment of the predictions and a quantitative error estimation of the variables measured (i.e. flame temperature, burning rate, heat flux, flame height, flame surface, and surface emissive power), the main strengths and weaknesses of FLACS-Fire and FDS are identified when modelling hydrocarbon pool fires.

ProstateAnalyzer enables experts to manage prostate cancer patient data set more efficiently. The tool allows delineating annotations by experts and displays all the required information for use in diagnosis. According to the current European Society of Urogenital Radiology guidelines, it also includes the PI-RADS structured reporting scheme.